UnlikelyAI Webinar: Understanding AI Reasoning through Kahneman’s "Thinking, Fast and Slow"

#AITrust #AIReasoning #NeurosymbolicAI #airesearch When we try to build machines that reason, we have only one fully worked example of a reasoning system to look at: ourselves. So it's no surprise that AI research looks to cognitive science for design cues. Kahneman's Thinking, Fast and Slow is one framework in human psychology that has been applied when designing and making sense of neurosymbolic AI systems, but does that analogy illuminate, or does it constrain? In our latest UnlikelyAI webinar, Callum Hackett (Head of Research, UnlikelyAI) and Louis Mahon (Senior Applied Scientist, UnlikelyAI) wrestled with exactly that question. They took the analogy apart property by property and asked which ones hold up, which are borrowed for credibility, and what actually justifies hybrid AI architectures in practice. 00:00 — Welcome and introductions 02:00 — How AI has always borrowed from human thinking 04:00 — Neural networks: rooted in 1940s neuroscience 05:30 — Symbolic AI: treating language like logic 07:00 — Evolution and behavioural psychology as inspirations 08:30 — Who was Daniel Kahneman? 11:00 — The myth of the rational agent 13:00 — Is Steve a librarian or a farmer? 16:00 — The bat and ball problem 18:30 — System 1 and System 2, defined 22:30 — Fast vs slow, automatic vs deliberate 26:30 — Louis on neural vs symbolic computation 32:00 — Why hybrid systems matter 34:00 — AlphaGo as a neurosymbolic success story 37:30 — Does the System 1 / System 2 analogy hold up? 44:00 — Where Kahneman thought AI got it wrong 46:30 — Q&A: How does the brain switch between systems? 50:00 — Q&A: Are neural and symbolic really separate? 53:00 — Closing remarks More information: UnlikelyAI LinkedIn:   / unlikely-ai   UnlikelyAI website: https://www.unlikely.ai/ UnlikelyAI Lab website: https://lab.unlikely.ai/ UnlikelyAI webinar channel: https://watch.getcontrast.io/unlikelyai