Artificial intelligence (AI) promises to automate and scale solutions to perennial accessibility challenges (e.g., generating image descriptions for blind users). However, research shows that AI-bias disproportionately impacts people already marginalized based on their race, gender, or disabilities, raising questions about potential impacts in addition to AI’s promise. In this talk, Cynthia Bennett will overview broad concerns at the intersection of AI, disability, and accessibility. She will then share details about one project in this research space that led to guidance on human and AI-generated image descriptions that account for subjective and potentially sensitive descriptors around race, gender, and disability of people in images.
The COVID-19 pandemic is said to be a once-in-a-century incident, and it brought to us a sense of crisis at various levels. What is a crisis, though? Can any unnerving moment or period be called a crisis, or are there different dimensions of a crisis to which we need to be attentive? Is solidarity possible after experiencing a crisis like Covid-19? Can Buddhism make any contribution to facilitating solidarity? This presentation explores the meaning and nature of a crisis and our responses to it by drawing on modern Korean political thinker Pak Ch’iu’s (1909–1949) analysis of crisis and feminist-Buddhist thinker Kim Iryŏp’s (1896–1971) Buddhist philosophy. By doing so, this presentation considers what social, political, existential, and even religious meaning we can draw from our experience of crises, and what questions these insights present to us.
With responses from Karsten Struhl (John Jay College of Criminal Justice, CUNY)
Presented by THE COLUMBIA SOCIETY FOR COMPARATIVE PHILOSOPHY
RSVP is required for dinner. If you would like to participate in our dinner, a $30 fee is required. Please contact Lucilla at lm3335@columbia.edu for further information.
Conceptual misalignment is a pervasive phenomenon in the studies of Non-Western philosophy and the History of Philosophy (NW&HP). However, conceptual misalignment is often undetected, unsuspected, or seen as a hurdle that NW&HP materials need to overcome to contribute to contemporary discussions. Specifically, conceptual misalignment refers to the following: In the process of crystalizing NW&HP materials, a linguistic coordination of concepts is formed between the speaker, i.e., NW&HP, and its context of contemporary anglophone philosophy. However, in philosophically meaningful ways, the original NW&HP concept and its anglophone counterpart misalign. This misalignment is particularly intricate and hard to detect when it comes to emotion concepts, as they are thought to involve phenomenal and/or intentional features. Through investigating the concept of emotion in Chinese philosophy, I propose a refocusing on conceptual misalignment as a method of cross-cultural comparative and history of philosophy. Moreover, I argue that conceptual misalignment is an important resource for contemporary conceptual engineering and amelioration projects.
With responses from Andrew Lambert (College of Staten Island, CUNY)
RSVP is required for dinner. Dinner will take place at a nearby restaurant. Please contact Lucilla at lm3335@columbia.edu for further information.
In Sanskrit epistemology, philosophers are preoccupied with the notion of pramā. A pramā, roughly, is a mental event of learning or knowledge-acquisition. Call any such mental event a knowledge-event. In A Confection of Refutation (Khaṇḍanakhaṇḍakhādya), the 12th century philosopher and poet Śrīharṣa argued that knowledge-events are indefinable. Any satisfactory (and therefore non-circular) definition of knowledge-events will have to include an anti-luck condition that doesn’t appeal back to the notion of learning or knowledge-acquisition itself. But there is no such anti-luck condition. What is novel about Śrīharṣa’s argument is that it is motivated by his commitment to a certain “knowledge first” approach to epistemology: the view that knowledge-events are epistemically prior to other non-factive mental states and events. On this view, when we are trying to determine whether an agent has undergone a knowledge-event, we don’t initially ascribe to them some other non-factive mental event, and then check if that event meets some further conditions (like truth or reliability) necessary for it to count as a knowledge-event; rather, we treat certain mental events by default as knowledge-events until a defeater comes along. Surprisingly, Śrīharṣa argues that this kind of “knowledge first” epistemology should give us reason to doubt whether our ordinary attributions of knowledge-events are reliably tracking any sui generis psychological kind. In this talk, I reconstruct Śrīharṣa’s position.
With responses from Rosanna Picascia (Swarthmore College)
RSVP is required for dinner. Dinner will take place at a nearby restaurant. Please contact Lucilla at lm3335@columbia.edu for further information.
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
When someone is in a conscious state, must they be aware of that state? The Buddhist philosopher Dignāga offers a brilliant route to answering this question by leveraging the role awareness might play as a constraint on memory. I begin by clarifying his strategy and what conclusions it might be used to establish. Here I examine different candidate directions of explanation between consciousness and inner awareness. I interpret the metaphor of consciousness as a lamp that lights itself, and use the metaphor to distinguish between his view and contemporary higher-order theories of consciousness. I then turn to explain why the memory argument fails. The first main problem is that, contrary to Dignāga’s contemporary defenders, there is no good way to use the argument to reach a conclusion about all conscious states. The second main problem is that the proposed awareness constraint on memory is highly problematic, in tension both with ancient objections as well as current psychology.
With responses from Lu Teng (NYU Shanghai)
How does the brain cope with Complexity? How do we make decisions when confronted with practically infinite streams of information?
The conference showcases cutting edge research on these questions in Neuroscience and Psychology (neural mechanisms of cognitive control, exploration, decision-making, information demand, memory and creativity), Computer Science (artificial intelligence of curiosity and intrinsic motivation) and Economics (decision making and information demand). Alongside formal presentations, the conference will encourage ample interactions among faculty, students and postdocs through informal discussions and poster presentations.
Submissions for poster presentations and travel awards are due February 15, 2023. Please visit the call for submissions for complete requirements.
Event Information
Free and open to the public. Registration is required and will open shortly. All in-person attendees must follow Columbia’s COVID-19 policies. Visitors will be asked to provide proof of COVID-19 vaccination. Online attendees will receive a Zoom link. Please email events@zi.columbia.edu with any questions.
The International Conference on Brain Informatics (BI) series has established itself as the world’s premier research conference on Brain Informatics, which is an emerging interdisciplinary and multidisciplinary research field that combines the efforts of Cognitive Science, Neuroscience, Machine Learning, Data Science, Artificial Intelligence (AI), and Information and Communication Technology (ICT) to explore the main problems that lie in the interplay between human brain studies and informatics research.
The 16th International Conference on Brain Informatics (BI’23) provides a premier international forum to bring together researchers and practitioners from diverse fields for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences on brain Informatics research, brain-inspired technologies and brain/mental health applications.
The key theme of the conference is “Brain Science meets Artificial Intelligence“.
The BI’23 solicits high-quality original research and application papers (both full paper and abstract submissions). Relevant topics include but are not limited to:
- Track 1: Cognitive and Computational Foundations of Brain Science
- Track 2: Human Information Processing Systems
- Track 3: Brain Big Data Analytics, Curation and Management
- Track 4: Informatics Paradigms for Brain and Mental Health Research
- Track 5: Brain-Machine Intelligence and Brain-Inspired Computing
Keynote Speakers
Professor Emery N. Brown
MIT, Massachusetts General Hospital, USA
Profile: Emery Neal Brown is the Warren M. Zapol Professor of Anesthesia at Harvard Medical School and at Massachusetts General Hospital (MGH), and a practicing anesthesiologist at MGH. At MIT he is the Edward Hood Taplin Professor of Medical Engineering and professor of computational neuroscience, the Associate Director of the Institute for Medical Engineering and Science, and the Director of the Harvard–MIT Program in Health Sciences and Technology. Brown is one of only 19 individuals who has been elected to all three branches of the National Academies of Sciences, Engineering, and Medicine, as well as the first African American and the first anesthesiologist to be elected to all three National Academies.
Professor Bin He
Carnegie Mellon University, USA
Profile: Bin He is the Trustee Professor of Biomedical Engineering, Professor of the Neuroscience Institute, and Professor by courtesy of Electrical and Computer Engineering at Carnegie Mellon University. Dr. He has made significant research and education contributions to the field of neuroengineering and biomedical imaging, including functional biomedical imaging, noninvasive brain-computer interface (BCI), and noninvasive neuromodulation. His pioneering research has helped transforming electroencephalography from a 1-dimensional detection technique to 3-dimensional neuroimaging modality. His lab demonstrated for the first time for humans to fly a drone and control a robotic arm just by thinking about it using a noninvasive BCI. He is an elected Fellow of International Academy of Medical and Biological Engineering (IAMBE), American Institute of Medical and Biological Engineering (AIMBE), Biomedical Engineering Society (BMES), and IEEE. Dr. He served as a Past President of the IEEE Engineering in Medicine and Biology Society, the Editor-in-Chief of IEEE Transactions on Biomedical Engineering from 2013-2018, the Chair of the International Academy of Medical and Biological Engineering from 2018-2021. Dr. He has been a Member of NIH BRAIN Initiative Multi-Council Working Group from 2014-2019.
Professor John Ngai
NIH BRAIN Initiative, USA
Profile: John J. Ngai, Ph.D., is the Director of the NIH’s Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative. Dr. Ngai earned his bachelor’s degree in chemistry and biology from Pomona College, Claremont, California, and Ph.D. in biology from the California Institute of Technology (Caltech) in Pasadena. He was a postdoctoral researcher at Caltech and at the Columbia University College of Physicians and Surgeons before starting his faculty position at the University of California at Berkeley. During more than 25 years as a Berkeley faculty member, Dr. Ngai has trained 20 undergraduate students, 24 graduate students and 15 postdoctoral fellows in addition to teaching well over 1,000 students in the classroom. His work has led to the publication of more than 70 scientific articles in some of the field’s most prestigious journals and 10 U.S. and international patents. Dr. Ngai has received many awards including from the Sloan Foundation, Pew Charitable Trusts, and McKnight Endowment Fund for Neuroscience. As a faculty member, Dr. Ngai has served as the director of Berkeley’s Neuroscience Graduate Program and Helen Wills Neuroscience Institute. He has also provided extensive service on NIH study sections, councils and steering groups, including as previous co-chair of the NIH BRAIN Initiative Cell Census Consortium Steering Group. Dr. Ngai oversees the long-term strategy and day-to-day operations of the NIH BRAIN Initiative as it strives to revolutionize our understanding of the brain in both health and disease.
Professor Helen Mayberg
Icahn School of Medicine at Mount Sinai, USA
Profile: Helen Mayberg is a neurologist recognized for her neuroimaging studies of brain circuits in depression and their translation to the development of deep brain stimulation as a novel therapeutic for treatment resistant patients. Born and raised in Southern California, she received a BA in Psychobiology from UCLA and a MD from the University of Southern California, then trained in Neurology at Columbia’s Neurological Institute in New York and did a research fellowship in nuclear medicine at Johns Hopkins. She had early academic appointments at Johns Hopkins and the University of Texas Health Sciences Center in San Antonio, held the inaugural Sandra Rotman Chair in Neuropsychiatry at the University of Toronto, the first Dorothy C. Fuqua Chair in Psychiatric Imaging and Therapeutics at Emory University and is now the Mount Sinai Professor of Neurotherapeutics at the Icahn School of Medicine where she is founding Director of the Nash Family Center for Advanced Circuit Therapeutics. She is a member of the both the National Academy of Sciences and the National Academy of Medicine as well as the National Academy of Inventors and American Academy of Arts and Sciences.
Professor Vinod Goel
York University, Canada
Profile: Vinod Goel is a professor of cognitive neuroscience at York University, Toronto, Canada. He completed his PhD in cognitive science at UC-Berkeley, and received postdoctoral training in neuroscience at the NIH (NINDS) and the Wellcome Department of Cognitive Neurology, Institute of Neurology, UCL, UK. He has made significant empirical contributions to our understanding of the roles of prefrontal cortex in real-world problem solving and reasoning, hemispheric asymmetry in prefrontal cortex, and models of rationality, using the methodologies of fMRI and lesion studies. He has most recently completed a book reconstructing the role of rationality in human behavior entitled “Reason and Less: Pursuing Food, Sex, and Politics” (The MIT Press, 2022). His current project is to explore the implications of this work on our understanding of reason and legal responsibility.
Professor Amy Kuceyeski
Cornell University, USA
Profile: Amy Kuceyeski is an Associate Professor of Mathematics and Neuroscience in Radiology at Weill Cornell Medicine and the Computational Biology Department at Cornell University. She is the director of the Computational Connectomics (CoCo) Laboratory and the Machine Learning in Medicine group at Cornell. Over the past 14 years, she has been working to understand the human brain using quantitative modeling approaches, including machine learning, to map anatomical and physiological characteristics to behavior. Specifically, she is interested in understanding how brains recover from injury so we can devise strategies, possibly via non-invasive neuromodulation, to support natural recovery processes. She also performs research at the intersection of biological and artificial neural networks that aims to understand how human brains process incoming visual information.
Professor Patrick Purdon
Harvard Medical School, USA
Profile: Patrick L. Purdon, Ph.D., is an Associate Professor of Anaesthesia at Harvard Medical School and the Nathaniel M. Sims Endowed Chair in Anesthesia Innovation and Bioengineering at Massachusetts General Hospital. Dr. Purdon received his A.B. in Engineering Sciences from Harvard College in 1996, his M.S. in Electrical Engineering from MIT in 1998, and his Ph.D. in Biomedical Engineering from MIT in 2005. Dr. Purdon’s research in neuroengineering encompasses the mechanisms of anesthesia, Alzheimer’s disease and brain health, anesthesia and the developing brain, neural signal processing, and the development of novel technologies for brain monitoring. He has published over 90 peer-reviewed publications, is an inventor on 16 pending patents, and is a Fellow of the American Institute for Medical and Biological Engineering. Dr. Purdon has won numerous awards, including the prestigious National Institutes of Health Director’s New Innovator Award.
Important Dates
- 15 April 2023: Full paper submission deadline
- 20 April 2023: Workshop proposal deadline
- 10 May 2023: Abstract presentation submission deadline
- 30 May 2023: Final paper and abstract acceptance notification
- 20 Jun 2023: Accepted paper and abstract registration deadline
- 1-3 Aug 2023: The Brain Informatics Conference
Paper Submission and Publications
Full Paper (Regular):
1. 9-12 pages are strongly encouraged for the regular papers including figures and references in Springer LNCS Proceedings format(https://www.springer.com/us/computer-science/lncs/conference-proceedings-guidelines). Over length papers will be charged for 100$ per page.
2. All papers will be peer-reviewed and accepted based on originality, significance of contribution, technical merit, and presentation quality.
3. All papers accepted (and all workshop & special sessions’ full-length papers) will be published by Springer as a volume of the Springer-Nature LNAI Brain Informatics Book Series(https://link.springer.com/conference/brain).
Abstract (Only for Workshops/Special Sessions):
Research abstracts are encouraged and will be accepted for presentations in an oral presentation format and/or poster presentation format. Each abstract submission should include the title of the paper and an abstract body within 500 words. The abstract will not be included in the conference proceedings to be published by Springer.
Journal Opportunities:
High-quality BI conference papers will be nominated for a fast-track review and publication at the Brain Informatics Journal, (https://braininformatics.springeropen.com/) an international, peer-reviewed, interdisciplinary Open Access journal published by Springer Nature. Discount or no open access article-processing fee will be charged for BI conference paper authors.
Special Issues & Books Opportunities:
Workshop/special session organizers and BI conference session chairs may consider and can be invited to prepare a book proposal of special topics for possible book publication in the Springer-Nature Brain Informatics & Health Book Series (https://www.springer.com/series/15148), or a special issue at the Brain Informatics Journal.
Poster-Conference Publication
1. Accepted full papers will be selected to publish in the Brain Informatics Journal upon revision.
2. Discount or no article-processing fee will be charged for authors of Brain Informatics conference (https://braininformatics.springeropen.com/).
3. The organizers of Workshops and Special-Sessions are invited to prepare a book proposal based on the topics of the workshop/special session for possible book publication in the Springer-Nature Brain Informatics and Health book series (http://www.springer.com/series/15148).
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.
What is an appropriate response to humiliating treatments such as insults? This question is not only relevant to today’s discourse but has also piqued the curiosity of thinkers in classical Chinese philosophy. The Warring States period debate regarding whether one’s inner sense of shame can shield one from insulting situations and from experiencing shame is frequently presented as a one-sided narrative that focuses on the Confucian texts. Meanwhile, the views of their rival thinkers, such as the Daoist, legalist, or much-neglected Songzi (3rd century BCE), are rarely the focus of attention. This paper brings Songzi, a key player in the debate of emotions as responses to external triggers, into the picture and restores the historical intellectual discourse over the topic of what constitutes an appropriate response to humiliating situations such as insults. More importantly, I point out the philosophical significance of this debate, namely how Songzi prompts Xunzi to respond to an ambiguity within the Confucian doctrine: The early Confucians appear to think that an individual’s internal virtues can isolate and shield one from hostile external stimuli while also maintaining that the external environment impacts one’s moral cultivation and moral life in significant ways. Xunzi’s strategic move, I argue, is to give credit to both an inner sense of shame and the function of external stimuli in inducing negative emotions, thus making an important philosophical concession compared to Confucius and Mencius.
With responses from Nalei Chen (New York University)
- September 15 – Jing Hu (Concordia)
- October 13 – Bill Waldron (Middlebury)
- October 27 – David Wong (Duke)
- December 1 – Stephen Angle (Wesleyan)