Symposium on Behavioral AI in Education, Work, and Decision-Making
April 8–9, 2026
ESSCA School of Management
Paris, France
About the Symposium
Recent advances in algorithms and Large Language Models (LLMs) are changing how digital tools are used in practice. Rather than serving only as background infrastructure for computation and information storage, these systems are increasingly deployed as interactive components of work and learning. They generate text, propose solutions, summarize evidence, and can support or shape human judgment. This shift raises core questions for the social and behavioral sciences. How should cognitive labor be divided in hybrid human–AI workflows? When does reliance improve decision quality, and when does it degrade it? How should responsibility, accountability, and trust be understood when decisions are mediated by LLMs?
The symposium aims to bring together researchers from the social, behavioral, and computational sciences working on these issues, with a particular focus on implications for education, the workplace, and everyday decision-making.
The symposium will be organized as a single-track event to allow generous time for presentations, discussion, and informal exchange.
Thanks to the financial support of the EUonAIR Alliance, registration is free, and we are arranging preferential accommodation rates with local hotels for symposium participants.
Keynote Speakers
Jean-François Bonnefon
Toulouse School of Economics
Thomas Coustenoble
Microsoft
Erwan Paitel
French Ministry of Education
Phanish Puranam
INSEAD
Symposium Themes
Productivity & Work
Workplace AI adoption, including the division of cognitive labor, task redesign, productivity and quality effects, reskilling, and handover in hybrid workflows.
Decision Quality
AI-assisted decision-making, including cognitive offloading, judgment accuracy and calibration, algorithm aversion and appreciation, and weak or “lazy” oversight.
Responsible AI
AI-mediated decisions, including trust and transparency, machine behavior, and responsibility and blame, as well as work using LLMs as “synthetic subjects”.
Education
AI use in education, including effects on student learning and performance, assessment integrity, and integration of AI as a learning support.
Local Organizers: Pierette El Howeyek, Dejan Glavas, Alexandros Karakostas, Yann Truong
For more information, contact us at: euonair@essca.fr