Speakers:
Biyu Jade He (NYU Medical Centre)
Hakwan Lau (UCLA)
Victor Lamme (University of Amsterdam)
Johannes Fahrenfort (University of Amsterdam)
Where in the brain are the neural correlates of perceptual consciousness? Some leading theories of consciousness, including global workspace and higher-order thought theories, hold that these correlates centrally involve prefrontal cortex. Other leading theories, including first-order and integrated information theories, hold that these correlates centrally involve sensory cortices, with prefrontal cortex playing at most a secondary role. In recent years much experimental evidence has been brought to bear on both sides of the question.
In this debate, Hakwan Lau (UCLA) and Biyu Jade He (NYU) will defend the view that neural activity in prefrontal cortex is important for conscious perception, while Victor Lamme (Amsterdam) and Johannes Fahrenfort (Amsterdam) will argue that prefrontal activity is not important for conscious perception.
The NYU Center for Bioethics is pleased to welcome submissions of abstracts for its 1st Annual Philosophical Bioethics Workshop, to be held at NYU on Friday, April 3, 2020.
We are seeking to showcase new work in philosophical bioethics, including (but not limited to) neuroethics, environmental ethics, animal ethics, reproductive ethics, research ethics, ethics of AI, data ethics, and clinical ethics.
Our distinguished keynote speaker will be Frances Kamm.
There will be four additional slots for papers chosen from among the submitted abstracts, including one slot set aside for a graduate student speaker. The most promising graduate student submission will be awarded a Graduate Prize, which includes coverage of travel expenses (up to $500, plus accommodation for two nights) as well as an award of $500. Please indicate in your submission email whether you would like to be considered for the Graduate Prize.
Please submit extended abstracts of between 750 and 1,000 words to philosophicalbioethics@gmail.com by 11:59 pm EST on Friday, January 24, 2020. Abstracts should be formatted for blind review and should be suitable for presentation in 30-35 minutes. Notification of acceptance will take place via email by Friday, February 14, 2020.
When submitting your abstract, please also indicate whether you would be interested in serving as a commentator in the event that your abstract is not selected for presentation. We will be inviting four additional participants to serve as commentators.
NYU’s Center for Mind, Brain, and Consciousness will host a debate on the relationship between memory and imagination.
This event will be held in person at Jurow Hall, Silver Center, 31 Washington Place, and will also be streamed over Zoom at: tinyurl.com/nyumemory
Attendance is free but registration (requiring proof of vaccination) is required for non-NYU guests. Please register no later than April 25th at: forms.gle/tNqkBYPDcZxTdxY38
The NYU Mind, Ethics, and Policy Program is thrilled to be hosting a talk by David Chalmers on whether large language models can be sentient.
About the talk
Artificial intelligence systems—especially large language models, giant neural networks trained to predict text from the internet—have recently shown remarkable abilities. There has been widespread discussion of whether some of these language models might be sentient. Should we take this idea seriously? David Chalmers will discuss the underlying issue and try to break down the strongest reasons for and against.
The talk, which is free and open to the public, will take place on October 13 2022 from 5:00-6:30pm ET. The in-person location will be Jurow Lecture Hall (inside the Silver Center at 32 Waverly Place), and the virtual location will be Zoom (you can sign up to receive a link by clicking “Register here” below). There will also be a light reception from 6:30-7:30pm in the Silverstein Lounge (immediately outside of the Jurow Lecture Hall).
– If you plan to attend in person, please be prepared to show proof of full vaccination.
– If you plan to attend virtually, please check your email for a link in advance of the event.
About the speaker
David Chalmers is University Professor of Philosophy and Neural Science and co-director of the Center for Mind, Brain, and Consciousness at NYU. He is the author of The Conscious Mind (1996), Constructing the World (2010), and Reality+: Virtual Worlds and the Problems of Philosophy (2022). He co-founded the Association for the Scientific Study of Consciousness and the PhilPapers Foundation. He is known for formulating the “hard problem” of consciousness, which inspired Tom Stoppard’s play The Hard Problem, and for the idea of the “extended mind,” which says that the tools we use can become parts of our minds.
Thank you to our co-sponsors for your generous support of this event:
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NYU Center for Bioethics
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NYU Center for Mind, Brain, and Consciousness
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NYU Minds, Brains, and Machines Initiative
This talk explores the reflexive nature of consciousness, which consists primarily in the fact that a state of consciousness has a reflexive relation to the subject who has that state, so that the subject can typically be aware of itself as having that state. Comparing Kant’s, Fichte’s, and selected contemporary analytic theories of this reflexivity shows that there is a crucial difference in the way the relation between form (or mode) and content of a state of consciousness is conceived. The first part examines Kant’s formal theory of consciousness: reflexivity is understood not in terms of a self-referential content resulting from a reflection on the state of the subject, but as the universal transcendental form that any content must have in order to be representationally significant and potentially conscious to the subject. The second part examines Fichte’s departure from Kant in his theory of a self-positing consciousness: in the original act of self-positing, the mere form of reflexivity is turned into a self-referential content that determines the subject as an object from the absolute standpoint of consciousness. The third part examines analytic theories that explain the reflexivity (or what is often called the subjective character) of consciousness on a model of mental indexicality. These theories tend to reduce reflexivity to an objective constituent of content that, although often implicit, can be read off from the subject’s contextual situatedness in nature. In conclusion, Kant’s theory can be understood as a moderate, human-centered kind of perspectivism that navigates between Fichtean absolute subjectivity and a naturalist absolute objectivity.
Registration is free but required. A registration link will be shared via email with our department mailing lists a few weeks before the event. Please contact Jack Mikuszewski at jhm378@nyu.edu if you did not receive a registration link.
The Philosophy Department provides reasonable accommodations to people with disabilities. Requests for accommodations should be submitted to philosophy@nyu.edu at least two weeks before the event.
A two-day conference on the philosophy of deep learning, organized by Ned Block (New York University), David Chalmers (New York University) and Raphaël Millière (Columbia University), and jointly sponsored by the Presidential Scholars in Society and Neuroscience program at Columbia University and the Center for Mind, Brain, and Consciousness at New York University.
About
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?
A pre-conference debate on Friday, March 24th will tackle the question “Do large language models need sensory grounding for meaning and understanding ?”. Speakers include Jacob Browning (New York University), David Chalmers (New York University), Yann LeCun (New York University), and Ellie Pavlick (Brown University / Google AI).
Conference speakers
- Cameron Buckner (University of Houston)
- Rosa Cao (Stanford University)
- Ishita Dasgupta (DeepMind)
- Nikolaus Kriegeskorte (Columbia University)
- Brenden Lake (New York University / Meta AI)
- Grace Lindsay (New York University)
- Tal Linzen (New York University / Google AI)
- Raphaël Millière (Columbia University)
- Nicholas Shea (Institute of Philosophy, University of London)
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 phildeeplearning@gmail.com by January 22nd, 2023 (11.59pm EST).
https://philevents.org/event/show/106406
Yejin Choi is Wissner-Slivka Professor and a MacArthur Fellow at the Paul G. Allen School of Computer Science & Engineering at the University of Washington. She is also a senior director at AI2 overseeing the project Mosaic and a Distinguished Research Fellow at the Institute for Ethics in AI at the University of Oxford. Her research investigates if (and how) AI systems can learn commonsense knowledge and reasoning, if machines can (and should) learn moral reasoning, and various other problems in NLP, AI, and Vision including neuro-symbolic integration, language grounding with vision and interactions, and AI for social good. She is a co-recipient of 2 Test of Time Awards (at ACL 2021 and ICCV 2021), 7 Best/Outstanding Paper Awards (at ACL 2023, NAACL 2022, ICML 2022, NeurIPS 2021, AAAI 2019, and ICCV 2013), the Borg Early Career Award (BECA) in 2018, the inaugural Alexa Prize Challenge in 2017, and IEEE AI’s 10 to Watch in 2016.
Join us for a special live taping of the Clearer Thinking podcast. Host Spencer Greenberg and guest Jeff Sebo will discuss the moral status of insects and AI systems, as well as other thorny questions in global priorities research.
About the speakers
Jeff Sebo is Associate Professor of Environmental Studies, Affiliated Professor of Bioethics, Medical Ethics, Philosophy, and Law, Director of the Animal Studies M.A. Program, Director of the Mind, Ethics, and Policy Program, and Co-Director of the Wild Animal Welfare Program at New York University. He is the author of Saving Animals, Saving Ourselves (2022) and co-author of Chimpanzee Rights (2018) and Food, Animals, and the Environment (2018). He is also an executive committee member at the NYU Center for Environmental and Animal Protection, a board member at Minding Animals International, an advisory board member at the Insect Welfare Research Society, a senior research fellow at the Legal Priorities Project, and a mentor at Sentient Media.
Spencer Greenberg is an entrepreneur and mathematician with a focus on improving human well-being. He’s the founder of ClearerThinking.org, which provides 70 free, digital tools to help people make better decisions and improve their lives, as well as the host of the Clearer Thinking podcast. Spencer is also the founder of Spark Wave, an organization that conducts psychology research and builds psychology-related products designed to help benefit the world. He has a Ph.D. in applied math from New York University, with a specialty in machine learning, and his work has been featured by numerous major media outlets, including The Wall Street Journal, the Independent, the New York Times, Gizmodo, and more.
Thank you to Effective Altruism New York City for their generous support of this event.