Summary of older AI and Collective Intelligence discussions

        The recent progress in Artificial Intelligence provides both challenges and opportunities for scientific collective intelligence. Among the most notable examples of AI progress are ChatGPT and other Large Language Models, which have shown unexpected capabilities (Wei 2022, Mitchell 2023), and AlphaFold, which can predict the 3D shape of proteins from their genetic sequence with unprecedented accuracy (Jumper 2021). The development of AlphaFold has been recognized by the award of the 2014 Nobel Prize in Chemistry.

Challenges

          AI poses specific challenges for science. There are many reports of errors in statements from ChatGPT and from other AI systems. The types of errors and blind spots seem different from those more common in humans.

            These AI systems consist of neural networks with billions to trillions of parameters (Mitchell,…

Contribution received from Christopher Wills, Professor Emeritus of Biology, University of California, San Diego

The size increase in the human brain, which is exceptionally large for a primate having such a body mass (Miller, 2019), has led to hypotheses of a co-evolutionary positive feedback driving brain evolution. Proposed mechanisms are positive feedback between brain size and culture or language (Wills, 1993; Deacon, 1998) or between the brain sizes of humans engaged in a socio-cognitive evolutionary arms race (Dunbar, 1998; Miller, 2011). Drawing an analogy with these processes affecting the evolution of individual intelligence, we can expect co-evolution to lead to accelerated progress of AI and human collective intelligence. This is likely to be primarily cultural but given enough time it may lead to biological evolutionary changes such as the recent repeated selection of lactose tolerance in cultures that have domestic animals for milk production.

- Wills C. 1993. The R…