AI and the New Future of Work CFP | Spring 2026

Collaboration between people is a central mechanism in how work gets done, but AI doesn’t yet work as well for teams as it does for individuals. Understanding how humans and AI can work better together in group settings is a critical area of the AI frontier. In this year’s New Future of Work Call for Proposals, we’re looking to support research that advances this frontier. Some of the research challenges we expect scientists to propose include (but are not limited to):

• Systems that help a team with AI dramatically outperform an individual with AI: AI systems that enable teams of people to robustly and substantially outperform appropriate comparison conditions (e.g., individuals with AI and teams without AI) on important tasks.
• Collaboration “arenas” and world models: Developing simulation models that can help people train and test AI systems in collaborative settings.
• Envisioning a positive future of collaboration: Empirical and theoretical models of AI-empowered collaboration that have the potential to lead to positive outcomes for all stakeholders (individual participants, teams, organizations, society more broadly).
• Eliminating collaboration “drudgery”: AI systems that reduce effort spent on aspects of teamwork that are empirically shown to be low value or aversive to participants (e.g., through prior literature, formative studies, or explicit measurement of perceived burden).
• Addressing the attention crisis in collaboration: AI systems that address communication overload at work by radically reducing low-value uses of attention in collaborative settings, allowing people to focus where their cognition and effort is most valuable.
• AI proactivity in collaborative settings: When and how should an AI proactively participate in a group conversation? How do we measure the cost of precision and recall errors in this context?
• Increasing fluidity in collaboration: How can people in an organization on-board (and step away from) a project more efficiently and effectively so that expertise can be brought to bear in new ways?
• Ensuring the work of a team benefits the team: Non-exploitative AI systems and corresponding incentive structures in which the value of any data created benefits the individuals and teams that created it.
• Leveraging behavioral science: AI systems and models that learn from well-defined negotiation scenarios, problem solving scenarios, conflict management scenarios and similar.
• New norms and etiquette of AI-empowered teams: Identifying successful norms and social frameworks for teams that have AI deeply embedded in their work.
• Strengthening core teamwork mechanisms: AI capabilities that can support and improve core teamwork mechanisms like grounding and common ground maintenance.
• Collaborative AI systems and approaches that focus on how AI can do different things than humans, not just replicate what humans do: AI’s scalability, instantaneous ideation, externalized cognition and affordance of low-cost experimentation capabilities are all examples of underutilized but promising applications of AI rooted in its differences to humans, not its similarities.

Key Dates

• April 28, 2026:
  Proposal period opened
• May 25, 2026:
  Proposal period closed
• Week of June 8th:
  Recipients announced