Event Description
The conference will explore current issues in AI research from a philosophical perspective, with particular attention to recent work on deep artificial neural networks. The goal is to bring together philosophers and scientists who are thinking about these systems in order to gain a better understanding of their capacities, their limitations, and their relationship to human cognition. The conference will focus especially on topics in the philosophy of cognitive science (rather than on topics in AI ethics and safety). It will explore questions such as:
- What cognitive capacities, if any, do current deep learning systems possess?
- What cognitive capacities might future deep learning systems possess?
- What kind of representations can we ascribe to artificial neural networks?
- Could a large language model genuinely understand language?
- What do deep learning systems tell us about human cognition and vice versa?
- How can we develop a theoretical understanding of deep learning systems?
- How do deep learning systems bear on philosophical debates such as rationalism vs empiricism and classical vs. nonclassical views of cognition?
- What are the key obstacles on the path from current deep learning systems to human-level cognition?
Event Speakers
- Cameron Buckner, Associate Professor of Philosophy, University of Houston
- Rosa Cao, Assistant Professor of Philosophy, Stanford University
- Ishita Dasgupta, Research Scientist, DeepMind
- Nikolaus Kriegeskorte, Professor of Psychology and Neuroscience, Columbia University
- Brenden Lake, Assistant Professor of Psychology and Data Science, New York University
- Grace Lindsay, Assistant Professor of Psychology and Data Science, New York University
- Tal Linzen, Assistant Professor of Linguistics and Data Science, New York University
- Raphaël Millière, Presidential Scholar in Society and Neuroscience, Columbia University
- Nicholas Shea, Professor of Philosophy, Institute of Philosophy, University of London
A pre-conference debate on March 24 will address whether large language models need sensory grounding for meaning and understanding. Speakers include:
- Jacob Browning, Postdoctoral Associate, New York University
- David Chalmers, University Professor of Philosophy and Neural Science, New York University
- Yann LeCun, Silver Professor of Data Science, Computer Science, Neural Science, and Electrical Engineering, New York University
- Ellie Pavlick, Assistant Professor of Computer Science, Brown University
Event Information
Free and open to the public; event registration is now full. However, the conference will be live-streamed on phildeeplearning.github.io/streaming. Please visit the event website for additional information or email [email protected] with any questions.
This event is co-organized by Presidential Scholars in Society and Neuroscience at Columbia University as part of the Seminars in Society and Neuroscience series and by the Center for Mind, Brain, and Consciousness at New York University.
The Center for Mind, Brain, and Consciousness at New York University provides reasonable accommodations to people with disabilities. Requests for accommodations should be submitted to [email protected] at least two weeks before the event.
Call for Abstracts
We invite abstract submissions for a few short talks and poster presentations related to the topic of the conference. Submissions from graduate students and early-career researchers are particularly encouraged. Please send a title and abstract (500-750 words) to [email protected] by January 22nd, 2023 (11.59 PM EST). Please note that we are unable to cover travel expenses for selected talks and posters.
