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SUMMARY:Human-Centered AI: Addressing the Ecological Fallacy in LLMs - Pro
 f\, H Andrew Schwartz (State University of New York at Stony Brook)
DTSTART:20250508T140000Z
DTEND:20250508T150000Z
UID:TALK231031@talks.cam.ac.uk
CONTACT:Shun Shao
DESCRIPTION:Abstract:  Today’s foundation models - whether they process 
 sequences of words (NLP)\, matrices of pixels (vision)\, or timelines of a
 udio spectra (speech) - treat each observation in isolation\, a so-called 
 ecological fallacy in disregarding the individuals and communities that ge
 nerate data. In this talk\, I argue for reconceptualizing the core probabi
 listic tasks of foundation models to integrate the people behind the data\
 , for instance\, by having LLMs estimate the probability of the next word 
 not only from its preceding tokens but also from a higher-order representa
 tion of the data’s author. This “human language modeling” (HuLM) fra
 mework explicitly conditions on dynamic user states\, drawing on theories 
 of traits and states from psychology\, to capture the structured dependenc
 ies among data and avoid the ecological fallacy. In a trade-off for modeli
 ng complexity\, we will show these models can lead to improved performance
  on both traditional NLP tasks and health and psychological applications\,
  more fundamentally aligning models of data with the realities of the huma
 n behavior that produced it.\n\n\nBio: H. Andrew Schwartz is the director 
 of the Human Language Analysis Lab (HLAB) housed in the Computer Science D
 epartment at Stony Brook University (SUNY) and a PI/co-founder of the Worl
 d Well-Being Project—a multidisciplinary consortium between the Universi
 ty of Pennsylvania\, Stony Brook University\, and Stanford University focu
 sed on developing large-scale language analyses that reveal differences in
  health\, personality\, and well-being. Andrew is an active contributor in
  the fields of AI-natural language processing\, psychology\, and health in
 formatics\, as well as a participant in tech for the public good\, such as
  the UN Global Working Group on Big Data for Official Statistics. He was t
 he 2020 recipient of a DARPA Young Faculty Award. Andrew is also the co-cr
 eator of the new R-Text package\, which brings the language model technolo
 gy behind ChatGPT to R\, and the maintainer of the well-established Python
  package\, Differential Language Analysis ToolKit (DLATK)\, used in over 1
 00 studies and within tech. His research frequently attracts public intere
 st\, with coverage in publications such as The New York Times\, USA Today\
 , and The Washington Post.
LOCATION:https://cam-ac-uk.zoom.us/j/97599459216?pwd=QTRsOWZCOXRTREVnbTJBd
 XVpOXFvdz09
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