[CogSci] Call for Participation & Abstracts: 2025 Workshop on Human-AI Complementarity for Decision Making (Sept 25–26, 2025)

[Norman Gottron]

Dear Colleagues,

We are pleased to invite you to participate in the 2025 Workshop on
Human-AI Complementarity for Decision Making, sponsored by the NSF AI
Institute for Societal Decision Making (NSF AI-SDM), and hosted by Carnegie
Mellon University. Please see the information below and feel free to pass
it along to any of your colleagues.

Dates: September 25–26, 2025
Location: Carnegie Mellon University, Pittsburgh, PA

Call for Abstracts

We invite abstract submissions from students, faculty, and researchers.
Submissions should highlight ongoing or proposed research related to the
workshop theme and topics. Selected abstracts will be presented as talks or
interactive poster sessions. The primary author of the abstract will be
invited to attend the workshop in person. Their travel and lodging expenses
will be covered by NSF AI-SDM.

Abstract Submission Deadline: July 15, 2025

Submit abstracts using this form
<https://docs.google.com/forms/d/e/1FAIpQLScV8bphvZVnfaW8ltOfqGYG58b8y1eYG5SS_lxyyndmXt6SSA/viewform?usp=dialog>
. Abstracts should be no longer than 300 words and include the title,
authors, and affiliations.

We look forward to your participation in what promises to be a dynamic and
enriching workshop.

Warm Regards,
Norman Gottron, Managing Director, NSF-AI-SDM

on behalf of

Cleotilde Gonzalez (coty at cmu.edu) & Aarti Singh (aarti at andrew.cmu.edu)

NSF AI-SDM

Carnegie Mellon University


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Workshop Motivation and Goals

This annual workshop explores the concept of Human-AI Complementarity—a
condition where humans and AI systems working together outperform either
working alone. Our 2025 theme focuses on flexible Human-AI teams: systems
that align with human values, withstand unexpected behaviors, and remain
robust even under failure.
Key goals of the workshop include:

   - Delivering cutting-edge instruction on achieving Human-AI
   complementarity
   - Creating common knowledge around emerging research challenges
   - Generating new ideas and concrete proposals for future research

*Who Should Participate?*

We welcome contributions from multiple disciplines—decision science,
cognitive science, computer science, machine learning, and beyond.
Participants may be:

   -

   Tutorial Instructors: Delivering state-of-the-art educational sessions
   -

   Students: Presenting interactive posters and engaging in tutorials
   -

   Presenters: Providing brief, targeted insights on key research topics

Topics of Interest

Sessions will focus on the flexibility and dynamics of Human-AI
interactions for
decision making, including but not limited to:

   -

   The role of AI agents in shaping human decision confidence and
   calibration
   -

   AI's influence on trust, coordination, and collaboration
   - Addressing undesirable or failure-prone AI behaviors
   - And others.
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