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HAICAI@FLAIRS 2026 : FLAIRS-39 Special Track: Human AI Collaboration and Augmented Intelligence

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Link: https://sites.google.com/view/haicai/home
 
When May 17, 2026 - May 20, 2026
Where Boca Raton, Florida
Abstract Registration Due Jan 19, 2026
Submission Deadline Jan 26, 2026
Notification Due Mar 16, 2026
Final Version Due Apr 6, 2026
Categories    NLP   AI   ML   HCI
 

Call For Papers

The evolution of artificial intelligence (AI) technologies is reshaping how humans interact with machines, paving the way for innovative collaboration and augmented intelligence. At the core of the current revolution is natural language processing (NLP), which offers intuitive interfaces to enhance human capabilities and facilitate more effective human-AI collaboration and augmented intelligence (HAICAI) - the strategic partnership and cooperative interaction between human intelligence and agentic AI aimed at achieving superior outcomes. Similarly, we consider augmented intelligence to be the cooperative interaction between human intelligence and non-agentic AI such as providing timely information or processing support.

This special track on human-AI Collaboration and Augmented Intelligence invites research toward amplifying human potential through agentic action or timely information provided to the user. Papers that either explore novel instantiations of AI collaboration or augmented intelligence are appropriate. Further, papers that explore fundamental questions regarding HAICAI are encouraged. Highest priority will be given to papers that explore the intersection of natural language and HAICAI.

Topics of interest may include (but are not limited to):
Collaborative Tools & Systems: Development of NLP-driven tools that foster seamless human-AI collaboration and productivity enhancement
Evaluation of Models: Evaluation of models and their relevant capabilities for human-collaboration
Understanding Uncertainty: Investigating the impact of, and strategies for, managing uncertainty in collaborative interactions human-AI Communication: Foundational research on AI systems understanding and supporting human directions and preferences
Domain Applications: Integration of NLP within healthcare, education, and business contexts to extend human knowledge
Agentic Systems: Applications showcasing collaborative AI agents improving desired outcomes
Evaluation Studies: Human-centered research evaluating the effectiveness of AI-assisted workflows, productivity tools, and decision-support systems
Ethical Considerations: Examining challenges in creating transparent, trustworthy AI systems that empower rather than replace human capabilities
Fundamental Questions: Investigation of the fundamental problems associated with human-AI collaboration and efforts to augment human intelligence through AI.

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