AI to Make us Super-Scientist, not Super-humans
Human communication in a language such as English consists of words, sentences and sound to convey a meaning, based on the underlying semantics of the language. This is also why LLMs (Large Language Models) have been so successful since it consumes these words and sentences — although no sounds so far — and is able to construct the underlying semantics of language to create new sentences. Similarly, a LLM trained on sequences of very large numbers of molecules and their structure can tell us about the underlying biology - the semantics of life itself. The quality of LLM output is a reasonable indication of how good that domain or topic exists on the Internet, which accounts for a large amount of the world's knowledge. Foundation Models such as transformer based LLMs and artificial intelligence (AI) generally are extensions of humans and make us Super-Scientist.
The pioneering computer scientist Alan M. Turing, known for his profound contributions to the early development of computer science and AI. Turing famously said:
"We can only see a short distance ahead, but we can see plenty there that needs to be done."
which implies the inevitability and inherent necessity of advancing technology and AI. Turing's work laid the groundwork for modern computing and AI, suggesting that these technologies are a natural progression of human intellectual endeavor.
Another thought that aligns closely with the idea of AI being a natural extension of human intelligence and creativity is from Ada Lovelace, often considered the first computer programmer. 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.
AI and advanced technology are seen as integral, perhaps even inevitable, outcomes of human development and creativity. These technologies are less a break from natural human evolution and more a continuation of our innate drive to understand, create, and evolve. These make us Super-Scientist as long as we build AI to augment humans and not replace them.
References
Further read
From Infinite Improbability to Generative AI: Navigating Imagination in Fiction and Technology
Human vs. AI in Reinforcement Learning through Human Feedback
Generative AI for Law: The Agile Legal Business Model for Law Firms
Generative AI for Law: From Harvard Law School to the Modern JD
Unjust Law is Itself a Species of Violence: Oversight vs. Regulating AI
Generative AI for Law: Technological Competence of a Judge & Prosecutor