Moving AI Forward: An Interdisciplinary Approach


Wed, December 23, 2020 | 4:00 PM - 7:00 PM EST

Moderator and co-organizer (with Vincent Boucher): Gary Marcus

Confirmed speakers: Ryan Calo, Yejin Choi, Daniel Kahneman, Celeste Kidd, Christof Koch, Luis Lamb, Fei-Fei Li, Adam Marblestone, Margaret Mitchell, Robert Osazuwa Ness, Judea Pearl, Francesca Rossi, Ken Stanley, Rich Sutton, Doris Tsao, Barbara Tversky and more TBA


Panel 1: "Architecture and Challenges"

Yejin Choi, Luis Lamb, Fei-Fei Li, Robert Ness, Judea Pearl, Ken Stanley and Rich Sutton

Panel 2: "Insights from Neuroscience and Psychology"

Danny Kahneman, Christof Koch, Adam Marblestone, Doris Tsao and Barbara Tversky

Panel 3: "Towards AI we Can Trust"

Ryan Calo, Celeste Kidd, Margaret Mitchell and Francesca Rossi

Final Words, Readings, Slides and Relevant Materials

"It takes a village to raise an AI that's ethical, robust, and trustworthy" - Gary Marcus

Ryan Calo


*Ryan Calo's Remark at AI DEBATE 2: Artificial Intelligence Policy: Not Just A Matter of Principles, Ryan Calo, 2020:

Yejin Choi


*Yejin Choi's Remark at AI DEBATE 2: Commonsense AI: Cracking the Longstanding Challenge in AI, Yejin Choi, 2020:

Daniel Kahneman


*Daniel Kahneman's Remark at AI DEBATE 2: System 1 is not non-symbolic, Daniel Kahneman, 2020:

Celeste Kidd


*Celeste Kidd's Remark at AI DEBATE 2: Profound impacts of AI (and its biases) on human beliefs, Celeste Kidd, 2020:

Christof Koch


*Christof Koch's Remark at AI DEBATE 2: Don’t look (anymore) at neuroscience for help with AI, Christof Koch, 2020:

Luis Lamb


*Luis Lamb's Remark at AI DEBATE 2: Neurosymbolic AI: The 3rd Wave, Luis Lamb, 2020:

Final Words

"The AI Debate #2 hosted a convergence of diverse views on the future of AI.

We need from a technical perspective to integrate machine learning and logical) reasoning to build interpretable and explainable AI systems and technologies. This is in line with systems 1 and 2 of Kahneman: we need to integrate AI schools of thought, which ideally walk hand in hand and thus strengthen science.

We have to improve scientific understanding amongst AI paradigms, so as to build AI that benefits humanity and the planet. The world will need a principled AI education for all, since AI will be the key technology of the next decades, if not of the XXI century." - Luis Lamb

Readings and Relevant Materials

"Readings that harmonize with the great AI Debate #2" - Luis Lamb

Neurosymbolic AI: The 3rd Wave, Artur d’Avila Garcez and Luis Lamb, 2020:

Thinking Fast and Slow in AI, Booch et al., 2020:

Neural-Symbolic Cognitive Reasoning, D'Avila Garcez, Artur S., Lamb, Luís C., Gabbay, Dov, 2009:

Rebooting AI : Building Artificial Intelligence We Can Trust, Gary Marcus and Ernest Davis, 2019:

Causality, Judea Pearl, 2009 (2nd Edition):

Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World, Leslie Valiant, 2013:

Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP, Prates et al., 2019:

Learning a SAT Solver from Single-Bit Supervision, Selsam et al., 2019:

Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective, Lamb et al., 2020:

Thinking, Fast and Slow, Daniel Kahneman, 2011:,_Fast_and_Slow

Fei-Fei Li


*Fei-Fei Li's Remark at AI DEBATE 2: In search of the next AI North Star: a tale of two kittens, Fei-Fei Li, 2020:

Adam Marblestone


*Adam Marblestone's Remark at AI DEBATE 2: Leveraging neuro-technology for AI, Adam Marblestone, 2020:

Margaret Mitchell


*Margaret Mitchell's Remark at AI DEBATE 2: Ethics in the Vision and Language of Artificial Intelligence, Margaret Mitchell, 2020:

Robert Ness


*Robert Ness's Remark at AI DEBATE 2: Causal Reasoning with (Deep) Probabilistic Programming, Robert Ness, 2020:

Judea Pearl


*Judea Pearl’s Remark at AI DEBATE 2: The Domestication of Causal Reasoning: Cultural and Methodological Implications, Judea Pearl, 2020:

What I would have said had I been given six (6), instead of three (3) minutes, Judea Pearl, 2020:

Readings and Relevant Materials

The Seven Tools of Causal Inference, Judea Pearl, 2016: (Summary:

Radical Empiricism and Machine Learning Research, Judea Pearl, 2020:

Data versus Science: Contesting the Soul of Data-Scienc, Judea Pearl, 2020:

Francesca Rossi


*Francesca Rossi’s Remark at AI DEBATE 2: Thinking Fast and Slow in AI: Towards more general and trustworthy AI, Francesca Rossi, 2020:

Kenneth O. Stanley


*Kenneth O. Stanley’s Slides presented at AI DEBATE 2: Open-Endedness, Evolution, and AI, Kenneth O. Stanley, 2020:


Why Greatness Cannot Be Planned: The Myth of the Objective, Kenneth O. Stanley and Joel Lehman, 2015th Edition:

Rich Sutton


*Rich Sutton's Remark at AI DEBATE 2: Reinforcement Learning is the Computational Theory of Intelligence, Rich Sutton, 2020:

Doris Tsao


*Doris Tsao's Remark at AI DEBATE 2: How the brain builds a model of the world: insights from neuro-science, Doris Tsao, 2020:

Barbara Tversky


*Barbara Tversky's Remark at AI DEBATE 2: Thinking with the Body and the World, Barbara Tversky, 2020:


Leading computer scientists debate the next steps for AI in 2021, By Ben Dickson | January 2, 2021 | VentureBeat:

AI Debate 2: Night of a thousand AI scholars, By Tiernan Ray | December 23, 2020 | ZDNet:

‘The Debate of the Next Decade’ – AI Debate 2 Explores AGI and AI Ethics, Reporter: Yuan Yuan | Editor: Michael Sarazen | December 24, 2020 | Synced:



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