The current pandemic has focused attention on the techniques used by epidemiologists and other non-experimental scientists to infer causal hypotheses from correlational data. I have previously argued* that we need to explain these techniques by reducing causal relationships to dependencies in systems of structural equations with probabilistically independent exogenous variables. In this talk I shall aim to use this account to cast light on (a) single-case counterfactual dependence and actual causation, (b) the content and practical relevance of generic causal claims like “smoking causes cancer”, (c) the temporal asymmetry of causation, and (d) the proper understanding of rational action under risk.
*In particular, I’ve argued this in http://weebly-file/1/8/5/5/18551740/stat_nat_csn_monist.pdf. I will also be giving a talk on it at the CUNY Logic and Metaphysics workshop on Monday 7 March 1615-1815.
The talk will be on Zoom. All are welcome to attend!
The zoom link will be distributed through the MAPS mailing list. If you are not on the MAPS mailing list and would like to receive the Zoom link for the talk, please email nyphilsci@gmail.com.
Naked Statistical Evidence and Verdictive Justice
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.
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.