Topics of Interest

Conference Information & Theme

The 14th ACM Collective Intelligence Conference (CI 2026) will be held September 27-30, 2026 at Virginia Tech's Academic Building One near Washington, D.C., USA.

This year, the conference will be co-located and tightly integrated with the 2026 ACM Conference on Human-AI Complementarity and Alignment (HCOMP), creating a unique synergy between researchers in collective intelligence and human-AI collaboration.

The theme of this year's co-located event is Connections. We encourage submissions that explore connections across disciplines; across humans, animals, and machines; between individuals and communities, and beyond.

General Chairs

Collective Intelligence (CI)

ACM Collective Intelligence is the premier venue for disseminating the latest research that advances the theoretical and empirical understanding of collective performance in diverse systems, whether biological, technological, or a combination. We are interested in research on a broad range of systems that vary in scale and scope and focus on implications for a diverse range of social, ecological, and economic outcomes.

CI has a transdisciplinary focus devoted to advancing the theoretical and empirical understanding of collective intelligence, broadly designed. The community does basic science on emergent collective phenomena, as well as designing and engineering systems for combining computational and human intelligence. We are interested in research on a broad range of phenomena that vary in scale and scope with implications for a diverse range of social, ecological, and economic outcomes.

Researchers who participate in the CI conference represent a wide and growing cross-section of social science and computer science as well the natural sciences, arts, and humanities. All types of contributions—empirical, conceptual, theoretical, quantitative, and qualitative—are welcome, including computational models.

Topics include (but are not limited to) research that helps us to explain the mechanisms of emergent behavior as well as presentations of design solutions and systems engineering.

Research on collective behaviors including, but not limited to:

• Crowds, flocks and swarms
• Collective emotion and polarization
• Belief formation and misinformation
• Social network formation and functioning
• Science and innovation
• Open source communities
• Organizational Studies

Research into systems and tasks to support the following, but not limited to:

• Forecasting and decision-making
• Democracy, civics and policymaking
• Complex problem solving
• Crisis response
• Community-driven design
• Innovation contests
• Citizen science
• Discussion moderation and decision facilitation
• Computer-human collaboration (e.g. hybrid systems, LLMs)

CI 2026 Program Co-Chairs

Human-AI Complementarity and Alignment (HCOMP)

ACM HCOMP is the premier venue for disseminating the latest research findings on human-AI complementarity and alignment. Our community studies and designs systems that combine the complementary strengths of human and artificial intelligence to achieve outcomes neither could achieve alone, in ways that are ethical, safe, and intentional. This research builds on a foundation established by the HCOMP community during its first decade as an AAAI conference series focused on human computation and crowdsourcing.

HCOMP focuses on the emerging science and practice of human-AI complementarity and alignment. As AI systems become increasingly capable, the field is expanding from studying how humans contribute to building these systems to also studying how humans and AI systems work together as complementary partners. This broader perspective situates complementarity and alignment across the full lifecycle of AI systems, from how systems are built and evaluated to how they are used and governed in practice, with attention to how responsibilities are divided, how collaboration evolves over time, and how alignment is achieved and maintained in real-world use.

While artificial intelligence (AI) and human-computer interaction (HCI) represent traditional mainstays of the conference, HCOMP believes strongly in fostering and promoting broad, interdisciplinary research. Our field is particularly unique in the diversity of disciplines it draws upon and contributes to, including human-centered qualitative studies, HCI design, social computing, machine learning, natural language processing, the broader realms of artificial intelligence (including LLMs and generative AI), economics, computational social science, digital humanities, policy, and ethics. We promote the exchange of advances in human-AI complementarity and alignment not only among researchers but also engineers and practitioners, to encourage dialogue across disciplines and communities of practice.

Example topics for HCOMP include, but are not limited to:

Research on human-AI complementarity

• Human-AI collaboration, coordination, and co-adaptation
• Division of labor, delegation, and supervisory control
• Complementarity versus redundancy in human-AI systems
• Hybrid workflows that combine human and AI strengths
• Human-AI decision-making and problem solving
• Human-AI interaction in organizational and societal settings

Research on human-centered alignment

• Alignment in training and in use
• Trust, reliance, and calibration
• Scalable human oversight
• Steering, monitoring, and control of AI systems
• Detecting, communicating, and repairing misalignment
• Governance, accountability, and safety in human-AI systems

Research on human contributions to AI systems

• Crowdsourcing and human computation
• Human feedback, preference learning, and evaluation
• Data collection, annotation, and quality assurance
• Bias, fairness, and responsible data practices
• Human roles in the development, assessment, and governance of AI systems

HCOMP 2026 Program Co-Chairs