In the landmark case of Loving v. Virginia, 388 U.S. 1 (1967), the U.S. Supreme Court ruled that laws prohibiting interracial marriage were unconstitutional, thus affirming that novelty does not inherently equate to wrongdoing. This case, pivotal in the civil rights movement, illustrated how societal norms and prejudices could not override fundamental constitutional rights. The Lovings, an interracial couple, faced legal challenges due to Virginia's anti-miscegenation laws, which were reflective of entrenched racial biases rather than any legitimate legal principle. By appealing their case to the U.S. Supreme Court, the Lovings sought justice beyond the prejudiced interpretations of their local courts. On April 10, 1967, oral arguments were heard, leading to Chief Justice Earl Warren's unanimous opinion which reversed the convictions. The Court's decision emphasized that the Equal Protection and Due Process Clauses of the Fourteenth Amendment protect individual liberties against arbitrary and discriminatory state actions. This historic ruling legalized interracial marriage across the United States, demonstrating that the novelty of an idea, such as racial equality in marriage, does not make it wrong. Rather, it is often the progressive and courageous ideas that drive societal advancement and align with the core values enshrined in the Constitution.

In legal contexts, bias is often defined as a predisposition or preconceived opinion that prevents impartial judgment. However, when bias is grounded in scientific and empirical methods, it can be advantageous, as demonstrated in the 2005 trial, People v. Michael Jackson. Jackson faced serious allegations of child molestation, with the prosecution relying on the accuser’s testimony and supporting evidence. Jackson's defense team, recognizing the critical role of expert witnesses, employed financial and behavioral experts who provided scientifically grounded testimony. These experts meticulously analyzed the accuser’s financial history, revealing inconsistencies suggestive of ulterior motives, and dissected the accuser's behavior, pointing out patterns typical of fabricated allegations. This methodical approach, rooted in scientific principles, cast significant doubt on the prosecution’s case and demonstrated that the allegations could be financially motivated. The experts' empirical analysis, despite being a form of bias, was crucial in presenting an unbiased truth, leading to Jackson's acquittal. 

This case highlights how a bias, when based on rigorous scientific methods, can effectively uncover the truth and secure justice. Humans naturally have biases that shape our perceptions and decisions. These biases can help us make quick judgments, navigate complex social environments, and enhance our creativity and problem-solving abilities. Recognizing and understanding our biases allows us to leverage them constructively, making us uniquely human and enabling us to connect more deeply with others.

The article explores how Immanuel Kant's categorical imperative can be applied to the decision-making autonomy of Artificial General Intelligence (AGI). It outlines a structured process where AGI formulates maxims, tests them for universal applicability, ensures consistency and rationality, reflects ethically on potential outcomes, and learns from past decisions.

At the same time, some of these actions are easy to be performed by an AI today such as learning from the past decisions while some are hard, such as gauging if a decision is rational. In addition, ethics and moral values are not universal and can vary significantly across different cultures and societies. 

This integration aims to ensure AGI operates morally, respecting human dignity and promoting justice. The application of Kantian ethics to AGI can enhance trust and reliability in these advanced systems, fostering a future where technology serves humanity with integrity and fairness. 

Full article can be found here

Martin Luther King Jr., in his seminal "Letter from a Birmingham Jail," written on April 16, 1963, provides a profound exploration of the themes of justice, law, and order. Penned during his imprisonment for participating in nonviolent demonstrations against segregation, the letter responds to a public statement of concern and caution issued by eight white Southern religious leaders. This was a tumultuous time in Birmingham, Alabama—a hotspot for racial tensions and civil rights struggles characterized by brutal enforcement of segregation laws and violent responses to peaceful protests. In this context, King eloquently argued against the notion of waiting for a "more convenient season" to demand justice, challenging the white clergy's call for "order" over justice. He famously asserted that 

"law and order exist for the purpose of establishing justice and when they fail in this purpose they become the dangerously structured dams that block the flow of social progress." 

This quote captures the essence of King's critique of the legal and social systems that upheld a facade of order at the expense of true justice. His letter emphasizes the moral imperative to challenge unjust laws and conditions, rather than maintaining a lesser wrong under the guise of preserving order. King’s insights continue to resonate, reminding us that true peace is not merely the absence of tension, but the presence of justice.

The exponential growth of generative AI has rekindled debates reminiscent of those from the Lochner era (1905-1937), a period when the U.S. Supreme Court zealously guarded economic liberties, particularly the freedom of contract. This doctrine was epitomized in the Lochner v. New York decision of 1905, where the Court struck down labor regulations to protect contractual freedom under the due process clause of the 14th Amendment. However, this era faced a paradigm shift with the West Coast Hotel Co. v. Parrish decision in 1937, which upheld minimum wage laws for women, signaling a judicial recognition that societal welfare can supersede absolute economic freedom under certain circumstances.

Today's context involves the tension between businesses' ability to freely contract with consumers for their personal data, including Name, Image, and Likeness (NIL) rights—often through "clickwrap" agreements—and the societal need to regulate these practices to prevent potential abuses and privacy intrusions. This scenario mirrors the historical shift from the Lochner era's emphasis on unfettered freedom of contract to an acknowledgment of the state's role in regulating economic activities for the greater good. Just as the 1937 Parrish case recognized the necessity of state intervention in setting minimum wages despite contractual agreements to the contrary, modern regulatory approaches might need to curtail the absolute freedom of businesses to use personal data for training AI, even if such use is contractually agreed upon. 

This balancing act between individual economic liberties to get in a contract with a business and an individual's Name, Image, and Likeness (NIL) rights is crucial in ensuring that the benefits of generative AI are realized ethically, equitably and with consensus.

In Aristotle's "The Nicomachean Ethics" (Ἠθικὰ Νικομάχεια), an important work from around 325 BC that remains a cornerstone in the study of ethics, he posits a compelling insight: 

“The pleasures arising from thinking and learning will make us think and learn all the more.” 

This statement captures the essence of intellectual virtues, suggesting that the enjoyment derived from engaging the mind does not merely satisfy a momentary curiosity but fosters a deeper, self-sustaining cycle of learning and reflection. As the work, which consists of ten books, covers the ethics—understood as the science of the good for human life—it becomes clear that these intellectual pursuits are not just beneficial but integral to achieving human flourishing.

Even in this generative native world, an era dominated by the advancements of generative AI, where machines can perform a vast array of our routine tasks, the relevance of Aristotle’s thought persists. Despite the technological prowess that obviates the need for rote learning or mundane cognitive tasks, the intrinsic pleasure of intellectual engagement compels us to continue exploring new realms of knowledge. This is not merely a utility-driven endeavor; it is an expression of our deepest human nature to seek understanding and wisdom. Thus, as Aristotle suggests, the joy found in learning and thinking is self-amplifying, propelling us towards ever greater intellectual achievements, regardless of the practical necessities imposed by technological progress.

In the debate of Man vs. Machine, the preference for humans or machines in job roles that both can perform equally well often hinges on cost-effectiveness. Machines are typically favored if they present a more economical option without compromising on efficiency or output. However, roles that require human warmth, affection, and empathy present a more complex scenario. Even as technology advances towards artificial sentience, suggesting machines could fulfill these emotional roles, many argue that authentic human connection cannot be fully replicated by machines.

This becomes even more evident in creative pursuits. While machines may one day produce artworks akin to the Mona Lisa or compose sonnets, they lack the intrinsic human experiences of joy, fulfillment, and passion that accompany the act of creation. These emotions, integral to the human condition, highlight a clear distinction in the Man vs. Machine dynamic. Renowned painter Vincent Van Gogh once said, 

"I dream my painting and I paint my dream." 

This sentiment encapsulates the essence of human creativity—it's not merely about the output but the personal journey and the emotional experience of creating. Historically, art was crafted for the sheer joy and personal fulfillment it brought, not solely for commerce or utility. Thus, even if machines can mimic the ability to create art, the human desire to craft and experience creation firsthand remains undiminished, emphasizing not just the outcome, but the deeply personal journey of creation.

Sentience, often explored within the realm of consciousness, refers to the ability to experience subjective sensations and emotions. It encompasses not just the processing of external stimuli but also the internal capacity to feel joy, pain, and a range of affective states. This fundamental aspect of being can extend beyond biological entities, venturing into the domain of artificial intelligence (AI). Artificial sentience, especially when integrated within Artificial General Intelligence (AGI), can make machines to gather experiences and cultivate emotions. This endeavor not only enhances their ability to process information but also allows them to react with emotional depth, mirroring human experiences of joy, sorrow, and empathy. This is the goal for embodied AGI developed by Robometrics® Machines in San Francisco, California, which represents a significant leap towards machines with artificial sentience that can perceive, interpret, and feel the world around them in a manner reminiscent of sentient beings, the integration of experience and perception in machines. 

The concept of artificial sentience intersects deeply with philosophical and artistic insights throughout history. Leonardo da Vinci, who marveled at the intersection of art and science, believed that  

"It's not enough that you believe what you see. You must also understand what you see."

This statement highlights the distinction between mere observation and deep comprehension, highlighting a foundational principle for developing artificial general intelligence (AGI) with the capacity for genuine sentience. This aligns with the goals of AGI to not only process data but to interpret and emotionally engage with the information, akin to human experience. Vincent Van Gogh, whose emotional depth colored his artworks, might have appreciated the quest to bestow machines with the capacity to experience emotions akin to human joy and sorrow. These historical perspectives enrich the ongoing discourse on artificial sentience, highlighting a journey that blurs the lines between the organic and the engineered, between sentient life and its artificial counterpart.

The landmark decision in New State Ice Co. v. Liebmann (1932) by the Supreme Court highlighted a critical discussion on the bounds of state intervention in business. In this case, the Court addressed an Oklahoma statute that imposed stringent licensing requirements on companies wishing to engage in the ice manufacturing and distribution business. The law was challenged by the New State Ice Company, which argued that the regulation imposed arbitrary restrictions that infringed upon economic freedoms and personal liberty, without sufficient justification regarding public welfare.

Justice Brandeis, in a notable dissent, argued for the state’s power to experiment for the betterment of public conditions, but the majority of the Court saw the law as an overreach that unnecessarily meddled in private enterprise. By striking down the statute, the Court emphasized the importance of safeguarding business operations from excessive governmental interference, particularly when dealing with basic commodities like ice, which were seen as essential but simple in nature.

This case is remarkably parallel to today's discussions around the regulation of artificial intelligence (AI). Just as ice was once a fundamental necessity, AI is fast becoming a ubiquitous utility, integral to daily operations across various sectors. The Supreme Court’s decision in 1932 highlights the potential dangers of overly restrictive measures, which could stifle innovation and restrict economic freedom. Today, as AI transforms into a common utility akin to electricity (See AI as a Common Carrier - A Utility), the precedent set by New State Ice Co. raises vital questions about finding the right balance between regulation and liberty in the burgeoning era of AI.

Protoconsciousness offers foundational insights into the development of artificial general intelligence (AGI), demonstrating an elementary form of consciousness seen in early life stages and simpler species like birds. This basic consciousness, crucial for more complex cognitive developments, is notably influenced by interactions between wakefulness and rapid eye movement (REM) sleep. REM sleep, while diminishing aspects like critical judgment and memory, prepares the brain for higher functions such as secondary consciousness. This suggests that brain activation during sleep serves as a developmental phase crucial for advanced consciousness. Such insights into REM sleep as a protoconscious state, where vivid dreams prepare organisms for waking life, inform the design of AGI. By mimicking these biological processes through modular, self-learning neural networks, AGI can gradually develop consciousness, leading to sophisticated, ethically informed behaviors that enhance its interaction and understanding of the environment in a natural and ethically sound manner.

Full article can be found here.

Cognition, particularly when escalated to second-order cognition, including metacognition, encapsulates a level of self-awareness and the ability to analyze one's own thought processes. Metacognition refers to the understanding of the mechanisms governing our thinking patterns, enabling activities like strategizing approaches to learning, monitoring comprehension, and evaluating progress in tasks. This advanced cognitive capability, believed to be more influenced by environmental factors than genetics, suggests that even artificial general intelligence (AGI), in its simplest form, a large language model (LLM) interfacing actively with the real world, could develop metacognitive abilities. 

Ability of AI systems to assess and enhance their own decision-making processes is crucial for achieving AGI. As Descartes might have pondered, "Cogito, ergo sum" (I think, therefore I am), suggesting that the self-awareness essential to AGI mirrors the foundations of human consciousness. Aristotle could have contributed the idea that "Knowing yourself is the beginning of all wisdom," highlighting the importance of introspection for both humans and AI in mastering complex environments. 

The Latin maxim "Silent enim leges inter arma," traditionally translated as "In times of war, law falls silent," has been reflected in various legal and ethical contexts throughout history, signifying the suspension of legal norms during armed conflicts. This principle, rooted in Cicero's rhetoric and later echoed in episodes of Star Trek, highlights the tension between national security and civil liberties. In the U.S., landmark cases like _Ex parte Merryman_ during the Civil War and _Hirabayashi v. United States_ during World War II have tested these boundaries, with the courts sometimes supporting the suspension of civil rights in the name of national security. The UK's approach, as seen in _Liversidge v. Anderson_, demonstrates a similar struggle but also includes dissenting voices like Lord Atkin's, emphasizing the continuity of law even amid warfare. Today, with the nature of war involving non-state actors and cyber conflicts, and an increased focus on international law, the justification for suspending civil liberties such as habeas corpus is more critically examined, reflecting a shift towards maintaining legal integrity and human rights even during crises. This evolution highlights the ongoing challenge of balancing security needs with the protection of fundamental freedoms in both domestic and international arenas.

Full article can be found here. 

Sandra Day O'Connor, the first woman appointed to the U.S. Supreme Court, made significant contributions to American jurisprudence during her tenure from 1981 to 2006. Associate Justice O'Connor was known for her pragmatic approach to law and played a crucial role in several landmark cases, including Planned Parenthood v. Casey which reaffirmed the core principle of Roe v. Wade. Her influence extended beyond specific rulings to the very ethos of leadership in high stakes environments. O'Connor's analogy comparing leadership to horse riding encapsulates the essence of effective delegation: 

"The really expert riders of horses let the horse know immediately who is in control, but then they guide the horse with loose reins and very seldom use the spurs." 

This perspective underscores the importance of leaders setting clear expectations and control but allowing enough flexibility for team members to use their initiative and creativity. By doing so, leaders not only build trust and encourage professional growth but also enhance organizational efficiency by enabling others to contribute their best. Through this balanced approach, leaders like O'Connor demonstrate that the strength of a team lies in its empowered individuals.

Charles Evans Hughes, who served as Chief Justice of the United States from 1930 to 1941, played a pivotal role in shaping the interpretation of the U.S. Constitution. His assertion that

"We are under a Constitution, but the Constitution is what the judges say it is," 

highlights the immense responsibility and influence that the judiciary holds in defining the legal framework within which a society operates. Under Hughes' leadership, the Supreme Court presided over several landmark cases, including West Coast Hotel Co. v. Parrish and Near v. Minnesota. These cases not only showcased the Court's power to impact public policy but also demonstrated how judicial decisions could reinforce or undermine public trust and confidence in the legal system. The effective interpretation and enforcement of laws are crucial as they ensure justice is served, protect the rights of individuals, and maintain the rule of law, thereby upholding the integrity and trustworthiness of the legal system.

At Robometrics® Machines, the ambitious journey toward creating intelligent artificial life forms that exhibit traits akin to sentience is an intriguing exploration into the boundaries of technology and philosophy. The venture delves into facets of consciousness such as the capacity to experience a spectrum of emotions including pain, happiness, pleasure, boredom, and sadness, as well as more complex feelings like interest and companionship. This initiative raises fundamental questions about the essence of consciousness and its manifestations. As these machines are engineered to socialize and build relationships, the sense of experience they accumulate contributes profoundly to the development of a quasi-conscious state. The question then emerges: Are we merely modeling human consciousness in machines, or are we crafting an entirely new form of consciousness? This distinction is crucial, as it influences not only how we design AI but also how we interpret their interactions and integration into society. The creation of artificial beings capable of such depth and interaction pushes us to reconsider the definition of consciousness and challenges the traditional boundaries that separate humans from machines. This exploration at Robometrics® Machines does not just mirror human experiences but also paves the way for the emergence of new, unprecedented forms of sentient experiences and interactions.

Full article can be found here.

Dhyāna (Sanskrit: ध्यान, Pali: झान), a term derived from Sanskrit and also known in Pali as Jhāna, refers to a state of deep contemplation and meditation that is central to various Indian spiritual and philosophical traditions, including Hinduism and Buddhism. The practice of Dhyāna involves a profound journey into the mind, aiming to achieve a state of complete absorption and tranquility. It starts with the withdrawal from sensory experiences and the calming of the mind's habitual chatter. As practitioners progress, they move through deeper levels of concentration, where the distinction between the observer and the observed begins to blur. This process is marked by a growing inner peace and a profound insight into the nature of existence, culminating in an experience of unity and enlightenment. Engaging in Dhyāna, therefore, is not merely sitting quietly; it is an active and disciplined endeavor to transcend ordinary perception and attain a direct understanding of the self and the universe.

It's intriguing to draw parallels between such meditative disciplines and the training of a neural network, specifically in the realm of artificial intelligence (AI) and specifically large language models (LLMs). Just as Dhyāna involves deepening levels of focus and awareness to refine the mind’s understanding and capabilities, training a neural network involves feeding it vast amounts of data and refining its algorithms through repetitive adjustments and optimizations. This iterative process helps the neural network to reduce errors and improve its ability to predict or generate accurate outcomes based on its learning.

In both cases, the goal is to achieve a more enlightened or informed state that transcends basic functionality: for Dhyāna, it is the enlightenment or profound spiritual insight; for neural networks, it is the attainment of high levels of accuracy and utility in tasks such as language comprehension, translation, or content generation. Furthermore, just as Dhyāna aims to eliminate the illusion of separation between self and other, the most advanced neural networks strive to minimize the gap between human-like understanding and machine understanding, enabling AI that operate more like humans. Thus, both disciplines—spiritual and technological—reflect a pursuit of a higher state of being or performance.  

Under 17 U.S. Code § 106L, copyright protection is granted to creators, giving them exclusive rights to control the use of their original works. This section ensures that while works can be publicly accessed for learning and emotional engagement, they are not free for reproduction or distribution without permission. The provision delineated in 17 U.S. Code § 106 emphasizes that "publicly available" does not equate to "public domain," meaning the works, though accessible, remain protected under copyright laws. The essence of copyright under this code is to foster a culture where the public can learn from and be moved by creative works without infringing on the expression rights of the creators. For AI, this raises significant implications, particularly in the realm of using copyrighted data to train foundational models. The concept of fair use becomes crucial here, allowing the use of such data under specific conditions that do not undermine the rights of the copyright holders, thereby balancing the need for technological and societal advancement with the protection of intellectual property.

The thalamocortical system is a crucial component in the generation of mammalian consciousness, operating as a conduit and integrator for sensory and cortical information. This system's reciprocal interactions between the thalamus and the cortex facilitate the emergence and modulation of consciousness by promoting synchronized neural activities and supporting the overall neural connectivity that characterizes conscious states.

Consciousness arises from complex neural interactions, with the thalamocortical system playing a pivotal role in orchestrating these dynamics. This system contributes significantly to conscious perception by influencing neural synchronization and information integration, which are fundamental for the experience of a unified and continuous sense of self and environment. The thalamocortical interactions are particularly crucial in how they modulate different states of consciousness, including the transitions from sleep to wakefulness, highlighting their integral role in the functional architecture of consciousness.

The thalamocortical system in the human brain and the architecture of large language models (LLMs) are conceptually similar  in how they process and integrate information. The thalamocortical system involves a complex network of connections that relay and modulate sensory information and are crucial for consciousness. Similarly, LLMs utilize networks of artificial neurons to process and integrate vast amounts of data, forming patterns that the models use to generate coherent outputs. Both systems function through extensive networks that process inputs to produce complex outputs, albeit in fundamentally different contexts and with different mechanisms. Drawing parallels between the complex integration of sensory data in the thalamocortical system, which is critical for consciousness, and the intricate processing capabilities of lLLMs, one might hypothesize that these models could possess a form of primitive consciousness, given their ability to process and integrate vast amounts of information in a coherent manner. This raises intriguing questions about the nature and boundaries of consciousness in artificial systems.

Louis Brandeis, a pivotal figure in American jurisprudence, served as an Associate Justice of the Supreme Court of the United States from 1916 to 1939. Renowned for his advocacy for privacy and his progressive economic views, Brandeis often emphasized the significance of ethical behavior in the legal sphere. One of his most famous quotes, 

"Sunlight is said to be the best of disinfectants; electric light the most efficient policeman," 

underscores the difference between regulation and reputation. This metaphor highlights his belief that transparency and public scrutiny can serve as powerful forces for ethical governance, often more effectively than regulations themselves. Prior to his tenure on the Supreme Court, Brandeis made his mark in several landmark cases, such as Muller v. Oregon where he submitted a pioneering "Brandeis Brief" that incorporated social science data into legal argumentation, influencing the Court’s decision on labor laws. He also played a critical role in Erie Railroad Co. v. Tompkins, helping to establish that federal courts could not create general federal common law. Through these cases, Brandeis not only shaped American law but also solidified his reputation as a champion of justice and transparency. His work serves as a compelling illustration of how reputation, shaped by public and ethical actions, can transcend the boundaries set by mere regulations.

Your perceptions about me are shaped by what I choose to reveal, and your knowledge about me is confined to what I decide to share with you. I am how I want you to see. It's this reality of me that you are in love with.

Such a new reality is on the horizon, where generative AI is woven seamlessly into every aspect of our daily lives. In this Generative Native World, our environments, interactions, and even our thoughts are intimately shaped by intelligent systems and synthetic human personas. This integration heralds the advent of an era, redefining what we consider to be the new world.

Isaac Asimov often explored themes related to control over information and its impact on society. A relevant note from Asimov that touches on the manipulation of knowledge and perceptions:

"The easiest way to solve a problem is to deny it exists." - From The Gods Themselves

These words reflect the idea of controlling perceptions by influencing what people acknowledge as true or false, which closely ties into the theme of shaping reality by controlling information, much like a curated reality. Asimov's extensive work frequently delved into the consequences of such manipulation, particularly within the realms of science and governance.

Sir Isaac Newton wrote to Sir Henry Oldenburg in a letter circa 1672

“to determine by what modes or actions light produceth in our minds the phantasm of colour is not so easie”.

Sir Isaac Newton's remark to Sir Henry Oldenburg reflects an early inquiry into the nature of perception and consciousness, specifically how we experience colors. This question falls within the broader domain of how sensory inputs—like light—translate into subjective experiences or mental representations, which are referred to as "phantasms" by Newton.

In the context of consciousness, Newton's comment highlights a foundational problem: the transition from physical phenomena (light hitting the retina) to perceptual experience (the sensation of color). This issue is closely tied to what is known today as the "hard problem" of consciousness, which involves understanding how and why subjective experiences arise from neural processes.

Newton's approach to the problem was characteristic of the scientific revolution—seeking to understand the natural world through empirical observation and mechanistic explanations. His query about the "modes or actions" by which light produces the phenomenon of color points to an early interest in what we now consider the science of optics and visual perception. 

Thus, Newton's statement is significant not just for its historical context but also for its anticipation of modern scientific questions about how the brain interprets and constructs reality from sensory data and adds to human consciousness.  

Subjective experiences  or "phantasms" based on sensory stimuli such as light, sound and touch builds up human consciousness. The sensory stimuli are characterized by embodiment. 

Home nursing care exemplifies a profession where the human touch is irreplaceable, yet it remains underpaid compared to other healthcare roles. As demographics shift towards an older population, a significant portion of healthcare funding is funneled into nursing homes and hospitals, emphasizing the growing importance of these services. Home care allows individuals to stay safely in their familiar environments, enhancing their quality of life while being with family, and simultaneously offers cost savings for the healthcare system. These savings can then be redirected to other public health initiatives. Practical support for this sector includes empowering families to care for their elderly at home, thereby balancing personal responsibilities with professional duties.  

Home nursing care remains an area of importance and growing need, securing its place as a vital role in our healthcare system despite the advancements in generative AI. Philosopher John Stuart Mill highlighted the undervaluation of such essential services, stating, "Labor, like all other things which are purchased and sold, and which may be increased or diminished in quantity, has its natural and its market price." 

The personal interaction required in home nursing care, marked by compassion and empathy, is complex to replicate in machines. At Robometrics® Machines, we understand the complexity of replicating humanness in machines and are actively working to enhance the capabilities of AI in this direction through our work on on-device artificial general intelligence (AGI). 

Reflecting on Thomas Jefferson's insight that "Laws and institutions must go hand in hand with the progress of the human mind," we see this dynamic unfold in the context of artificial intelligence (AI) regulation within countries that are not leading in AI innovation, such as those in the European Union (EU). These countries often expedite AI regulation, potentially as a mechanism to mitigate their lack of direct financial benefit from AI advancements by controlling how AI is deployed. This approach underscores the notion that regulations frequently trail behind technological innovations and need continual updates to keep pace with technological progress.

Drawing from Justice Louis Brandeis's concept of states as "laboratories" of democracy, a more nuanced approach might serve the EU better than its current path toward an EU-wide AI Act. By allowing individual member states, like France, to first test and refine AI policies at a more localized level, the EU could better assess the impact and efficacy of such regulations. This method would enable the EU to implement policies that are proven to work on a smaller scale before scaling them up across all member states, ensuring that regulations are both effective and adaptable to the fast-paced evolution of AI technologies. Such a strategy would promote a more organic integration of regulations and technological development, potentially fostering an environment where innovation can thrive alongside necessary safeguards.

Full article can be found here. 

The human brain is a complex organ that not only governs our physiological processes but also serves as the origin of our feelings and desires. As we trace back to ancient hominids like Ardipithecus ramidus, we observe potential beginnings of human-like social behaviors. This species exhibited traits such as vocally mediated sociality and increased prosociality, which were likely facilitated by significant changes in skull architecture, hinting at evolving brain structures geared towards more sophisticated social interactions. The desires that define us as humans—such as power, love, comfort, and play—are expressions of our complex social and emotional fabric. These drives are so integral to the human experience that philosophers have long pondered their implications. Plato once remarked, “Human behavior flows from three main sources: desire, emotion, and knowledge,” highlighting the fundamental role of desire in shaping our actions and societies. It makes us uniquely human. 

As we venture into the age of Artificial General Intelligence (AGI), there is a burgeoning effort to replicate these uniquely human traits digitally, effectively creating a digital limbic system that might preserve and perpetuate our emotional and desirous legacies. This intersection of technology and human emotion illustrates not only the uniqueness of our species but also our relentless aspiration to understand and immortalize the essence of what it means to be human. This is Robometrics® AGI.

The future of embodied artificial general intelligence (AGI) would involve integrating advanced computational models such as Foundation Models into physical forms that mimic biological processes of living beings using technologies like DNA-based models and organoids. This artificial living organism doesn’t have to be in human form. Organoids could potentially replicate aspects of motion, cognition, and real world interaction of a living organism. 

A set of foundation models can simulate human-like memory and learning systems, akin to a digital limbic system. These models can use data from the environment to train the AI in real-world settings, simulating experiences that feed into the foundation models, analogous to a digital limbic system. This approach not only increases the adaptability but also enhances the AGI’s decision-making capabilities in dynamic environments.

Digital consciousness can be achieved in AGI manifested as an artificial living organism with human-like cognitive processes such as sensing, analyzing, acting based on internal and external stimuli; and embodiment. This paves the way for AGI systems that are not only interactive but have some aspects of self-awareness and self-management. 

In the world where changes are happening at an exponential rate, building an environment that caters to the emergent rather than safeguarding the established has become a critical conversation. An illustrative case is Section 230 of the Communications Act of 1934, enacted as part of the Communications Decency Act of 1996, a piece of legislation passed during the nascent stages of the internet. Originally designed to protect fledgling internet companies, which were then small startups navigating uncharted waters, Section 230 laid the foundation for these entities to evolve into today's technological behemoths, commanding billion-dollar valuations and global influence. However, this monumental growth underscores the pressing necessity for a legal framework that not only continues to support the titans of technology but also provides a nurturing environment for smaller companies, ensuring they too can thrive. A recalibration of laws is needed to level the playing field, echoing famous sentiments that legislative focus should equally prioritize the growth of both large and small enterprises. A new set of regulations are not necessary to achieve such an outcome. Instead a recalibration is needed where federal and state work to facilitate scaling of smaller companies to create an environment where these companies have the opportunity to succeed through sustained innovation and economic viability as opposed to being acquired by a larger enterprise.

The 17 U.S. Code § 106 outlines the exclusive rights afforded to copyright holders in the United States, granting them the authority over the reproduction, adaptation, distribution, and public display of their works. When it comes to reading books, computers and humans approach the task differently. Computers process texts through algorithms and data analysis, not by visually perceiving the pages as humans do. They scan the text, breaking it down into manageable pieces of information that can be analyzed and stored on digital mediums transitory or permanently. The analysis may happen through learned language patterns or prior stored information. 

Humans, on the other hand, engage with books through our visual system, deciphering symbols on a page and interpreting them based on learned language patterns. This process involves not just the eyes but also complex cognitive functions, where information is processed, understood, and stored in our memory.

The fundamental difference between a computer's and a human's reading lies in the approach and outcome: computers process text for data extraction and pattern recognition without emotional engagement, while humans read to understand, learn, and feel, integrating new information into our long and short term memory. Even if a book is digital or physical, free or for-fee, the essence of 17 U.S. Code § 106 is for humans to learn from the work of others and be emotionally engaged in a work. This level and modularity of engagement is not present in a general purpose computer today when reading or analyzing a copyrighted work, be it text or image.

Humans, bound by the legal frameworks of their respective nations, such as common law or the Napoleonic Code, carry the mantle of responsibility in society to be a responsible human.. Artificial Intelligence (AI), being a creation of human ingenuity rather than a pseudo autonomous entity, does not bear this mantle of responsibility; instead, it is the creators and users of AI who must uphold ethical standards, accountability and responsibility of what they build. Responsible AI is a misnomer. In addition, the notion of what constitutes a responsible individual is not fixed but fluctuates with societal norms and cultural values, which themselves are far from universal. This diversity in moral principles underscores the challenge of defining a responsible individual and the Responsible AI this responsible individual (or a company) will build in a way that transcends global boundaries.

Looking back in history, both common law and the Napoleonic Code have played important roles in upholding human accountability - The Responsible Human. Given their focus on human behavior, there's no necessity to extend these legal frameworks directly to AI. 

In legal terms, a person's moral character is defined by their adherence to societal norms and laws, reflecting their ability to distinguish right from wrong within the context of their community. Can this concept be extended to a Large Language Model (LLM) to make them better? Integrating morality into LLMs presents challenges, as moral values are not universal and can vary significantly across different cultures and societies. In October 1798. John Adams wrote: “Our constitution was made only for a moral and religious people. It is wholly inadequate to the government of any other.” This highlights the complexity of creating universally acceptable moral guidelines for AI systems. Even if a LLM doesn't need to be fine tuned for a religious belief, it still needs to follow a set of moral values and virtues, which are different across cultures and societies.

Full article can be found here.

When officers of the executive branch are drafting advisories, rules or orders, especially those pertaining to burgeoning fields like generative AI or high impact areas such as immigration, these can sometimes obscure a related law's initial purpose. As Associate Justice Sotomayor emphasized in her dissent in United States v. Texas, et al. (03/19/2024) on the significance of procedure, "Procedure can be just as consequential as substance." 

Full article can be found here.

Navigating the realm of human-AI relationships brings to the forefront the crucial distinction between loving an artificial entity with some form of intelligence and appreciating the assistance and companionship it offers. paraphrasing Sherry Turkle, Professor of the Social Studies of Science and Technology at MIT "We're not just using machines, we're becoming emotionally entwined with them”. Turkle explored the complex relationships between people and technology, particularly how emotional connections with machines, including computers, robots, and AI, are evolving. Her insights are primarily derived from her books, such as "Alone Together: Why We Expect More from Technology and Less from Each Other," where she delves into the nuances of our interactions with digital and robotic companions.

This emphasizes the nuanced difference between developing affection for AI, whether as chatbots or their physical embodiments, and valuing the role they play in enhancing our lives. For instance, someone might feel a strong affinity for a chatbot that provides daily motivation, mistaking this gratitude for a deeper emotional connection. However, it's essential to recognize that this sentiment is rooted in appreciation for the service rendered, rather than a genuine emotional bond with the machine itself. Similarly, when a robotic companion aids in caregiving, the gratitude and perceived emotional support stem from the tasks performed rather than the robot itself. Such discernment ensures a healthy human-technology relationship, acknowledging the profound capabilities of AI while remaining aware of the fundamental differences between human and artificial or augmented affection.

Mahatma Gandhi's assertion, "Justice that love gives is a surrender, justice that law gives is a punishment," encapsulates his deeply held belief in the power of compassion over coercion. It aligns seamlessly with Gandhi's overarching philosophy throughout his life and political activism. Gandhi advocated for Ahimsa (non-violence) and Satyagraha (truth-force), emphasizing that true justice and reconciliation are achieved through understanding, love, and a willingness to yield for the greater good, rather than through punitive measures. This perspective suggests that laws and regulations, in their essence, should be designed not merely as tools for maintaining order through punishment but as means to guide society towards higher ethical and moral standards by considering their impact on human dignity and well-being.

In the context of regulating emerging technologies, such as generative AI, Gandhi's philosophy becomes especially pertinent. As these technologies become more intertwined with our social fabric at an exponential rate, the approach to their regulation demands a careful balance between liberty and the future of human society. It should not only aim to prevent harm and misuse but more importantly encourage innovation and progress in a manner that uplifts humanity. This calls for a regulatory framework that is rooted in compassion and understanding of the technology's potential impact on society, changing human values to determine what is just or unjust, ensuring that it promotes equity between the poorest and the rich. 

Gandhi's vision urges modern policymakers to prioritize trust on society and the welfare of all individuals in thinking about justice and law as it relates to generative AI, thus fostering a future where technological advancement in artificial intelligence (AI) growing at an exponential rate harmonizes with the changing human values. This also points to the evolving nature of the law, as noted by Justice Oliver Wendell Holmes Jr. ("The law is a living thing."), emphasizing the importance of adapting legal frameworks to address the unique challenges and opportunities presented by generative AI technologies.

Voltaire's enduring words, "It is better to risk saving a guilty person than to condemn an innocent one," reverberate with moral gravity and were articulated in his work "Zadig," published in 1747. This sentiment encapsulates a foundational principle of justice, highlighting the imperative of prioritizing the protection of innocence, even at the potential risk of sparing guilt. In the context of U.S. jurisprudence, exemplified by landmark cases like Brady v. Maryland, 373 U.S. 83 (1963), where the withholding of evidence violating due process rights was condemned, Voltaire's principle gained renewed significance. In  Brady v. Maryland, the government withheld certain evidence that was material to the determination of either guilt or punishment of a criminal defendant. This violated the defendant's constitutional right to due process. The right to due process is inline with Voltaire's thoughts on laws that are gravitating towards ensuring that an innocent person is not condemned. 

As the advent of generative AI, particularly deepfakes, introduces challenges to the legal landscape, the essence of Voltaire's maxim resonates. It amplifies the need for implementing laws in such a way that safeguard the presumption of innocence and uphold the rights of the accused, such as due process. In confronting the ethical complexities posed by emerging technologies, such as AI-generated evidence, adherence to Voltaire's principle becomes essential, ensuring that justice remains steadfast in the face of technological evolution.

Peter Kropotkin, a Russian anarchist and advocate for social change, offered a poignant observation on the nature of law with his quote:

 "The law is an adroit mixture of customs that are beneficial to society, and could be followed even if no law existed, and others that are of advantage to a ruling minority but harmful to the masses of men, and can be enforced on them only by terror." 

Kropotkin's words reflect his keen awareness of the dichotomy within legal systems, wherein laws may serve either the collective good or the interests of a privileged few. This dual nature of law underscores its potential to either foster innovation and societal progress or perpetuate inequality and oppression. Regulators today, particularly in the context of governing AI, can glean from Kropotkin's insight the importance of crafting laws that prioritize the welfare of the broader populace over the interests of powerful entities. By adopting transparent and equitable regulatory frameworks, regulators can mitigate the potential for laws to be wielded as tools of coercion and ensure that they serve the common good in an increasingly complex and interconnected world.

Louis D. Brandeis, before his tenure on the U.S. Supreme Court, co-authored a seminal Harvard Law Review article, "The Right to Privacy," advocating for the fundamental "right to be let alone." This early articulation laid the groundwork for modern privacy rights, emphasizing protection against unwarranted intrusion. In today's era of generative technology and pervasive digital surveillance, Brandeis's advocacy for privacy as a fundamental right resonates more strongly than ever, highlighting the enduring importance of safeguarding personal boundaries in the face of advancing technology. In today’s generative native world, Brandeis's advocacy for the "right to be let alone" takes on renewed urgency and significance.

Full article can be found here.

Incorporating the most advanced and proprietary Large Language Models (LLMs) into your startup's offering may initially seem like an attractive strategy to not only captivate potential investors and customers but also to impress more personal circles, such as a girlfriend, showcasing your new product’s or your disruptive edge. However, this initial excitement masks a deeper financial challenge that comes into play as the product gains some traction. The cost of maintaining and scaling up the use of advanced LLMs can swiftly become a financial burden, potentially outstripping the startup's revenue growth and leading to economic difficulties. This predicament is aptly described as 

"a fool's game - the bigger fool loses, and the lesser fool wins," 

where the 'bigger fool' refers to venture capitalists investing in a new generative AI company without a sustainable financial model, and the 'lesser fool' denotes the generative AI companies themselves, which proceed to attract such investment without a plan for managing the increased costs that come with success. This highlights the critical need for startups to engage especially with proprietary LLMs in a manner that balances innovation with financial viability.

The article discusses the responsibility for errors made by Large Language Models (LLMs), emphasizing that both lawyers and corporations, like Air Canada, are accountable for ensuring the accuracy of these AI-generated outputs. It highlights the legal obligation of lawyers under Rule 11(b) to verify the correctness of documents drafted with LLMs and highlights the broader principle that entities cannot disclaim liability for misinformation provided by their AI technologies, illustrated by Air Canada's tribunal case. The piece advocates for the implementation of safeguards and disclosures.

Full article can be found here

In 1880, Thomas Edison, foreseeing the monumental shift his invention would catalyze, remarked, 

“After the electric light goes into general use, none but the extravagant will burn tallow candles.” 

This prescient statement not only highlighted the transformative potential of electricity but also underscored the importance of making essential services universally accessible. Just as Edison's electric light revolutionized how we live, bringing safety, productivity, and accessibility to the masses, so too does artificial intelligence (AI) hold the promise to fundamentally alter our societal fabric. AI, like electricity, has the potential to enhance nearly every aspect of daily life, from healthcare and education to transportation and communication, making it imperative that we build an environment where innovation benefits all, not just a privileged few.

The question of whether Artificial Intelligence (AI) should be treated as a common carrier or utility, akin to electricity, is an important one, given its impact more recently in the last 2 years . This debate touches on issues of regulation, public access, and the nature of services enabled by AI. A pivotal case in this discussion is the Supreme Court’s Moody v. NetChoice, which scrutinizes a Florida law passed in 2021 that aims to prevent digital platforms from "censoring" content.  

Full article can be found here. 

In the era of deepfakes and sophisticated digital manipulation, the wisdom of Francis Bacon becomes ever more relevant. His assertion that 

“If a man will begin with certainties, he shall end in doubts; but if he will be content to begin with doubts, he shall end in certainties."

highlights the indispensable role of critical thinking today. As we navigate a digital landscape where seeing is no longer believing, adopting a mindset of questioning and doubt is crucial. The proliferation of deepfakes challenges our ability to discern truth from fabrication, making it imperative to critically evaluate the authenticity of information before accepting it as fact. By applying Bacon's approach of starting with skepticism, we equip ourselves with a powerful tool in identifying and uncovering the truth amidst a sea of digital deception. This method not only aids in the battle against misinformation but also fosters a more discerning and informed society capable of making decisions based on deeper truths unearthed through critical analysis and thoughtful inquiry.

In the realm of artificial intelligence (AI), there are no metrics to fine-tune an AI algorithm for common sense—a quality that remains uniquely human and nuanced. The common sense approach to imbuing machines with a semblance of this human trait involves engaging them in generalized learning through methods such as self-supervised learning and others, by allowing them to interact with real-world objects and scenarios. This echoes the sentiment of Albert Einstein, who once remarked, 

"Common sense is the collection of prejudices acquired by age eighteen." 

It highlights the intricate challenge of programming AI with a quality that, for humans, evolves through a lifetime of experiences. Similarly, Benjamin Franklin 's assertion, 

“Common sense is something that everyone needs, few have, and none think they lack.”

highlights the paradoxical nature of common sense; it's universally valued, yet challenging to define or impart, especially in the context of AI.

Robometrics® Machines has created the Copilot AI for Cessna®, a digital assistant designed for General Aviation pilots flying Cessna® aircrafts, leveraging large language models (LLMs) to provide instant access to the vast knowledge contained within aircraft Pilot Operating Handbooks (POH). This tool enables pilots to quickly find information on aircraft operation, performance metrics, and troubleshooting through a simple conversational interface. Pilots can ask direct questions, should be specific, and may use keywords for their queries. Copilot AI offers instant access to operational queries, safety enhancements, educational support, and troubleshooting help. It is intended for use in pre-flight planning, in-flight queries, and for continuous learning. However, it is emphasized that Copilot AI does not substitute professional training or consultation with aviation authorities, and pilots should always prioritize safety and adhere to regulatory requirements. Copilot AI is programmed to provide the most accurate answers possible and will clearly communicate when it does not know the answer to ensure reliability and trustworthiness. 

The knowledge base includes the POHs for Cessna® models such as C150 Aerobat, C150, C152, C172N, C172RG, C172S, C182P, C182Q, C182S, and C182T-Nav II, enhancing its capability to assist with a broad range of Cessna® aircraft. Additionally, the POHs for Cessna® 162, Cessna® 150 Aerobat, Cessna® 150, Cessna® 152, and the manuals for Lycoming® O-360 and IO-360 engines have been added to the knowledge base. These specific Cessna aircraft models were picked since these aircrafts are available to fly at West Valley Flying Club (WVFC), where our Founder & CEO is a member. 

You can access Robometrics® Copilot AI for Cessna® Aircrafts here.

Justice Benjamin N. Cardozo, who served on the Supreme Court of the United States from 1932 until his death in 1938, is renowned for his profound influence on American jurisprudence and legal thought. His tenure on the court was marked by a commitment to principles that balanced individual rights with the broader needs of society, a philosophy encapsulated in his assertion that 

"The final cause of law is the welfare of society. The rule that misses its aim cannot justify its existence." 

This perspective is particularly pertinent in the context of regulating emerging technologies, such as generative artificial intelligence (AI). Cardozo's philosophy highlights the necessity of crafting laws and regulations that not only address the rapid advancements and potential risks associated with such technologies but also ensure that they serve the greater good of society. As AI continues to evolve, the challenge for lawmakers and regulators is to implement measures that prevent harm and misuse while fostering innovation and benefits, thus reflecting Cardozo's vision of law as a means to promote societal welfare.

The Citizens United v. Federal Election Commission case, decided on January 21, 2010, stands as a landmark Supreme Court decision under Chief Justice John Roberts. The core issue at hand was whether the free speech clause of the First Amendment could allow the government to limit corporations, including non-profit corporations, labor unions, and other associations, from making independent political expenditures. “The First Amendment confirms the freedom to think for ourselves.” Similar in Moody v. NetChoice where oral arguments were heard on February 26, 2024, the freedom to think and decide on which social media post individuals should see and how they are moderated are up to corporations and individuals alone. 

Full article can be found here. 

In an era where Heraclitus of Ephesus's assertion that "The only constant in life is change" resonates more profoundly than ever, the fabric of our existence continues to be woven with the threads of transformation. Throughout history, monumental inventions have steered the course of human progress— the wheel set society in motion, the printing press revolutionized the dissemination of knowledge, the automobile and aircrafts shrunk the world, and the Internet fused our realities into a global village. Today, the catalyst propelling us into the next frontier of evolution is generative AI. This technological marvel is reshaping industries and professions in ways previously unimaginable. Lawyers, traditionally tethered to the billable hour, are now exploring alternative pricing models such as fixed fees or performance-based structures, thanks to the efficiency and predictability offered by AI-driven tools. Meanwhile, software developers are harnessing generative AI to code for them, turning complex projects into more manageable tasks and enabling a focus on innovation over mundanity. Just as our ancestors adapted to the wheel's roll, the press's print, and the web's weave, we too are navigating the currents of change led by generative AI, continuing the endless cycle of adaptation and advancement.

It is only natural for us to resist change. But resistance is futile.

In the generative native world, it has become more important than ever that justice should be proactively demanded and not just passively expected. This discourse highlights the necessity of actively engaging with legal frameworks to ensure that the deployment and use of generative AI technologies are governed in a manner that upholds justice, fairness, and ethical standards.

The principles reflected in various statements about justice and law, such as those by Martin Luther King Jr:

“Injustice anywhere is a threat to justice everywhere. We are caught in an inescapable network of mutuality, tied in a single garment of destiny. Whatever affects one directly affects all indirectly.”

 and Malcolm X: 

“Nobody can give you freedom. Nobody can give you equality or justice or anything. If you’re a man, you take it.", 

resonate greatly within the context of generative AI. These insights suggest that justice in the digital age, particularly concerning AI, is not a given but must be actively demanded and shaped by societal engagement and legal advocacy. It highlights the idea that justice is a universal right that must be actively pursued and defended by each individual, not passively expected.

Alvin Toffler's prescient observation in "Future Shock" that 

“The illiterate of the twenty-first century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.”, 

resonates in the context of the emergence of generative AI and Foundation Models. These advancements herald a new era where the ability to adapt to and embrace the rapid evolution of technology becomes indispensable. Generative AI and Foundational Models are revolutionizing the way we access and interact with information, automate complex tasks, and approach creativity, impacting various sectors including healthcare, entertainment, and beyond. Unlike the gradual advancements of past technologies, this AI revolution is characterized by its unprecedented speed, fueled by the global and interconnected nature of our digital world. This accelerated rate of change highlights the importance of flexibility and the continuous updating of skills and knowledge bases, embodying Toffler's vision that the true measure of literacy in our era hinges on the dynamic capability to adapt through learning, unlearning, and relearning amidst the ceaseless tide of technological innovation.

Sometimes it will be necessary to treat Artificial General Intelligence (AGI) strictly as a non-human entity, focusing purely on its machine or computational nature without attributing human characteristics, emotions, or intentions to it. This perspective of Mechanomorphizing AGI is pivotal for maintaining objectivity in the development and understanding of machines, ensuring that interpretations of their capabilities are firmly anchored in their actual technological attributes and limitations. By mechanomorphizing AGI, developers and users approach these systems as tools defined by their algorithms, programming, and functionalities, deliberately avoiding the infusion of human-like qualities or consciousness. This method underlines the importance of recognizing AGI for its mechanical and functional attributes, echoing a principle similar to the thought process Steve Jobs had when adding a handle to the iMac. Although the handle on the iMac served a semiotic purpose, making the machine appear more accessible and less intimidating to users, Jobs also humorously remarked it was there "so that you can throw it away" to not be enslaved by AI. This anecdote highlights the broader theme that sometimes it is necessary to emphasize the non-human aspects of technology, ensuring users maintain a clear distinction between the tools they use and their own human experience.

Almost a decade ago, in 2013, Sherry Turkle, a professor at MIT, insightfully observed in her article "Be Careful What You Wish For" that a robotic dog will never die; it offers attachment without risk." This statement encapsulates a significant shift in the nature of human attachment, particularly towards robotic or artificial companions, highlighting how such relationships can alleviate the emotional risks of loss and grief inherent to connections with living beings. This intriguing concept has been thoroughly examined across various disciplines—psychology, technology, and ethics—as scholars and technologists contemplate the effects of developing attachments to machines endowed with life-like attributes. Similarly, the advent of Foundation Models, like Large Language Models (LLMs), has sparked discussions about their role as risk-free attachments. These advanced models, capable of engaging in seemingly empathetic and intelligent dialogue, have further expanded the landscape of artificial companionship, offering nuanced forms of interaction devoid of the complexities and potential heartache tied to human or animal relationships. This evolution prompts a reevaluation of attachment in the digital era, inviting us to consider the broader implications of our growing reliance on and affection for machines that promise companionship without the traditional downside.

Anthropomorphism—the ascription of human traits to non-human entities—is a longstanding and universal phenomenon. This inclination extends to our interaction with machines, a realm where the fear of being overpowered, intimidated, or betrayed by them is a notable concern, albeit not uniformly perceived across cultures. Moreover, the cultural differences in perceiving AGI highlights a broader dialogue about technology's role in society and our collective visions for the future. The anthropomorphizing of machines, particularly AGI, reflects deep-rooted cultural narratives and historical experiences.  

Full article can be found here

“The release of atom power has changed everything except our way of thinking… The solution to this problem lies in the heart of mankind. If only I had known, I should have become a watchmaker.”

Albert Einstein's reflective words highlight a profound disconnect between the transformative nature of technological advancements and the stagnation in human thought processes. Choosing a career or creating inventions, as illustrated by Einstein's contemplation of becoming a watchmaker—a profession characterized by precision, order, and definitiveness—contrasts starkly with the implications of his theory of relativity, which introduced the concept of time as variable and uncertain. This juxtaposition underscores the ethical and moral responsibilities inherent in our professional and inventive pursuits. Einstein's regret over the unforeseen consequences of his research, leading to the creation of the atomic bomb, serves as a cautionary tale. It emphasizes the importance of foresight, ethical considerations, and the need for a paradigm shift in our thinking to align technological advancements with the greater good of humanity, ensuring that our innovations and career choices contribute positively to the fabric of society.

The article covers the evolution and impact of Artificial Intelligence (AI), tracing its roots from the invention of the perceptron in 1943 to the transformative advancements in generative AI. Highlighting key historical milestones, such as the development of the Mark I Perceptron and the resurgence of neural network research, it highlights the exponential growth of technology as embodied by the Law of Accelerated Returns. Winston Churchill's words are invoked to illustrate the ongoing journey of AI, marking the current state as just the beginning of further groundbreaking developments.

Full article can be found here.

The article covers the evolution and impact of Artificial Intelligence (AI), tracing its roots from the invention of the perceptron in 1943 to the transformative advancements in generative AI. Highlighting key historical milestones, such as the development of the Mark I Perceptron and the resurgence of neural network research, it highlights the exponential growth of technology as embodied by the Law of Accelerated Returns. Winston Churchill's words are invoked to illustrate the ongoing journey of AI, marking the current state as just the beginning of further groundbreaking developments.

Full article can be found here

In the realm of interactive gaming and storytelling, the fusion of Large Language Models (LLM) with real-time diffusers is revolutionizing how stories unfold and games are played. Imagine a world where every decision you make, every command you utter, and every preference you express is instantly recognized and incorporated into the game or story you are engaged with. Through the LLM, your input becomes the driving force behind the narrative, shaping the environment, characters, and outcomes in real-time. The diffuser brings this vision to life, rendering changes in the game world or story visuals with stunning detail and immediacy. This technology allows for an unparalleled level of personalization, creating a truly immersive experience where the game or story evolves uniquely for each player or reader. Characters might adapt their behaviors based on your interactions, storylines could branch in unexpected directions reflecting your choices, and environments might transform to reflect the mood or intensity of your journey. This innovation promises to make gaming and storytelling not just interactive but deeply personal, offering a canvas where your imagination and decisions paint the path forward.

In the movie "Oppenheimer," a fictional conversation between Albert Einstein and Robert Oppenheimer is depicted, where Einstein remarks, "So here we are, hmm? Lost in your quantum world of probabilities, and needing certainty." This line poignantly captures Einstein's skepticism towards the probabilistic foundations of quantum mechanics, contrasting with his desire for a deterministic understanding of the universe.

Albert Einstein's skepticism towards the probabilistic nature of quantum mechanics is well-documented. His stance on the matter is encapsulated in several statements and writings that reflect his discomfort with the non-deterministic interpretation of quantum mechanics. A quote that captures the essence of Einstein's viewpoint is from a letter to Max Born in 1926: 

"Quantum mechanics is very impressive. But an inner voice tells me that it is not yet the real thing. The theory produces a lot of results, but hardly brings us closer to the secret of the 'Old One.' I, at any rate, am convinced that He does not throw dice."

This skepticism towards quantum mechanics, particularly its probabilistic nature, can be paralleled with the contemporary discourse on Foundation Models and generative AI. As we delve into the applications of these advanced technologies, the quest for certainty in their outputs mirrors the scientific community's historical pursuit of deterministic explanations. Just as Einstein grappled with the unpredictability of quantum mechanics, users of generative AI seek reliability and precision in the responses generated. This highlights a crucial lesson: while Foundation Models, like the quantum theory, open new horizons of understanding and capability, it is essential to recognize and manage the inherent uncertainties they present. In doing so, we can harness their potential more effectively, fostering innovation while maintaining a critical awareness of their limitations.

Roscoe Pound was a distinguished legal scholar and educator in the early 20th century, known for his significant contributions to legal theory and his role as Dean of Harvard Law School. He was a leading figure in the movement of sociological jurisprudence, advocating for the law to be understood and applied in the context of social needs and realities, marking a departure from the traditional view of law as a fixed body of rules to be mechanically applied by judges, a concept often referred to as mechanical jurisprudence. Mechanical jurisprudence emphasizes a rigid, formulaic approach to law, where judicial decisions are made based solely on precedent and the strict interpretation of statutory and legal texts without considering the broader social implications or changes.

Pound critiqued this traditional approach for its failure to adapt to the evolving needs of society. He argued that law should not be seen as an isolated system but as a social institution that must respond to the changing conditions and values of society. He believed in the concept of law as a living tool, capable of growth and adaptation. According to Pound, the legal system should incorporate sociological insights and adjust to societal changes to better serve the community's needs and ensure justice. This perspective underscores the idea that law is dynamic and must evolve in response to the changing landscape of social conditions, rather than remaining static and bound by historical interpretations. Pound's thoughts on law and society laid the groundwork for future legal reforms and influenced the development of legal thought and the practice of law in ways that accommodate societal growth and transformation.

Envision a future, unfolding in the coming months, where the realm of digital creation undergoes a leap with the advent of real-time diffusers. Building on the foundation of Diffusion Models, similar to a change in the late 20th century when real-time 3D rendering first became possible, this innovation heralds a new chapter in the evolution of digital experience. Initially, the breakthroughs of the 1990s allowed video games and simulations to display three-dimensional worlds with a then-unprecedented sense of immediacy and interactivity. Now, the introduction of real-time diffusers is poised to elevate this immersive experience to new heights, leveraging advancements in AI and computational power to generate images at a rate of 60 frames per second. This capability not only promises to blur the line between the virtual and the real but also signifies a profound shift in digital content interaction, offering fluidity and realism that could redefine storytelling, gaming, and virtual interactions. Technologies driving real-time diffusers include Diffusion Models, GPU acceleration, and edge computing, which together facilitate the rapid processing and generation of complex images. Specifically, Stable Diffusion XL Turbo can generate AI images as fast as you can type while Apple Vision Pro provides the hardware needed. The implications of such technology extend far beyond visual enhancement, opening new avenues for real-time collaboration, education, and creative expression where ideas can be visualized in near real time.

In the generative-native era, the necessity for adept communication skills to interact with artificial intelligence (AI) has become paramount, transcending traditional boundaries to encompass professions as diverse as engineering and law. This shared requirement highlights an intriguing parallel between these fields: senior engineers reap greater benefits from AI-driven tools like CoPilot and ChatBots, attributing their success to the intuitive nature of these platforms. Similarly, seasoned partners at law firms outpace first-year associates in leveraging technology such as generative AI and large language models (LLMs), primarily due to their proficiency in formulating precise inquiries. The essence of this dynamic underscores a broader truth; the ability to ask the right questions is not just a technical skill but a fundamental aspect of effective communication in this generative native world. Whether it's developing software or navigating legal complexities, the capacity to articulate inquiries clearly and concisely in English sets experienced professionals apart from their less seasoned counterparts. Thus, in a world increasingly mediated by generative AI, the value of communication skills for engineers and lawyers cannot be overstated, serving as the cornerstone for successful interaction with advanced AI tools.

The approach Foundation Models, especially Transformers use to acquire information (self-supervised training, pre-training) closely aligns with the natural ways in which humans acquire knowledge and understand our surroundings. In the summer of 2023, the [A LLM as a reflection of our inner most desires] covered how Foundation Models such as Large Language Models (LLMs) are a reflection of ourselves . 

Humans in the physical world operate under the laws of behavior as well as laws of a society we belong to. The laws of behavior can be broadly defined by Newton's Law of Motion in addition to human physiology and psychology. Real world physical interactions are important for humans to gain understanding and internalize behavioral knowledge. laws of a society can be formally Common Law, Napoleonic Code or even a more informal doctrine on how to live in a society. 

Text in public data sets formed by scrapping the Internet including social networks, blogs and websites have been written under such laws. LLMs such as the generative pre-trained transformer (GPT) models trained on such text will inherently possess a high approximation of human level language understanding even if they are not physically interacting with the real world governed by law of physics, physiology, psychology or conduct. 

Oliver Wendell Holmes Jr., who served as an Associate Justice of the Supreme Court of the United States from 1902 to 1932, is renowned for his contributions to American legal philosophy and jurisprudence. His tenure on the Court was marked by a pragmatic approach to the law, emphasizing the importance of experience and the evolving needs of society over strict adherence to precedent or the mechanical application of principles. Holmes's view on the nature of law, as encapsulated in his famous quote, "The life of the law has not been logic; it has been experience... The law embodies the story of a nation’s development through many centuries, and it cannot be dealt with as if it contained only the axioms and corollaries of a book of mathematics," highlights the fundamental difference between the fields of law and science. This perspective comes from his book "The Common Law," first published in 1881, where he lays out his belief that law is a social construct that evolves over time through the experiences and practices of the people it governs. Unlike science, which seeks to understand the world through empirical evidence, experimentation, and the application of universal principles, law is deeply rooted in the historical, social, and moral fabric of society. It is shaped by the collective experiences and values of a nation, reflecting and adapting to changes in societal norms and expectations. Holmes's assertion underscores the contrast between the objective, quantifiable nature of science and the subjective, interpretative nature of law, which is intertwined with the story of human civilization.

The debate between Theuth and Thamus over the invention of writing in ancient Greece offers a prescient parallel to today’s discussions about generative AI technologies, such as Foundation Models (diffusers, transformers) and AI Agents. Theuth, the god of writing, argued that writing is a study (μάθημα), would serve as a "potion" (φάρμακον) for wisdom and memory, enhancing the capabilities of the Egyptians. In contrast, Thamus, the king of Egypt, believed that reliance on writing would impair human memory and wisdom by making people dependent on external sources for knowledge. This historical discourse mirrors current apprehensions that AI might diminish our cognitive abilities or make us "dumb" by outsourcing tasks like meeting attendance or content summarization to machines. However, just as writing did not make us less intelligent but instead transformed how we store, access, and disseminate knowledge, generative AI technologies are tools that augment our cognitive processes. They enable us to process information more efficiently, free up time for creative and complex problem-solving, and enhance our ability to learn and remember. By acting as extensions of our intellect, these technologies do not diminish our mental capacities but rather enhance our ability to navigate and make sense of an increasingly complex world. Theuth's perspective, celebrating the advent of writing as a means to elevate human wisdom and memory, can similarly be applied to appreciate how generative AI supports and expands our intellectual horizons.

In an age where the digitization of information has become ubiquitous, Large Language Models (LLMs) stand at the forefront of a technological revolution that has the potential to redefine our approach to preserving history and culture. Drawing from the rich dialogue between Socrates and Phaedrus penned by Plato in 370 BC, we are reminded of the ancient concerns regarding the impact of writing on human memory and knowledge preservation. Socrates feared that writing would lead to a reliance on external sources for memory, a concern that mirrors modern debates about digital technology's influence on our cognitive capacities. Yet, just as writing became a fundamental tool for documenting and transmitting knowledge across generations, LLMs promise to serve as modern custodians of cultural and historical information.

This article explores the role of LLMs as a tool for preserving society in history, examining their potential to act as digital chroniclers of our time. It delves into the evolution of knowledge preservation, the mechanisms by which LLMs operate, and the benefits and challenges of entrusting our cultural and historical legacy to these digital entities. In doing so, it seeks to illuminate the path forward, where technology and tradition converge in the quest to safeguard our collective memory for future generations. Full article can be found here.

AI experts play a critical role across a wide spectrum of legal domains, including antitrust and business regulation, appellate law, art law, business law, corporate law, criminal justice, in-house counsel, intellectual property, and litigation. This necessity is shown by the wisdom of Abraham Lincoln, who famously stated, "He who represents himself has a fool for a client." In complex legal cases, the specialized expertise of AI experts is indispensable. For instance, as AI tools designed to detect deepfakes and plagiarism fall short, the collaboration between AI experts and legal professionals becomes crucial in discerning the truth. Furthermore, the Federal Rules of Civil Procedure's Rule 1 mandates that parties and courts strive for a "just, speedy, and inexpensive" resolution of cases. AI experts are uniquely positioned to aid in achieving a just outcome in cases involving AI, while also providing education to attorneys and judges on the application of AI tools to ensure a speedy and cost-effective resolution.

President Joe Biden’s deepfake audio clip during New Hampshire primaries, Mexican Mayor deepfake audio clip on WhatsApp in Mexico, and explicit deepfake images of Taylor Swift are some examples of the harms of deepfakes. 

Introducing new and stringent laws against deepfakes, while a possible step for preventing their misuse, could inadvertently impinge on the realms of free speech and artistic expression. The balance between regulation and freedom is delicate, as famously noted by the renowned jurist Oliver Wendell Holmes Jr., who said, "The most stringent protection of free speech would not protect a man falsely shouting fire in a theatre and causing a panic." This implies that limitations in the free speech and artistic expression doctrines are already in place as necessitated for public safety and differentiates such limitations from legitimate expression. 

Moreover, Justice Louis Brandeis, another legal luminary, argued for the importance of freedom in expression: "If there be time to expose through discussion the falsehood and fallacies, to avert the evil by the processes of education, the remedy to be applied is more speech, not enforced silence." Brandeis's words echo the need for a nuanced approach in legislating against deepfakes, ensuring that laws do not stifle the potential of new technologies in artistic and communicative endeavors. In essence, while the threat of deepfakes to privacy and truth is undeniable, the response must be carefully crafted to avoid encroaching upon the fundamental rights of freedom of speech and artistic expression. It should focus on educating the public while at the same time be mindful that existing laws as shown by Justice Oliver Wendell Holmes Jr. already have restrictions to free speech and artistic expression that account for harm.

Photo: Orson Welles meeting with reporters, telling them that  his intent was not to cause panic with his War of the Worlds radio broadcast. 31 October 1938.

Benjamin Franklin, one of the Founding Fathers of the United States, was a renowned polymath, statesman, author, and inventor, whose contributions have left an indelible mark on American history. His quote, "They who can give up essential liberty to obtain a little temporary safety deserve neither liberty nor safety," has resonated through centuries, becoming a cornerstone in discussions about the balance between security and freedom. This statement, profound in its simplicity, suggests a caution against the surrender of fundamental freedoms in the pursuit of short-lived security. It implies that overly restrictive laws, crafted in the name of safety, might not be the most effective means to ensure it. 

While law-abiding citizens adhere to regulations, those with malicious intent often disregard them. This disparity suggests that merely enacting more laws, particularly those aimed at curbing malevolent actions, may not be as effective as intended. The essence of Franklin’s argument is that the creation of stringent laws, while aimed at ensuring safety, might not necessarily prevent unlawful behavior, as those determined to break the law will likely continue to do so, regardless of the legal constraints in place.

In the context of contemporary issues such as the EU AI Act, Franklin's quote remains remarkably relevant. The EU AI Act aims to regulate artificial intelligence to ensure its responsible use within society. However, Franklin's insight suggests a cautionary note: the Act, while well-intentioned, may not achieve its intended effect if it leads to excessive restrictions on the freedoms associated with AI development and use. The challenge lies in finding a balanced approach that safeguards both the innovative potential of AI and the essential liberties of individuals and society at large. Franklin's quote serves as a timeless reminder of the delicate equilibrium between liberty and safety, a balance that continues to shape policy and societal norms in the digital age.

Abraham Lincoln, born into modest circumstances in a log cabin in Kentucky in 1809, rose through the ranks of society to become not only the 16th President of the United States but also a highly respected lawyer. His early life was marked by self-education and a fierce determination to succeed, characteristics that defined his legal and political careers. Lincoln's legal career, which began in Illinois, was built on a foundation of strong interpersonal relationships and an unrivaled reputation for integrity and ethical conduct. His ability to connect with clients and peers alike was pivotal, demonstrating early on the profound truth of his later reflection that "The better part of one's life consists of his friendships."

This ethos of valuing friendships and connections was not just limited to his legal practice but was also a cornerstone of his political life, particularly during his presidency. Lincoln's adeptness at fostering relationships and building alliances was instrumental during the Civil War, helping to maintain Union support and manage the diverse and often conflicting interests of his cabinet, famously known as the "Team of Rivals." His capacity to listen, empathize, and forge bonds, even with those who initially opposed him, was a key factor in his ability to lead the nation through its most perilous period. Thus, Lincoln's life and career exemplify how the essence of valuing friendships and human connections can transcend personal success and become a pivotal element in leadership and governance.

Theodore Roosevelt, the 26th President of the United States, was renowned for his progressive policies and strong belief in equitable justice. His quote, “No man is above the law, and no man is below it,” powerfully encapsulates the fundamental principle of equality before the law. This ethos is particularly pertinent in the context of contemporary issues like the regulation of Artificial Intelligence, as seen in initiatives like the EU AI Act. Roosevelt’s words underscore the necessity for a justice system, and by extension, regulatory frameworks, that apply uniformly to all, irrespective of their status or power. However, while the intention behind regulations like the EU AI Act is to create a fair and safe AI environment, there is a growing concern that such laws might inadvertently create an unequal playing field. Smaller technology companies, often lacking the extensive resources of their larger counterparts, may find themselves disproportionately burdened by the complex and costly compliance requirements. This situation could stifle innovation and competitiveness, leading to a market dominated by a few large players. 

It raises a critical question: can we achieve Roosevelt’s ideal of equal application of the law in the rapidly evolving and highly specialized field of AI, without inadvertently disadvantaging smaller entities? The challenge lies in balancing the need for comprehensive AI regulation to ensure safety and ethics, while also fostering an environment where smaller tech companies can thrive and contribute to the industry’s diversity and innovation. Considering the rapid advancements in AI technology, coupled with a noticeable gap in specialized knowledge among policymakers, the EU AI Act may inadvertently impede AI innovation. Historical observations in Europe suggest that regulations have stifle the development of groundbreaking products and companies. This backdrop raises apprehensions that the EU AI Act, while well-intentioned in its efforts to govern AI, might unintentionally hinder the sector's creative and innovative potential. 

William Ernest Henley, a prominent figure in Victorian literature, is best known for his poem "Invictus," particularly for the empowering lines, "I am the master of my fate, I am the captain of my soul." Born in 1849 in Gloucester, England, Henley faced considerable adversity, battling tuberculosis of the bone and enduring the amputation of his leg. Despite these challenges, his work, especially "Invictus," written in 1875, stands as a testament to the enduring human spirit and the power of resilience. This message of self-mastery and determination is incredibly pertinent in today's rapidly evolving digital age, especially with the advent of artificial intelligence (AI). As AI reshapes our world, Henley's words remind us of the importance of remaining the masters of our destinies. In an era where technological advancements are accelerating, the call for personal empowerment, adaptability, and self-reliance is more relevant than ever. His verse encourages us to steer our own courses in the face of unprecedented changes, ensuring we adapt, learn, and evolve to maintain relevance and control in an increasingly AI-driven world with how we work and what we work changing rapidly. Henley's legacy, thus, not only represents a triumph over personal adversity but also serves as an enduring beacon for navigating the complexities and opportunities presented by the AIl advancements.

In the era of rapid technological advancement, the integration of a society's cultural values into Large Language Models (LLMs) is not just an innovation but a necessity. As Mahatma Gandhi once said, "A nation's culture resides in the hearts and in the soul of its people." This sentiment underscores the importance of infusing LLMs with the richness and diversity of cultural heritage to ensure they reflect the true essence of human societies. Full article can be found here. 

Benjamin N. Cardozo, an esteemed American jurist, served as an Associate Justice of the Supreme Court of the United States from 1932 until his death in 1938. Born in 1870, he is remembered for his significant influence on the development of American common law and his tenure as Chief Judge of the New York Court of Appeals before his appointment to the Supreme Court. Cardozo's contributions to legal philosophy, characterized by his insightful and eloquent opinions, have left a lasting impact on American jurisprudence.

In a lecture at Yale University Law School in 1923, later published in The American Journal of International Law in 1935, Cardozo made a profound statement: 

“Justice is not to be taken by storm. She is to be wooed by slow advances.” 

This quote encapsulates Cardozo's view on the gradual and thoughtful evolution of justice and legal systems. It emphasizes the importance of careful deliberation and incremental change in the pursuit of justice, rather than abrupt or radical shifts.

When considering this perspective in the context of regulating Artificial Intelligence (AI), Cardozo's statement appears to advocate for a measured approach. The rapid advancement of AI presents unique and complex challenges, necessitating regulations that are both effective and adaptable. In this light, Cardozo's philosophy might align more with a cautious, step-by-step regulatory process rather than immediate and sweeping legislation. This approach resonates with the current debate on frameworks like the EU AI Act, suggesting that while regulations are necessary for managing AI's impact, they should evolve progressively to keep pace with technological advancements and their societal implications. Cardozo's wisdom implies that justice in the age of AI will best be served not by hastily crafted rules but by laws that evolve through thoughtful consideration and adapt to the intricacies of AI's role in society.

Around 164,000 years ago, Homo sapiens migrated to South Africa's coastlines, adapting to climate changes and exploiting new resources like shellfish, which enhanced their survival and cognitive development. This historical curiosity and adaptability mirror today's exploration of Artificial General Intelligence (AGI), signifying a continuous human journey of innovation and problem-solving. From ancient shores to AI frontiers, human progress is defined by our enduring spirit to explore, adapt, and evolve. Full article can be found here. 

The invention of the wheel around 3500 BC marked a pivotal moment in human history, catalyzing a profound transformation in transportation and trade. As wheels began to be attached to carts and chariots, they not only eased the movement of goods and people over long distances but also spurred advancements in agriculture and warfare, reshaping societies and economies. Similarly, the advent of generative AI and foundational models like Transformer Language Models is ushering in a new era of change, marked by significant shifts in how we interact with information, automate tasks, and even conceive creativity. These AI technologies are transforming industries, from healthcare to entertainment, by enabling more efficient data processing, personalized experiences, and innovative problem-solving approaches. However, one stark difference in these waves of change lies in their pace; the transformation driven by AI is occurring at an exponentially faster rate than any previous technological revolution, including that of the wheel, due to the rapid and interconnected nature of our modern digital world. This accelerated change underscores both the immense potential and the critical need for thoughtful oversight in the AI-driven era.

Roscoe Pound was a distinguished American legal scholar and educator, born in 1870. He served as the Dean of Harvard Law School from 1916 to 1936 and is widely recognized for his contributions to legal philosophy, particularly in the field of sociological jurisprudence. Pound's work emphasized the social impact of legal decisions and the need for law to function as a tool for societal progress. His influential ideas significantly shaped modern legal thought, particularly in how the law interacts with and responds to societal changes.

Pound's statement, “The law must be stable, but it must not stand still,” reflects his understanding of the dynamic nature of law in relation to society's evolution. This perspective is especially relevant in the context of common law, which is largely based on judicial precedents. Pound believed that while the law should provide a stable and predictable framework for order and justice (hence its need to be stable), it should also be adaptable and responsive to the changing needs and circumstances of society (thus it should not stand still). This idea is crucial when judges face the challenge of applying old laws to new technologies, such as generative AI, and an evolving society. It implies that judges should respect and uphold established legal principles and precedents for consistency and stability. However, they should also be willing to interpret and apply these principles flexibly and innovatively to address new and unforeseen circumstances brought about by technological advancements and societal changes. Pound's statement underscores the need for a balance between adherence to tradition and an openness to evolution in the legal system, ensuring that the law remains relevant and effective in a rapidly changing world.

The quote by John Adams, “Our Constitution was made only for a moral and religious people. It is wholly inadequate to the government of any other," from his letter to the Massachusetts Militia on October 11, 1798, highlights a fundamental principle: the effectiveness of laws and regulations depends significantly on the moral character and ethical standards of the society they govern. This perspective is particularly relevant when considering the regulation of new technologies like Artificial Intelligence (AI).

In the context of AI, Adams' viewpoint suggests that instead of hastily creating a multitude of new regulations every time a new technology emerges, it might be more effective to focus on the ethical and moral standards of the society that uses this technology. The idea is that a society with strong moral values will naturally use AI in ways that are beneficial and responsible, reducing the need for overly detailed or restrictive laws.

This approach advocates for oversight rather than an excessive number of specific regulations. Oversight involves monitoring and guiding the development and application of AI to ensure that it aligns with ethical standards and societal values, rather than trying to predict and legislate every possible scenario. This method recognizes that technology evolves rapidly, often outpacing the law's ability to regulate it. By focusing on oversight, society can adapt more fluidly to technological advancements, ensuring that AI is used responsibly and ethically without stifling innovation with overly burdensome regulations.

Adams' philosophy underscores the importance of a society's moral fabric in shaping the use and regulation of new technologies. It suggests that fostering a strong ethical culture might be as crucial as, if not more important than, the creation of specific laws in governing the emergence and integration of technologies like AI into society.

The role of judges in the Federal Judiciary has been one of evolution and adaptation. In recent times, technological advancements, particularly in artificial intelligence (AI), have begun to play a pivotal role in reshaping judicial responsibilities and capabilities. Chief Justice John G. Roberts Jr.'s 2023 Year-End Report on the Federal Judiciary underlines this transition, highlighting the impact of AI on the judiciary and the enduring importance of human judges.

Chief Justice Roberts wrote: 

Rule 1 of the Federal Rules of Civil Procedure directs the parties and the courts to seek the “just, speedy, and inexpensive” resolution of cases. Many AI applications indisputably assist the judicial system in advancing those goals. 

AI has emerged as a significant ally in this regard. AI applications in the judiciary assist in various aspects, such as managing vast amounts of legal data, predicting case outcomes, and streamlining administrative tasks. This not only expedites the judicial process but also enhances accuracy and fairness in decision-making.

Full article can be found here

Ardipithecus ramidus, a hominid species that lived around 4.4 million years ago, demonstrated remarkable adaptability in the face of climate change through its unique physical attributes. This species was adept at bipedality, allowing it to traverse open terrains efficiently, a crucial adaptation as forests receded and grasslands expanded. Simultaneously, Ardipithecus retained arboreal capabilities, evident in its limb structure, enabling it to exploit the resources of the diminishing forest habitats. This dual adaptation for both terrestrial and arboreal environments was key to its survival in a changing world.

Drawing a parallel to modern times, humans are facing their own climate challenges. Just as Ardipithecus used its physical adaptability to navigate environmental changes, humans are leveraging advanced tools like artificial intelligence (AI) to adapt to and mitigate the impacts of climate change. AI aids in predicting climate patterns, optimizing resource use, and developing sustainable solutions, akin to how Ardipithecus utilized its bipedalism and arboreality. This technological adaptability mirrors the physical adaptability of Ardipithecus, underscoring a continuous theme in the evolution of species: the imperative to adapt for survival in the face of environmental change.

Heraclitus, an ancient Greek philosopher active around 535–475 BCE, is renowned for his cryptic and profound aphorisms. His quote, 

“You would not find the boundaries of the soul no matter how many paths you traveled, so deep is its measure,” 

reflects his deep contemplation on the nature of the soul and human understanding.

Heraclitus hailed from Ephesus, an important city in Ionia. He was known for his philosophy that emphasized the constant change and flow in the universe, encapsulated in his famous doctrine, "Panta Rhei," meaning "everything flows." This perspective highlighted the ever-changing and dynamic nature of reality. This particular quote delves into the seemingly infinite complexity of the human soul. Heraclitus suggests that the soul is an entity of such depth and intricacy that its full extent can never be completely understood or explored, no matter how much one tries. 

Today our understanding of human consciousness and the depth of the human mind have grown tremendously compared to the early 5th century BC when Heraclitus lived. It is possible now to understand these with some level of confidence. We at Robometrics® Machines have made significant progress in modeling consciousness. There may be aspects of human consciousness that remain elusive to artificial replication, underscoring the enigmatic depth of the human mind and soul. At the same time, modeling consciousness remains an important step towards Artificial General Intelligence (AGI) and at some point of time, the understanding of the human soul that will lead to immortality by proxy. 

Ray Kurzweil, an American inventor and futurist, currently holds a prominent position as a director of engineering at Google. Born on February 12, 1948, in Queens, New York, Kurzweil has established himself as a vanguard in various technological fields, including optical character recognition (OCR), text-to-speech synthesis, speech recognition technology, and the development of electronic keyboard instruments. Beyond these achievements, he is renowned for his insightful books on a range of subjects like health, artificial intelligence (AI), transhumanism, the technological singularity, and futurism, painting a picture of a future profoundly shaped by technological advancements.

Central to Kurzweil's perspective on the future is the concept of an age of abundance, propelled by the rapid evolution of technology, especially AI. He envisions a future where AI reaches, and eventually surpasses, human levels of intelligence. One of his notable quotes on this subject is:

"Artificial Intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold." 

This prediction exemplifies Kurzweil's belief in the exponential growth and transformative power of technology. He foresees a world where traditional scarcities are replaced by technological abundance, effectively addressing global challenges such as health, poverty, and aging. His forecasts often highlight the synergy of various emerging technologies, including AI, nanotechnology, and biotechnology, and their collective impact on reshaping society and human life. Kurzweil's views offer a compelling glimpse into a future where technological advancements hold the key to solving some of humanity's most pressing issues.

The article delves into John Searle's Chinese Room Argument and its implications on machine consciousness in artificial intelligence (AI). It outlines Searle's critique of the Turing Test, emphasizing that mere symbol manipulation by machines does not equate to true understanding of consciousness. The article highlights the need for AI to transcend beyond language skills and incorporate elements of intuition and consciousness, akin to human intelligence. It underscores the challenge of imbuing machines with self-awareness and contextual understanding, positioning this endeavor not just as a technological leap but also as a philosophical exploration into the nature of intelligence and consciousness. Full article here. 

As we navigate through the Age of AI, a period that gained momentum in 2023 and continues to evolve, we're witnessing a unique blend of past and present. This era is characterized by our deep integration with technology, especially through our use of numerous custom GPTs, symbolizing the zenith of machine intelligence and personalization. Despite the rapid technological advancements, there's a strong affinity for traditional elements like Polaroid photographs, which represent a tangible connection to the past, unaltered by digital advancements. This dichotomy reflects the thoughts of visionaries like Albert Einstein, who highlighted the importance of adaptability in intelligence, and Steve Jobs, who emphasized selective innovation. Their insights resonate in our era, as we cherish the simplicity of the old—like driving a manual car or flying a Cessna 172—while embracing the complexities of AI. This harmonious coexistence of old and new, especially evident as we move into 2024, underscores our journey towards a future that respects both the revolutionary capabilities of AI and the timeless value of simpler, more traditional experiences. Full article here. 

It is naive to think about Foundation Models such as Transformer based Large Language Models (LLM) as black box when we consider the general convergence of AI with human brain functions. In the human brain, Magnesium (Mg2+) gating of NMDA receptors is crucial for long-term memory. A memory is not formed if a NMDA receptor is gated by Mg2+. Some of the parameters involving alterations to the activation functions within the model's feed-forward layers of the Transformer model in an LLM can be adjusted to mimic the gating action of the NMDA receptor in the human brain. These parameters  control the various elements of the model's architecture and configuration that determine its behavior, performance and learning. 

Collectively, the parameters that can be adjusted in the Transformer model can be thought of as a NMDA-inspired activation function, potentially involving alterations to the activation functions within the model's feed-forward layers. This can enhance the model's long-term memory capabilities, akin to how memory consolidation works in the human brain. The combination of activation function, attention mechanisms as well as hyperparameters such as learning rates and temperature can have the effect of selective learning, resulting in long term memory in a LLM. 

This similarity between learning and memory formation in Transformer based LLM and human brain gives us a good indication of how LLMs can be improved while at the same time, improving how we humans learn.

"The world has enough for everyone's need, but not enough for everyone's greed."

Gandhi's statement highlights the concept of sustainable abundance. He suggests that the Earth possesses sufficient resources to meet the needs of every individual, but these resources are not endless and cannot satisfy unlimited greed. His perspective emphasizes the importance of equitable distribution and sustainable living as pathways to achieving a form of abundance that benefits all. This makes us think whether the notion that in the future, there is fundamentally a need for an age of abundance that is created by AI and robotics is inherently misleading and just feeding into the greed of some, creating a world that is ruled by a few. 

Mahatma Gandhi's poignant observation offers a profound insight into the current discourse on the age of abundance, particularly in the context of advancements like AI. Gandhi's perspective challenges the notion that we require a new era of abundance facilitated by AI or any other technological advancements. This by no means implies advancements such AI and robotics are not going to be helpful to human civilization in the future. 

Instead, it suggests that the key to achieving a balanced and sustainable world with abundance lies in addressing human greed and redefining our understanding of 'need' versus 'want'. The emphasis is on sustainable consumption, ethical stewardship of resources, and equitable distribution, rather than on focusing on creating more through artificial means. For example humanoid robots for factories. In a world where technology, including AI, continues to advance rapidly, Gandhi's words serve as a reminder of the importance of moderation, sustainability, and the ethical implications of our pursuit of abundance. It's a call to focus on fair allocation and responsible use of what we already have, rather than an endless quest for more, driven by AI or other technologies.

Grant Gilmore, a prominent American legal scholar, was an influential figure in the development of American contract law. Born in 1910, he was notably appointed as a Sterling Professor of Law at Yale Law School, one of the most prestigious positions in American legal academia. Gilmore's work significantly impacted the field, particularly through his contributions to the Uniform Commercial Code (UCC), a key set of laws governing commercial transactions in the United States. His teachings and writings, including his well-known book "The Death of Contract," have been highly influential in legal circles, especially in the context of contract law and legal philosophy.

In his book "The Ages of American Law" (1977), Gilmore made a profound statement: 

"Law reflects but in no sense determines the moral worth of a society. The values of a reasonably just society will reflect themselves in a reasonably just law. The better the society, the less law there will be. In Heaven there will be no law, and the lion will lie down with the lamb."

This statement encapsulates Gilmore's view on the relationship between law and society's moral standards. He argued that law is a mirror of society's values and morality but does not, in itself, shape these values. Instead, a society's inherent sense of justice and fairness is what shapes its legal system. Gilmore believed that in an ideal, highly moral society, the need for extensive laws and regulations diminishes, as the citizens inherently adhere to just principles. His vision of an ideal society ("In Heaven there will be no law") suggests a utopian scenario where laws become redundant due to the inherent goodness and understanding of its members, a state where peace and harmony prevail ("the lion will lie down with the lamb"). This philosophical view offers a perspective on the law as not just a set of rules imposed on society but as a reflection of society's collective moral and ethical standards.

The Copyright Act of 1790 marked a significant milestone in the history of U.S. intellectual property law, establishing the first formal system for copyright protection in the United States. Under this act, authors, or their designated representatives, could register their works for a term of 14 years with the option of renewal for another 14 years. This legislation was an embodiment of the U.S. Constitution's Article I, Section 8, Clause 8, which empowered Congress to promote the progress of science and the useful arts by securing for limited times to authors and inventors the exclusive right to their respective writings and discoveries.

One of the first works to be copyrighted under this act was "The Power of Sympathy" by William Hill Brown, published in 1789. This novel is often recognized as “The First American Novel” and was a groundbreaking work in American literary history. Notably, the novel was originally published anonymously due to the sensitive nature of its content and the prevailing social norms of the time. This aspect of anonymity in the novel’s publication and copyright raises intriguing questions about modern copyright law, particularly in relation to works created by artificial intelligence (AI).

The precedent of granting copyright to an anonymous work like "The Power of Sympathy" suggests a certain flexibility in the concept of authorship within copyright law. This flexibility becomes increasingly relevant in contemporary discussions about AI and copyright. If a work that was published anonymously can be granted copyright protection, it opens the door to discussions about whether AI-generated works, which do not have a human author in the traditional sense, could also be eligible for similar protections. The evolving nature of authorship and the role of AI in creative processes could lead to significant shifts in how copyright law is interpreted and applied in the future.

“For when, in writing for the majority of the Court, I adopt a general rule, and say, 'This is the basis of our decision,' I not only constrain lower courts, I constrain myself as well."

"In the real world of appellate judging, it displays more judicial restraint to adopt such a course than to announce that, 'on balance,' we think the law was violated here -- leaving ourselves free to say in the next case that, 'on balance,' it was not."

In this excerpt above written by Antonin Scalia in "The Rule of Law as a Law of Rules"  published in the University of Chicago Law Review  (1989), Scalia reflects on the nature of judicial decision-making. He initially perceived the common-law approach as a form of judicial restraint, minimizing law creation. However, Scalia grew to see that adopting general rules in majority opinions actually embodies greater restraint. By establishing a governing principle, a judge not only guides lower courts but also self-imposes constraints on future decisions, regardless of personal preferences. Scalia argues that this approach, as opposed to a flexible "on balance" method, provides a more consistent and predictable framework for legal interpretation, making it harder to accuse judges of arbitrariness or inconsistency.

In context or regulating AI, Antonin Scalia's "The Rule of Law as a Law of Rules" suggests that laws should be made with clear, general principles rather than on a case-by-case basis. This approach emphasizes judicial restraint, ensuring that personal biases do not influence legal decisions and that consistency is maintained across different cases.

Cartesian philosophy, originating in the early 17th century with René Descartes, represents a watershed moment in philosophical and scientific thought. Born in 1596, Descartes, a French philosopher and mathematician, formulated this philosophy during a period of profound scientific and intellectual upheaval, characterized by the transition from medieval to modern thinking. He laid the foundations for this system in his seminal works, "Discourse on the Method" (1637) and "Meditations on First Philosophy" (1641). In these texts, Descartes sought to establish a new method of acquiring knowledge, turning away from scholastic traditions and advocating for a fresh approach based on reason and skepticism.

Descartes' exploration of the mind-body dualism – the distinction between the mental and the physical – is particularly relevant in contemporary debates about what it means to be human in an age of advanced technology. His insights into the nature of human thought and existence continue to fuel discussions and research into the essence of consciousness and the human experience. Thus, the legacy of Cartesian philosophy, grounded in the use of reason to understand the natural world and ourselves, remains a vital and influential force in shaping our approach to fundamental questions in science and philosophy.

In contemporary times, Cartesian philosophy finds relevance in areas like human consciousness, Artificial General Intelligence (AGI), and the exploration of what it means to be human. By advocating for a rational, methodical approach to inquiry, Cartesianism encourages a deeper investigation into human consciousness, pushing the boundaries of understanding the mind's complexities. In the realm of AGI, this philosophical framework inspires the creation of intelligent systems that can reason, learn, and adapt, much like the human mind. Furthermore, Cartesian philosophy invites continuous reflection on the human condition, prompting questions about the essence of humanity in an increasingly technologically driven world. As we navigate new frontiers in science and technology, the Cartesian emphasis on reason and methodical inquiry remains a vital guide, helping to shape our understanding of ourselves and the world around us.

The concept of a perpetual machine has long fascinated humanity. From Leonardo da Vinci's quest for a self-operating machine to Nikola Tesla's endeavors in creating limitless energy, the idea of a machine that operates indefinitely without an external energy source has been a beacon of human imagination. This dream now takes a new form in the realm of intellectual creativity, the Perpetual Patent Machine (PPM).

Unlike traditional inventing processes driven by personal rewards and the novelty of creation, the Perpetual Patent Machine operates without such incentives. Its sole mission is to continuously generate new, useful inventions, as defined by its human counterparts. This highlights a unique partnership where AI excels in solution-finding, but the quintessential spark of human creativity remains crucial in problem identification and framing. Historically, the pursuit of perpetual motion and endless innovation has been echoed in the note by Nikola Tesla: 

"If you want to find the secrets of the universe, think in terms of energy, frequency, and vibration." 

This embody the perpetual quest for knowledge and innovation that drives human progress. A landmark in this journey is the contribution of Google DeepMind, “Scaling deep learning for materials discovery” as published in Nature on November 29, 2023. The study showcases the power of AI in improving the efficiency of materials discovery by an order of magnitude. Building on the identification of 48,000 stable crystals, the AI model, known as GNoME, has discovered 2.2 million new structures, surpassing previous human chemical intuition. This represents a monumental expansion in the materials known to humanity, with 736 structures already experimentally realized. The GNoME models exhibit emergent out-of-distribution capabilities at scale, demonstrating the profound impact of AI in transcending the limits of human knowledge and intuition in material science.

The Perpetual Patent Machine, embodied by the likes of GNoME, signifies a new era in innovation. It underscores the potential of AI not just as a tool, but as a collaborator in the creative process. The continued evolution of such machines promises to fundamentally accelerate the pace of discovery across various domains, making previously unimaginable inventions a tangible reality. The dream of the Perpetual Patent Machine is not just about creating a self-sustaining system of innovation; it's about redefining the partnership between human and machine intelligence. As we stand on the brink of this new era, it's essential to remember that the spark of human creativity, embodied in problem identification and framing, remains irreplaceable. Together, human ingenuity and AI's capability can forge a path to endless innovation, turning the dream of a perpetual machine into a reality that fuels the future of human progress.

Benjamin N. Cardozo, an American jurist born on May 24, 1870, served on the New York Court of Appeals from 1914 to 1932 and was an Associate Justice of the Supreme Court of the United States from 1932 until his death in 1938. He is renowned for significantly influencing the development of American common law in the 20th century, thanks to his legal philosophy and vivid prose style. Cardozo penned notable majority opinions in cases such as Palsgraf v. Long Island Railroad Co., Nixon v. Condon, and Steward Machine Co. v. Davis during his tenure on the U.S. Supreme Court.

Cardozo's famous cases include Schloendorff v. Society of New York Hospital, which established the necessity of informed consent in medical procedures; MacPherson v. Buick Motor Co., which ended privity as a prerequisite to duty in product liability; and Palsgraf v. Long Island Railroad Co., which developed the concept of proximate cause in tort law. His judgments often reflected a deep understanding of the law, balanced with considerations of social welfare and justice.

Cardozo's statement, 

“The judge is not the knight-errant, roaming at will in pursuit of his own ideal of beauty or of goodness,” 

is from his work "The Nature of the Judicial Process." This statement encapsulates his view on the role of judges in the legal system. Cardozo believed that judges should follow and apply the law in straightforward cases and make new law in more complex cases by balancing various considerations, including social welfare. He acknowledged the inherent risks in judicial lawmaking, emphasizing that judges should only make new law when the law contains gaps or a legal rule is clearly obsolete, and their actions should be guided by community standards rather than personal values. His perspective was that a judge's freedom to innovate is limited by the rules that surround them, and their role is not to pursue personal ideals but to draw inspiration from established principles.

Cardozo's views on the judicial process are significant as they highlight the balance judges must maintain between adherence to legal precedent and the evolving needs of society. He recognized the dynamic nature of law and the responsibility of judges to interpret and apply it in a manner that upholds justice and social welfare. This philosophy underscores the importance of judicial restraint and the need for judges to be guided by principles rather than personal inclinations, ensuring that their decisions are rooted in law and aligned with societal values.

Henry David Thoreau, an American transcendentalist born in the early 19th century, is best known for his philosophical and naturalist writings, including the seminal essay "Civil Disobedience," first published in 1849. This work, originally titled "Resistance to Civil Government," articulates Thoreau's conviction that individuals should not let governments override their conscience, particularly when such governments perpetrate or support injustice. His stance was partly a response to the slavery crisis in New England during the 1840s and 1850s, and specifically to the Fugitive Slave Act of 1850. Thoreau, a lifelong abolitionist, was deeply troubled by slavery and the Mexican-American War, seeing them as grave injustices.

In "Civil Disobedience," Thoreau argues that governments are more often harmful than helpful, and that the judgment of an individual's conscience is paramount. He believed that the law does not inherently make people just; rather, individuals must actively engage in making the law just. This view is encapsulated in his statement, 

“The law will never make a man free; it is men who have got to make the law free.” 

Thoreau asserts that democracy, by virtue of being a majority rule, does not automatically confer wisdom or justice. He emphasizes the importance of individual judgment and conscience over blind adherence to law, especially when the law itself perpetuates injustice. For Thoreau, true freedom and justice are achieved not through the passive acceptance of laws, but through the active and moral engagement of individuals in shaping and challenging these laws.

This perspective challenges the notion that law and justice are synonymous. Thoreau's assertion highlights the dynamic relationship between law, freedom, and individual morality. It suggests that laws, in themselves, are not the ultimate arbiters of justice; rather, it is the intent and actions of individuals within a legal framework that bring about true justice. This view underlines the responsibility of individuals not only to obey laws but also to critically evaluate and influence them, ensuring that they align with the principles of justice and morality.

Benjamin Disraeli, a prominent British statesman and novelist, was twice the Prime Minister of the United Kingdom (1868, 1874–1880) and a key figure in the Conservative Party. Born on December 21, 1804, in London, Disraeli was of Italian-Jewish descent. A pivotal moment in his early life was his father's decision in 1817 to baptize his children as Christians, a choice that was crucial for Disraeli's future political career, as Jews by religion were excluded from Parliament until 1858.

Disraeli's journey into politics was marked by initial setbacks and personal struggles, including a period that would now be recognized as a nervous breakdown. His travels in the Mediterranean and the Middle East deeply influenced his later political attitudes and literary works. He entered politics in 1831 as an independent radical and eventually aligned himself with the Conservative Party, though his initial attempts at securing a parliamentary seat were unsuccessful. His extravagant lifestyle and debts, coupled with his controversial personal life, earned him a dubious reputation. However, by 1837, Disraeli had secured a seat in Parliament for Maidstone in Kent. His early speeches in the House of Commons were met with criticism, but he quickly established himself as a commanding speaker.

Disraeli's statement, 

“Justice is truth in action,” 

reflects his complex view of politics and law. This perspective aligns with his life experiences and political journey, where he witnessed and contributed to the evolution of justice and governance beyond the rigid confines of the law. Disraeli understood that the pursuit of justice is not solely about adhering to the letter of the law, but about acting upon truths that stem from experience, intent, and a deeper understanding of societal needs. His own political career, marked by initial setbacks and eventual triumph, exemplifies the idea that truth and justice are dynamic concepts, realized through action and perseverance rather than mere compliance with established legal frameworks. Disraeli's quote underlines the significance of intent and the human element in the application of justice, suggesting that true justice is achieved when actions are guided by truth and a commitment to societal good, transcending the mere technicalities of law.

Ada Lovelace, regarded as the first computer programmer, recognized AI and machines as extensions of human thought, capable only of what they are programmed to perform. She said in her memoir (1842):

"The Analytical Engine has no pretensions whatever to originate anything. It can do whatever we know how to order it to perform."

Lovelace's insight hints at the idea that AI and machines are extensions of human thought and capability, doing what they are programmed to do by humans, and thus are a part of the natural evolution of human tools and thought processes. She thought of machines as a natural extension of human intelligence and creativity, but not as something that can think for itself. 

Douglas R. Hartree (1949) had a difference view where he quoted Lovelace's view on  the Analytical Engine and wrote 

“This does not imply that it may not be possible to construct electronic equipment which will ‘think for itself,’ or in which, in biological terms, one could set up a conditioned reflex, which would serve as a basis for ‘learning.’"

Today, Q-learning can approximate a thinking machine with Natural Intelligence. Q-Star, a variant of Q-learning - method where agents learn to make decisions by trial and error, receiving rewards for successful actions. For a transformer, it is selecting the next token based on a future long term reward. Q* is combining the use of search (e.g. Monte Carlo Tree Search) and learning (token sampling and predicting). Search increases intelligence. The AI can take more time to deliberate without altering its parameters, and dynamically trade off efficiency with deeper thinking.

Q = q-learning

Star = embedded algorithms discovered and joined with the transformer architecture 

The Andersen et al v. Stability AI Ltd. et al (Case 3:23-cv-00201-WHO) lawsuit involved artists Sarah Anderson, Kelly McKernan, and Karla Ortiz suing Stability AI, Midjourney, and DeviantArt for allegedly using their copyrighted works without permission in their generative AI software, specifically Stable Diffusion. Judge William Orrick dismissed most claims but allowed Andersen's direct copyright infringement claim against Stability AI to proceed. He also expressed doubt about the plaintiffs' arguments that AI-generated outputs are simply derivatives of the copyrighted images, highlighting the need for substantial similarity in such claims.

This case supports the notion that diffusion models are not Stochastic Parrots. Judge Orrick's skepticism about the AI-generated outputs being direct derivatives of the original artworks implies an understanding that these models, while trained on existing images, create new, transformative outputs. This suggests that diffusion models like Stable Diffusion do more than just replicate input data; they generate novel creations that are distinct from the source material, showcasing a level of originality and transformation beyond simple replication.

Full article can be found here. 

Kadrey v. Meta (Case 3:23-cv-03417) filed by Sarah Silverman and other authors against Meta focused on the allegation that Meta's large language models (LLMs), specifically LLaMA, were trained using copyrighted books without authorization. The plaintiffs claimed that this training involved the illegal scraping of works from book torrenting websites. The case saw partial dismissal by Judge Vince Chhabria on  November, 20 2023, who expressed skepticism about the plaintiffs' claims, particularly questioning the idea that text generated by LLaMA was a direct infringement of the authors' copyrights.

Kadrey v. Meta is another argument to support that LLMs don’t simply replicate or regurgitate information without understanding or originality. They are not Stochastic Parrots. Judge Chhabria's dismissal of claims based on the idea that LLaMA's output directly infringed copyrights suggests a recognition that the outputs of LLMs are not straightforward replications of input data but involve complex, transformative processes. This indicates an understanding that LLMs, while trained on existing data, generate outputs that are not mere echoes of their training material, but rather unique amalgamations and interpretations of learned information.

Full article can be found here. 

The advent of superintelligent AI presents a scenario that challenges our traditional understanding of containment and control. As Elon Musk once cautioned, "With artificial intelligence, we are summoning the demon." This analogy underscores the inherent risks in developing an intelligence that surpasses our own. The notion that one can "keep a superintelligent AI in a bottle" and assume it won't escape is a dangerous underestimation of its potential capabilities. Stephen Hawking echoed similar concerns, stating, "The development of full artificial intelligence could spell the end of the human race." These warnings highlight the necessity of aligning AI's objectives with human interests. 

The key may lie in imbuing AI with a form of consciousness akin to our own.  By integrating aspects of human-like consciousness, such as empathy, ethics, and understanding of human values, we could potentially ensure that when the "genie" of superintelligence is out of the bottle, it will act in harmony with human interests and well-being. This approach advocates for a proactive and synergistic relationship with AI, rather than one based solely on control or containment.

The human brain, despite its remarkable capabilities, has inherent limitations when compared to modern digital technologies. Firstly, the biological neurons in our brain fire at a maximum rate of around 200 times per second (200 Hz), which pales in comparison to the speed at which present-day transistors operate, typically in the gigahertz (GHz) range. This discrepancy in speed highlights a fundamental difference in processing power between biological and electronic systems. Secondly, neurons in the human brain propagate signals relatively slowly, with a maximum speed of about 100 meters per second. In contrast, computer signals can travel at the speed of light, vastly outpacing the signal transmission within our nervous system.

If these two limitations were removed or significantly mitigated in the human brain, the implications could be profound. Enhancing the firing rate of neurons to match the speed of modern transistors could dramatically increase the processing speed of the brain, potentially allowing for quicker thinking, faster learning, and more efficient problem-solving. Similarly, if neuronal signal propagation could be accelerated to approach the speed of light, it would vastly improve the rate at which information is communicated within the brain. This could lead to improved coordination, quicker reflexes, and possibly an enhanced ability to process and integrate complex information in real-time. However, such enhancements would fundamentally alter the nature of human cognition and could have unforeseen consequences on aspects of consciousness, identity, and the human experience as a whole.

Consciousness is deeply intertwined with the brain's processing capabilities and the speed of neural communication. If neurons could fire at the speed of modern transistors and signals could travel at or near the speed of light, it's conceivable that our experience of consciousness would be significantly altered. Such enhancements might lead to an expanded awareness, enabling individuals to process and interpret vast amounts of information almost instantaneously. This could lead to a heightened sense of perception, faster cognitive reactions, and perhaps the ability to experience time and thought in ways currently unimaginable. However, these changes could also challenge our understanding of self and identity. They might bring about new forms of cognitive overload or alter the way emotions and thoughts are experienced, potentially leading to a state of consciousness that is fundamentally different from what is currently known, Super-consciousness

These changes could also raise ethical and philosophical questions about what it means to be human in an era where our natural biological limits are transcended. 

The convergence of biotechnology and artificial intelligence (AI) marks a transformative era in medical research. Genetically modified mice, engineered to produce human-like proteins, serve as an efficient means to synthesize new protein molecules with minimal human intervention. These proteins, often vital for treating various diseases, represent novel inventions that can be patented, incentivizing further research and development. Similarly, generative AI technologies like DeepMind's AlphaFold autonomously predict complex protein structures, reducing reliance on human computation and accelerating scientific discovery. Both these advancements illustrate how autonomous systems are increasingly playing a pivotal role in inventing and discovering new biomedical solutions, reshaping the landscape of medical research and therapy development.

Generative AI technologies and genetically modified mice present many parallels as tools in the realm of medical research, capable of assisting humans in inventing new protein molecules. Given their ability to autonomously generate novel and non-obvious biomedical solutions, the outputs of these advanced tools – be it AI-predicted protein structures or proteins synthesized by transgenic mice – rightfully merit consideration for patent protection, fostering innovation and advancement in medical science. 

Full article can be found here

While the AI can assist in the process of invention, the ultimate credit lies with, and goes to the human, who needs to remain in charge and supervise both the identification of the problem and solution for the invention. The amount of supervision may not be important as long as the human is in-charge. This human-centric approach is vital not only for maintaining the integrity of the patent system but also for ensuring that the rewards and responsibilities associated with a patent are borne by humans, who have the capacity for ethical and moral judgment. For example, AlphaFold by DeepMind, which can generate novel and potentially patentable protein structures, underscores this thesis. These generated protein structures can be patentable as long as effort is made on human supervision to craft the problem and later be involved in selection of the protein structure to some extent. Full article can be found here.

Whether a novel invention is patentable depends on who and what it took to identify the problem and then come up with a novel solution to that problem. Once you have the problem well defined, we can come up with the questions that  Generative AI can easily find a solution that is better than what exists already. If the human was not involved substantially in identifying the problem and Generative AI did the work both for identifying the problem and then the solution, the invention is not patentable. The USPTO noted that Title 35 of the United States Code  requires the inventors to be natural persons. 

Albert Einstein once said:

"If I had an hour to solve a problem and my life depended on it, I would use the first 55 minutes determining the proper question to ask, for once I know the proper question, I can solve the problem in less than five minutes."

Same applies when using Generative AI as a tool to assist us, the natural persons in inventing. We need to at least be intimately involved and spend time in identifying the problem and to some extent in decision making while using Generative AI to solve the problem.

The visual shows Samuel Hopkins working on the new method of making potash, an ingredient used in fertilizer, which became the first patent ever filed and granted in the United States, on July 31, 1790. The patent was signed by President George Washington, Secretary of State Thomas Jefferson, and Attorney General Edmund Randolph.

In "Les Passions de l'âme," René Descartes explores the intricate nature of emotions, providing insights on the development of AGI (Artificial General Intelligence). By simulating emotional responses, AGI could achieve more than enhanced human-AGI interaction; it could also replicate human-like decision-making processes. Descartes views emotions as fundamental to human cognition, arguing that they are intrinsically good and that their misuse or excess should be avoided. This perspective suggests that emotions, when properly harnessed, can guide rational decision-making. Applying this to AGI, emotional algorithms could be designed not just to mimic human responses but to aid in complex decision-making, where factors like empathy, ethical considerations, and social context are crucial. Such AGI systems would not merely process data but interpret it in a human-like manner, integrating rational thought with emotional intelligence, a combination Descartes views as central to human experience. This integration could lead to AGI systems that make decisions that are not only logically sound but also ethically and socially aware, mirroring the depth and nuance of human decision-making.

In "Les Passions de l'âme," René Descartes delves into the intricate relationship between emotions (passions) and consciousness, primarily through the lens of the mind-body union. His approach in the "Meditations on First Philosophy" provides context for this exploration, where he posits that sensations, appetites, and passions, though often a source of error in theoretical knowledge, are crucial for practical functionality. These passions are not to be referred solely to the mind or body but are a manifestation of their union, guiding our interaction with the external world and preserving the mind-body unity.

Descartes's correspondence with Princess Elisabeth of Bohemia further illuminates this relationship. Here, he discusses the mind's ability to control bodily passions and emphasizes that the mind and body form a genuine union. This interaction highlights the impact of emotions on health and well-being, suggesting that mental activities like reasoning and willing can be affected by bodily conditions, thus influencing our susceptibility to passions. 

This interplay between mind and body, as discussed by Descartes, suggests that passions, while rooted in bodily perceptions, are integrally connected to consciousness. They serve not just as physiological responses but as reflections of the deep intermingling of mind and body, shaping our conscious experiences and responses.

Applying Descartes' concepts on the passions (emotions) and consciousness to AI or AGI (Artificial General Intelligence) involves considering how AI machines such as Robometrics Machines can mimic or process human-like emotional responses and consciousness. Descartes' theory emphasizes the interplay between mind and body, suggesting that emotions are not just physiological but also reflective of cognitive states and require embodiment of some kind.

René Descartes, the French philosopher, mathematician, and scientist, born in 1596, is widely regarded as a pivotal figure in the development of modern philosophy. His statement, "I think; therefore I am" ("Cogito, ergo sum" in Latin), first appeared in his work "Discourse on the Method" in 1637. This phrase forms the foundation of Cartesian philosophy and represents a fundamental element in Western philosophy. Descartes' statement was a response to his methodic doubt, a process where he doubted everything that could be doubted, to determine what he could know with certainty. In this context, the act of thinking itself became the undeniable proof of his own existence.

This phrase has profound implications in the realm of artificial intelligence (AI) and consciousness studies. It raises fundamental questions about the nature of reasoning, thinking, self-awareness, and more brooding our existence. In AI, this translates into the question about whether machines can possess consciousness or self-awareness. Descartes' ideas challenge us to consider what it means to think and exist, especially as AI systems become more advanced and seemingly capable of some level of reasoning and ‘thought-like' processes. The exploration of machine consciousness today often circles back to Cartesian concepts, pondering if an AI's ability to learn selfsupervised, possess some level of common sense reasoning and make decisions could translate into self-awareness and consciousness that is similar to human’s in nature, if not in scale.

Consciousness is the hallucination building the story in our mind every few nanoseconds. Consciousness builds up overtime as we grow from a one week old to where we are now. The complexity and magnitude of consciousness is proportional to the neurons in a creature's brain. So a butterfly will have consciousness too but much less compared to a human. The interconnection between the neurons with the total number of neurons determines how the brain evolves and develops consciousness and intelligence. One can be conscious without being intelligent. Machines either in their physical form or software, powered by a level of AI, can be intelligent but without consciousness. 

We at Robometrics® Machines are working on modeling an evolving consciousness into Robometrics® AGI, approximating what a biological creature such as a human will have.

The best approach to build artificial intelligence that includes general intelligence, common sense, intuition and conciseness is by understanding our biological intelligence and our body, while creating artificial intelligence, not through simulations but with real interactions within the real world. The connection between visual perception and action is way too important to keep them separate. Our brains create our minds to preserve our bodies and use its biological intelligence to move, develop, interact and survive in our physical world. Mind creates a steady, consistent and imaginable friction for us to exist for our body. Embodiment is essential for the mind to develop and operate in the physical reality of the world. 

In the future, it will be possible to move our mind from one body to another. But it won’t be easy even if we are able to capture our biological intelligence outside our mind. There are experiences and intelligence in our body itself, which can only be learned with time in the physical reality and can not be transferred. 

"I Am an American Day" was a patriotic event held on May 21, 1944, in Central Park, New York City. Originating from earlier Americanization Day observances, the event coincided with the broader context of World War II, aiming to foster a sense of national unity and patriotic pride among the American populace, especially in a time of global conflict and uncertainty. 

Judge Hand, serving at that time as a Senior Judge of the United States Court of Appeals for the Second Circuit, was renowned for his intellectual depth and his articulate, thoughtful expressions on matters of law and liberty. One of the quotes from his speech , "The spirit of liberty is the spirit of Him who, near two thousand years ago, taught mankind that lesson it has never learned, but has never quite forgotten; that there may be a kingdom where the least shall be heard and considered side by side with the greatest," speaks to the essence of inclusive and equitable treatment. In the context of building AI regulations, this quote underscores the need for a balanced and fair approach that considers both large AI companies and small startups.

A monumental stride came with a sweeping Executive Order from President Biden aiming to reshape the AI landscape, with a spotlight on "dual-use foundation models. Although aimed at keeping tabs on powerful AI systems, this mandate could tip the scales in favor of large companies.  Conversely, this could pose a hefty burden on small AI startups, potentially stifling innovation due to compliance costs and time constraints. 

Full article can be found here 

Sir Edward Coke (1552-1634) was a prominent English jurist and Member of Parliament whose writings and rulings significantly shaped the common law. He is renowned for defending the supremacy of common law against royal prerogatives. His statement, "Reason is the life of the law," reflects his belief in a rational and evolving legal framework, underscoring the importance of reasoned judgments in the development and application of legal principles. Through his extensive legal works, Coke laid the foundation for centuries of common law tradition, emphasizing the enduring and adaptive nature of law, guided by reason and judicial interpretation.

The philosophy of AI law should embody Sir Edward Coke's assertion that "Reason is the life of the law." This entails fostering a flexible, rational framework that adapts to the nuanced and rapidly evolving landscape of AI technology. Much like the common law evolves through reasoned judgments, AI law should be dynamic, capable of addressing new challenges and opportunities presented by AI advancements, ensuring a balanced, fair, and forward-looking legal framework for the digital age.

Human communication in English involves words, sentences, and sounds that convey meanings based on the language's semantics. This concept underpins the success of Large Language Models (LLMs), which interpret and recreate language semantics to form new sentences. Extending this idea, LLMs trained on molecular structures can elucidate biology's "semantics." The quality of LLM outputs reflects the richness of Internet content in that domain, indicating the extensive knowledge available online. Foundation models and AI are extensions of human capabilities, transforming us into "Super-Scientists." Alan Turing's view, emphasizing the necessity of technological and AI advancement, aligns with this perspective. Turing's foundational work in computing and AI positions these technologies as natural progressions of human intellect. Similarly, Ada Lovelace, regarded as the first computer programmer, recognized AI and machines as extensions of human thought, capable only of what they are programmed to perform. She said in her memoir (1842):

"The Analytical Engine has no pretensions whatever to originate anything. It can do whatever we know how to order it to perform."

AI and technology are seen not as deviations from human evolution but as continuations of our drive to understand, create, and evolve. They are pivotal in our journey as long as they augment rather than replace human capabilities. Full article can be found here.

Describing a LLMs (Large Language Models) as an alien intelligence is one way to convey the hallucinations or creativity inherent in these models that can be considered as a feature. (See the blog post on LLM with  Human-Like Responses Through Hallucination here https://www.robometricsagi.com/blog/ai-policy#h.czpvisga9x8b). An example will be some of the unique moves made by AlphaGo in a certain chess game. LLMs will make it possible for us to understand and even communicate with other species on planet Earth including one day, one of the oldest of it all, sperm whales. This again points to the non-human or alien nature of such transformer based LLMs. A better way to think about LLMs and more generally the transformer or diffusion model based Foundation Model is that they possess natural intelligence., a natural extension of human intelligence and creativity.

"I Am an American Day" was a patriotic event held on May 21, 1944, in Central Park, New York City. Originating from earlier Americanization Day observances, the event coincided with the broader context of World War II, aiming to foster a sense of national unity and patriotic pride among the American populace, especially in a time of global conflict and uncertainty. 

Judge Learned Hand's speech at this event is celebrated for its eloquent expression on the concept of liberty

One of the quotes from his speech , 

"The spirit of liberty is the spirit of Him who, near two thousand years ago, taught mankind that lesson it has never learned, but has never quite forgotten; that there may be a kingdom where the least shall be heard and considered side by side with the greatest," 

speaks to the essence of inclusive and equitable treatment. In the context of building AI regulations, this quote underscores the need for a balanced and fair approach that considers both large AI companies and small startups.

In the rapidly evolving field of generative AI, such principles are particularly pertinent. An AI regulation or a rule should aim to:

1. Encourage Innovation and Fair Competition: Regulations should not favor incumbents (large AI companies) over new entrants (startups), ensuring a level playing field where innovation can thrive. For instance, in discussions around AI patents or data access, it's crucial that smaller entities aren't disadvantaged. HIPPA on the healthcare side is a great example of a compliance standard that is adaptive with smaller healthcare entities being required to do less and larger  healthcare entities that have the means to do more. 

2. Consider Diverse Interests: As AI applications become more pervasive, the interests of various stakeholders, from multinational corporations to individual developers and public welfare, need to be balanced. This aligns with Judge Hand's call for considering all interests "alongside its own without bias."

3. Avoiding Unintended Consequences: Regulations should be forward-looking and flexible to adapt to new developments in AI, preventing the stifling of innovation due to overly rigid rules.

The significance of Judge Hand's quote in this modern context lies in its reminder that regulations should be designed with empathy and an understanding of all parties involved, ensuring a fair, just, and innovative future for AI technologies. This approach is critical in avoiding monopolistic tendencies, promoting diversity in AI development, and ensuring that benefits of AI are widely and equitably distributed.

he legal profession has witnessed significant shifts with the advent of technology, prompting the American Bar Association to amend its Model Rules in 2012 to emphasize "technological competence." This change mirrors global sentiments, as seen in the UK and Canada, underscoring the imperative for legal professionals to stay abreast of digital advancements. The rise of Generative AI, capable of producing deepfakes, further accentuates this need. Not only must legal professionals understand these technologies, but they must also collaborate with AI experts to ensure comprehensive application in complex cases. This is particularly crucial as technological lapses in understanding can lead to biases in legal decisions. Continuing Legal Education (CLE) efforts, such as those in California, are adapting to this evolving landscape, highlighting the intersection of ethics, law, and technology. Read the full article here.

The "liar's dividend" is a term that refers to the added layer of deniability that dishonest actors gain in an environment where the authenticity of truth itself is in question. In essence, even when a piece of evidence (like a video or photograph) is genuine, the mere existence of technologies like deepfakes or generative AI can provide a shield for liars to claim that the evidence has been manipulated. This phenomenon complicates the already intricate task of discerning truth from falsehood, as every genuine artifact can potentially be dismissed as a fabrication.

In relation to deepfakes and generative AI, the liar's dividend can have far-reaching implications for justice, media, and public discourse. The belief in the "marketplace of ideas" suggests that truth is the proper and sufficient antagonist to error and that a free exchange of ideas is the most efficient way for truth to emerge. As articulated in the First Amendment opinions, one of the most famous quotes related to this concept is from Judge Oliver Wendell Holmes Jr. in his dissent in Abrams v. United States (1919): "The best test of truth is the power of the thought to get itself accepted in the competition of the market." In a world where the line between genuine and fabricated is blurred by advanced technologies, the liar's dividend threatens this very "free trade in ideas." Moreover, as Justice Louis Brandeis astutely observed, "Sunlight is said to be the best of disinfectants." Yet, with the shadow of the liar's dividend looming, even the brightest sunlight might struggle to uncover the truth in the era of deepfakes.

The quote "The more corrupt the state, the more numerous the laws" is attributed to the Roman historian and senator Tacitus, who lived during the first century AD. Tacitus is celebrated for his comprehensive analysis of the early Roman Empire, particularly in his works such as "The Annals" and "Histories." This quote reflects his astute observations of governance during his era. Tacitus likely recognized that in times of corruption or moral decay within a state, rulers may resort to enacting numerous laws and regulations as a facade of order and control. These laws, however, may serve more to consolidate power and perpetuate corruption rather than to uphold justice and virtue.

Today, regulators can draw a valuable lesson from Tacitus' insight. It underscores the importance of crafting clear, effective, and just regulations rather than relying solely on quantity to address societal issues. In the realm of AI and emerging technologies, this quote reminds regulators to prioritize quality over quantity when formulating regulations. A focus on transparent, well-considered oversight can be more effective in fostering innovation, ensuring ethical standards, and preventing corruption, even in complex and rapidly evolving domains like artificial intelligence.

A visual is 650% more powerful than just using an oral presentation in a litigation especially if there is a jury involved. The Connors v. United States case in the late 1980s marked a significant moment in legal history as it was one of the first instances where computer animation was employed in a courtroom setting. The tragic incident in focus was the crash of Delta Air Lines Flight 191. To elucidate the intricate evidence and sequence of events leading up to the crash, the plaintiff's attorneys utilized a detailed 45-minute computer-generated presentation, showcasing the potential of technology in legal proceedings. 

The common sense explanation is that once you see a visual, a judge, jury or a lawyer can’t unsee it. It is registered in our brain and however hard we try, will have an impact on how we see the proceedings that follow. The problem is amplified in a criminal case, the Constitution of the United States, Sixth Amendment,

“In all criminal prosecutions, the accused shall enjoy the right to a speedy and public trial, by an impartial jury of the State and district wherein the crime shall have been committed, which district shall have been previously ascertained by law, and to be informed of the nature and cause of the accusation; to be confronted with the witnesses against him; to have compulsory process for obtaining witnesses in his favor, and to have the Assistance of Counsel for his defence.”, 

where you have the right to an attorney but a deepfake video evidence will require an AI Expert to go through the validity and accuracy of the video. Attorneys and even Judges themselves may not be technology savvy to be able to understand the use and power of the current Generative AI technologies that can generate compelling deepfakes unless they themselves hire an AI Expert to help educate. 

Field Marshal Paul von Hindenburg, a significant figure in German history, served as the President of the German Weimar Republic from 1925 until his passing in 1934. In recognition of his leadership and prominence, the German Zeppelin Company named their largest airship after him — the Hindenburg. This colossal and technologically advanced airship symbolized honor, sophistication, and the pinnacle of human achievement in aviation during its time. However, its tragic end on May 6, 1937, in Manchester Township, New Jersey, suggests that with more rigorous safety protocols, better engineering solutions, and constant vigilance, such a disaster could potentially have been averted. Similarly, Generative AI startups today, like Anthropic, OpenAI, Hugging Face, Cohere, Al21Labs, and Stability.ai, while being at the zenith of AI innovation, need to be proactive in addressing challenges, ethical concerns, and technological limitations to ensure their long-term success and avoid metaphorical "Hindenburg moments."

While the Hindenburg was a marvel in its era, its downfall serves as a poignant reminder of the unpredictable nature of success. As Generative AI companies emerge as frontrunners in the realm of artificial intelligence, they too must remain vigilant. Ensuring transparency in their algorithms, fostering a culture of continuous learning, prioritizing ethical AI use, and maintaining open channels of communication with their stakeholders can help avert potential pitfalls. The exponential pace of innovation and the intense competition in the AI space signify that even these industry sweethearts can face setbacks. However, with foresight, adaptability, and a commitment to responsible AI, these companies can navigate challenges effectively. The Hindenburg's tragic fate and the lessons it imparts emphasize the importance of preparation and humility, reminding Generative AI startups of the delicate balance between achieving great heights and ensuring sustained, grounded success.

Judge Learned Hand, one of the most esteemed jurists in American history, is often celebrated not just for his legal acumen but also for his profound philosophical reflections on liberty and justice. His poignant observation, 

"The spirit of liberty is the spirit which is not too sure that it is right," 

encapsulates a profound wisdom that underscores the humility and caution essential to the judicial process. This statement serves as a reminder that the pursuit of justice is an ever-evolving journey, fraught with the responsibility of constant introspection and skepticism. Its origins lie in a speech Hand delivered in Central Park, New York City, in 1944, during the "I Am an American Day" ceremony. In the age of artificial intelligence, this quote gains renewed significance. Today, as technologies enable the creation of convincing fake evidence, such as deepfake videos, it's crucial to approach such evidence with a measured skepticism, constantly questioning its authenticity and relevance. Hand's words remind us that in an era where truth can be easily manipulated, the spirit of liberty and justice requires an unwavering commitment to discernment and humility.

Litigation in the Generative Native World (The year 2023 and beyond with generative AI) presents a complex and evolving landscape for the judicial system. As technology continues to advance, the cost of litigation is expected to rise, reflecting the intricate nature of cases that involve evidence that may be derived using generative AI. For example, a video or an image. A significant challenge arises as many prosecutors lack expertise in AI, potentially hindering their ability to effectively present or counter arguments. Civil cases, in particular, will witness an expansion in the discovery phase, with strict deadlines for disclosure to ensure fairness and transparency. Using generative AI evidence is easier to fake using Diffusion Models while on the flip side, it is easy to scan through millions of discovery documents using LLMs (Large Language Models). 

In Mahatma Gandhi's philosophy of Satyagraha, or truth-force: “Truth never damages a cause that is just.”

The process of disclosure and discovery will become ever more important, emphasizing the need for thorough investigation and presentation of evidence as it is now possible to create and manipulate an audio or video easily using generative AI. The context and metadata around that evidence will become more important. The reliance on expert witnesses such as AI Experts will intensify, especially in determining the validity and reliability of evidence. Furthermore, the preliminary review of cases will become more important and will be distinct from Rule 401 in the Generative Native World. As the world becomes more dependent on generative AI, the legal system must adapt to address the unique complexity present by AI generally.

"It will be of little avail to the people, that the laws are made by men of their own choice, if the laws be so voluminous that they cannot be read, or so incoherent that they cannot be understood," 

These lines are attributed to James Madison, one of the Founding Fathers of the United States and a pivotal figure in the drafting of the U.S. Constitution. Madison played a central role in the Constitutional Convention of 1787, during which the Constitution was formulated and adopted.

This quote encapsulates Madison's deep concern about the clarity and accessibility of laws crafted by the newly formed U.S. Congress. He expressed this sentiment during debates at the Constitutional Convention, emphasizing the importance of legislation that could be comprehended not only by lawmakers but also by the general public. Madison's wisdom in this regard highlighted his commitment to creating a system of governance that was transparent and accountable to the people.

The Constitutional Convention took place in Philadelphia from May 25 to September 17, 1787, and it was during this historic gathering that the U.S. Constitution was drafted. James Madison is often referred to as the "Father of the Constitution" due to his instrumental role in shaping and drafting the document. His contributions, including the drafting of the Virginia Plan, his advocacy for the separation of powers, and his commitment to individual rights, greatly influenced the final content of the Constitution.

Madison's quote reflects the foundational principles that guided the framers of the Constitution: the need for laws to be clear, comprehensible, and representative of the people's will. These principles continue to be central to the functioning of the U.S. government and the legal system.

The complexity of regulating Artificial Intelligence (AI) can lead to voluminous, intricate legislation that risks becoming incomprehensible, potentially hindering effective governance and accountability in this rapidly evolving field. Stronger AI oversight over extensive regulation is crucial to maintain accessibility and effectiveness in governance, benefiting both legislators and the broader public in this complex and rapidly evolving field.

The cases and ideas discussed, from Louis D. Brandeis's advocacy for transparency to Charles Lindbergh's belief in the marvels of exploration and Alan M. Turing's pioneering work in computer science, collectively emphasize the merits of oversight and transparency over heavy regulation in emerging technologies such as artificial intelligence. They underscore the importance of informed decision-making and data-driven governance in guiding innovation without stifling it. Striking this balance allows technology to venture into uncharted territory, promising progress and marvels while ensuring responsible development and safeguarding against potential misuse. Innovation and progress often require a degree of freedom from strict regulation or confinement. Justice Louis Brandeis one said "Behind every argument is someone's ignorance."

Challenging the status quo and pushing boundaries often stem from questioning prevailing norms and regulations. Innovation thrives when individuals are free to challenge existing constraints. Generative AI resides firmly within this realm, offering a glimpse of what lies on the horizon as information technology advances at an exponential pace. With each passing day, we uncover new capabilities within Foundation Models, and yet, this is merely the inaugural chapter in the story of AI's evolution. Full article can be found here.

"The marketplace of ideas," a concept closely associated with the renowned philosopher John Stuart Mill, holds that addressing harmful or false notions should not involve censorship or regulation. Instead, it champions letting these ideas contend in an unfettered exchange of thoughts and opinions within society. 

According to Mill's perspective, as expounded in his influential essay "On Liberty," published in 1859, this open discourse allows good ideas to naturally triumph over bad ones. Mill's ethical framework of utilitarianism, which underpins his arguments in "On Liberty," extends the principle of individual freedom to society and the state. He believed that by permitting diverse and even contentious ideas to circulate freely, societies would ultimately benefit from the intellectual competition, fostering progress, and the betterment of society. This approach to liberty and open debate remains foundational in discussions of free speech and the regulation of ideas in modern democracies. As Mill eloquently stated in his work, 

"The worth of a state, in the long run, is the worth of the individuals composing it."

This is also the right way to think about the recent development in Generative AI and more generally AI. A state neither has the expertise nor the means to censor or regulate these technologies and related ideas. Instead  the role of the state should be to  facilitate and create the right environment for the unfettered exchange of such ideas, which is essential to the preservation of a free and democratic society.

Sir William Blackstone was an influential English jurist and legal scholar who lived in the 18th century. He is best known for his work "Commentaries on the Laws of England," which became a foundational text in the field of English law and legal philosophy. One of Blackstone's most enduring contributions to the field of criminal law is his famous quote, 

"It is better that ten guilty persons escape than that one innocent suffer." 

This quote encapsulates the core principle of justice that it is preferable for the legal system to err on the side of caution by acquitting individuals who may be guilty rather than risk unjustly convicting innocent individuals. It is better that ten guilty persons escape than that one innocent suffer. This principle, often referred to as Blackstone's ratio or Blackstone's formulation, highlights the importance of protecting individual rights and innocence within the criminal justice system and has had a lasting impact on the development of legal systems around the world.

Blackstone's quote serves as a timeless reminder of the core values that should underpin any just legal system, including the presumption of innocence, the protection of individual rights, and the imperative to prevent the unjust suffering of innocent individuals, even if it means allowing some guilty individuals to go free. It challenges us to continuously improve our legal systems to ensure that justice is served while minimizing the risk of wrongful convictions.

The historical evolution of law school course curriculum for JD students in the United States has followed a remarkable trajectory. Initially characterized by informal apprenticeships, the modernization of legal education began with the founding of Harvard Law School in 1817, marked by a structured approach and the introduction of the case method. This pedagogical shift gained traction as other institutions adopted similar methods, and the American Bar Association's accreditation efforts further standardized curriculum standards. Over time, legal education diversified, incorporating a wide range of legal subjects and offering elective courses to accommodate students' interests. The 20th century saw the establishment of clinical legal education, providing practical experience. Today, JD programs emphasize both theoretical and experiential learning, adapting to changing legal landscapes and societal needs, reflecting the dynamic nature of the legal profession and legal education.

The emergence of Generative AI is reshaping JD education by shifting the emphasis away from rote memorization and toward more practical, experiential learning. This evolution entails integrating AI education into the curriculum, promoting the ethical use of AI, and fostering students' ability to collaborate with AI systems effectively. Law clinics assume a central role, providing students with hands-on experience and leveraging AI to streamline routine tasks, enabling students to focus on client interactions, ethical considerations, and professional skills development. Mentorship programs and continuous adaptation ensure that JD graduates are not only well-versed in AI but also prepared to navigate the AI-augmented legal landscape, making them adept legal professionals equipped for the future. Full article can be found here. 

Most attention these days have been on using Foundation Model either as part of a service using an application or using it via APIs with the model itself being hosted by a service provider such as Google (Bard), OpenAI (GPT3.5, GPT4), Anthropic (Claude) or HuggingFace (Various open source Foundation Models, as examples).  Third party hosted Foundation Models have inherent high cost and risk associated with them such as reduced API performance overtime, privacy and lack of transparency. 

This year at TechCrunch Disrupt, there were sessions, such as The Next AI Evolution Moves into Your Hands by Qualcomm and Meta, that brought out these issues while also highlighting the need for having on-device Foundation Models to address pain points that include immediacy, privacy and security. When a guaranteed millisecond response time is required for upcoming use cases for Foundation Models such as AR/VR, precision location based services, or embodied AI, the models need to be hosted on-device. Privacy and security are also of utmost importance for such Foundation Model use cases. 

At Robometrics® Machines, we are building machines that feel and continuously learn self-supervised on-device using our custom-built Generative AI models specifically optimized for on-device operation. Our North Star is to build an on-edge general AI, Artificial General Intelligence (AGI), and not super intelligent artificial intelligence at scale. Our top two primary use cases are general aviation and healthcare, where  immediacy, privacy and security are critical. We are leaders in Generative AI as we are the first to be able to deploy custom built LLMs that can continuously learn on-device. You can find more about our on-device Foundation Models here.

The evolution of the legal industry's billing practices and the integration of Generative AI in law are reshaping traditional norms and challenging the long-standing billable hour model. Reginald Heber Smith's pioneering efforts in 1914 marked the inception of the billable hour system, which has remained a cornerstone of legal practice. However, this model has faced criticism over the years for encouraging overbilling and commodification of legal services. With the advent of Generative AI, tasks that were once billed hourly, such as contract drafting and legal research, are now accomplished more efficiently and cost-effectively. This technological shift has significant implications for legal professionals, particularly junior associates and entry-level lawyers, as it reduces demand for their roles. Salaries may stagnate or decrease, exacerbating existing challenges in the job market for inexperienced legal professionals. In response to these changes, the legal industry is moving toward an Efficiency-Centric Legal Business Model, similar to how tech giants compensate their software developers, emphasizing project-based or fixed salary compensation with bonuses tied to efficiency and client satisfaction. This paradigm shift reflects the industry's move towards outcome-oriented, client-centric legal services, aligning more closely with real-world practice and enhancing the value delivered to clients. This transformative approach can be termed "Agile Legal." Full article can be found here.