Thought Summits
AWARDED THOUGHT SUMMITS:
The Future of Survey Science: Sept. 22 – 25, 2024
Government, industry, and academia depend on surveys more than ever before. However, shifting social behaviors, technology, and public trust mean that the accuracy and reliability of surveys are in flux. This Thought Summit brings together experts in survey research with connections to large NSF-funded surveys, data science, and AI. Our goal is to identify strategies and infrastructure to support the most accurate and cost-effective surveys. To do this, the Thought Summit will focus on two overlapping areas.
1.) Identifying ways government-funded surveys can collaborate to gain efficiencies and meet survey research goals.
2.) Identifying ways AI and data science can enhance these collaborations and inform strategies to solve contemporary challenges faced by survey research.
To foster young talent and ensure participation of emerging scholars we have allocated a small number of seats for Masters and PhD students. Up to five students will be able to attend the Thought Summit fully-funded. More information about the call and how to apply can be found here. The deadline to apply is June 7, 2024.
Organizers:
Colleen Barry
Inaugural Dean, Brooks School of Public Policy
Peter Enns
Professor, Department of Government & Brooks School of Public Policy; Robert S. Harrison Director, Cornell Center for Social Sciences; Co-founder, Verasight.io
Thorsten Joachims
Professor, Department of Computer Science & Department of Information Science; Associate Dean for Research, Bowers College of Information Science
Jonathon P. Schuldt
Professor, Department of Communication; Executive Director of the Roper Center for Public Opinion Research
Large Language Models and Society : May 19 – 21, 2025
Generative AI technologies like Large language models (LLMs) are rapidly becoming a part of people’s daily lives worldwide with its effects being felt nearly everywhere, including in high-stakes contexts like healthcare, law, education, negotiation, and civic participation. While AI has brought transformative advances in these areas, research has shown that it can also have negative consequences. For example, to date these technologies have primarily benefited people in the West, which make up only a small fraction of the global population. Similarly, the risks of AI are considered primarily in such Western contexts even though these technologies are used all around the globe.
Our week-long thought summit will explore, analyze, and chart the future of LLMs and their integration into high-stakes settings in an increasingly complex and interconnected world. The summit will bring together experts, researchers, and thought leaders from diverse fields, who will delve into the implications and applications of LLMs for discovery, decision support, and creativity in diverse domains and geographies. The summit will foster a deeper understanding of the ethical, technical, and regulatory challenges that accompany the use of LLMs in such environments, discuss potential and pitfalls of these models, and find ways to harness the transformative power of these models.
PI: Aditya Vashistha, Information Science
Co-PIs and Collaborators
Rene Kizilcec, Information Science
Cristobal Cheyre Forestier, Information Science
Matthew Wilkens, Information Science
Malte Jung, Information Science
Allison Koenecke, Information Science
Thorsten Joachims, Computer Science
Laurent Dubreuil, Romance Studies
Morten H. Christiansen, Psychology and Cognitive Science
Marten van Schijndel, Linguistics
Natalie Bazarova, Communication
Lee Humphreys, Communication
Maria Goula, Landscape Architecture
Duarte Santo, Landscape Architecture
Everyday Sensing and AI for Mental Health Care: Navigating a Tipping Point: June 2025 (tbd)
From therapy chatbots that detect and reframe our thoughts, to Apple Watch that tracks our social activity rhythms, the combination of consumer-level sensing and Artificial Intelligence (AI) holds great promise in easing the US mental health crisis.
Yet, the blurred line between consumer-level sensing and clinical care also poses renewed challenges in AI model performance, AI fairness, patient privacy, patient autonomy, and more.
This Thought Summit will bring together clinical machine learning, mental health, human-centered AI, law and policy, and business and economics experts, together deliberating how these disciplines can join forces in realizing the promises of everyday sensing/AI in mental health while accounting for its risks. Workshop participants will together (1) envision how patients and their data might best transition between everyday wellness to clinical mental healthcare, (2) outline novel machine learning (ML) tasks and benchmarks that allow innovative AI systems to facilitate this transition, (3) identify regulatory needs for these systems, finally, (4) propose business models for such AI systems to both benefit society and remain economically viable in the real world.
Qian Yang Contact PI
Assistant professor
Information Science, College of Computing and Information Science (Ithaca) qianyang@cornell.edu
Fei Wang Co-PI
Associate professor
Population Health Sciences, Weill Cornell Medical College
Tanzeem Choudhury Co-PI
Professor
Information Science, Cornell Tech
Angel Hwang Senior Personnel
Postdoc
Information Science, College of Computing and Information Science (Ithaca)
