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HCOMP 2026 : The 2026 ACM Conference on Human-AI Complementarity and Alignment | |||||||||||||||
| Link: https://www.humancomputation.com/2026/submit.html | |||||||||||||||
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Call For Papers | |||||||||||||||
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WELCOME TO HCOMP 2026!
The 2026 ACM Conference on Human-AI Complementarity and Alignment (HCOMP) and the 2026 ACM Collective Intelligence (CI) Conference will be held as co-located events from September 27-30, 2026, at the Virginia Tech Institute for Advanced Computing near Washington, DC, USA. 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, the following: 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 Check back for submission instructions for papers, workshops, work-in-progress/demos, and the annual doctoral consortium. |
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