Machine Learning Street Talk (MLST)

Prof. Daniel Dennett - Could AI Counterfeit People Destroy Civilization? (SPECIAL EDITION)

04 Jun 2023

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Please check out Numerai - our sponsor using our link @ http://numer.ai/mlst Numerai is a groundbreaking platform which is taking the data science world by storm. Tim has been using Numerai to build state-of-the-art models which predict the stock market, all while being a part of an inspiring community of data scientists from around the globe. They host the Numerai Data Science Tournament, where data scientists like us use their financial dataset to predict future stock market performance. Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 Twitter: https://twitter.com/MLStreetTalk YT version: https://youtu.be/axJtywd9Tbo In this fascinating interview, Dr. Tim Scarfe speaks with renowned philosopher Daniel Dennett about the potential dangers of AI and the concept of "Counterfeit People." Dennett raises concerns about AI being used to create artificial colleagues, and argues that preventing counterfeit AI individuals is crucial for societal trust and security. They delve into Dennett's "Two Black Boxes" thought experiment, the Chinese Room Argument by John Searle, and discuss the implications of AI in terms of reversibility, reontologisation, and realism. Dr. Scarfe and Dennett also examine adversarial LLMs, mental trajectories, and the emergence of consciousness and semanticity in AI systems. Throughout the conversation, they touch upon various philosophical perspectives, including Gilbert Ryle's Ghost in the Machine, Chomsky's work, and the importance of competition in academia. Dennett concludes by highlighting the need for legal and technological barriers to protect against the dangers of counterfeit AI creations. Join Dr. Tim Scarfe and Daniel Dennett in this thought-provoking discussion about the future of AI and the potential challenges we face in preserving our civilization. Don't miss this insightful conversation! TOC: 00:00:00 Intro 00:09:56 Main show kick off 00:12:04 Counterfeit People 00:16:03 Reversibility 00:20:55 Reontologisation 00:24:43 Realism 00:27:48 Adversarial LLMs are out to get us 00:32:34 Exploring mental trajectories and Chomsky 00:38:53 Gilbert Ryle and Ghost in machine and competition in academia 00:44:32 2 Black boxes thought experiment / intentional stance 01:00:11 Chinese room 01:04:49 Singularitarianism 01:07:22 Emergence of consciousness and semanticity References: Tree of Thoughts: Deliberate Problem Solving with Large Language Models https://arxiv.org/abs/2305.10601 The Problem With Counterfeit People (Daniel Dennett) https://www.theatlantic.com/technology/archive/2023/05/problem-counterfeit-people/674075/ The knowledge argument https://en.wikipedia.org/wiki/Knowledge_argument The Intentional Stance https://www.researchgate.net/publication/271180035_The_Intentional_Stance Two Black Boxes: a Fable (Daniel Dennett) https://www.researchgate.net/publication/28762339_Two_Black_Boxes_a_Fable The Chinese Room Argument (John Searle) https://plato.stanford.edu/entries/chinese-room/ https://web-archive.southampton.ac.uk/cogprints.org/7150/1/10.1.1.83.5248.pdf From Bacteria to Bach and Back: The Evolution of Minds (Daniel Dennett) https://www.amazon.co.uk/Bacteria-Bach-Back-Evolution-Minds/dp/014197804X Consciousness Explained (Daniel Dennett) https://www.amazon.co.uk/Consciousness-Explained-Penguin-Science-Dennett/dp/0140128670/ The Mind's I: Fantasies and Reflections on Self and Soul (Hofstadter, Douglas R; Dennett, Daniel C.) https://www.abebooks.co.uk/servlet/BookDetailsPL?bi=31494476184 #DanielDennett #ArtificialIntelligence #CounterfeitPeople

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Machine Learning Street Talk (MLST)

Prof. Daniel Dennett - Could AI Counterfeit People Destroy Civilization? (SPECIAL EDITION)

This episode hasn't been transcribed yet

Other episodes from Machine Learning Street Talk (MLST)

Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

Why Every Brain Metaphor in History Has Been Wrong [SPECIAL EDITION]

Adversarial Examples and Data Modelling - Andrew Ilyas (MIT)

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