SYNERGY

Designing and Building Hybrid Human–AI Systems

Outline

This page describes the HHAI 2025 Workshop on Hybrid Human-AI Systems. If you're looking for last year's workshop, please visit the 2024 edition.

In 1960 the visionary Joseph Licklider wrote "Man-Computer Symbiosis", looking forward to a day when computation could “augment the human intellect” in a similar way that mechanical tools augmented humans' physical abilities. Today, this vision is becoming reality as AI systems work alongside people in complex tasks ranging from visual analytics to code generation. While we have experience with expert systems and AI performing specific subtasks, we are still learning how to design truly synergistic systems where humans and AI work flexibly together, leveraging their complementary abilities. Some human-in-the-loop systems, effectively mean the human is a cog in the machine, however true synergy means adapting AI algorithms to work more meaningfully with human intervention and adapting user interactions to make human intentions more available to the AI.

In this workshop we aim to bring together researchers working or intending to work in this new and rich area. Some will bring experience in designing intelligent systems; others may have worked on synergistic systems using non-AI technology; some may bring understandings of human-human collaboration; and others still simply interested and excited by the potential opportunities on radically new interactions.

The workshop will include consortium partners from the new 10 million Euro project TANGO "It takes two to tango: a synergistic approach to human-machine decision making".

Topics and Themes

This workshop focuses on the design, implementation, and evaluation of systems enabling meaningful human-AI collaboration. We invite submissions in the following key areas:

Interactive Decision-Making Systems
Mechanisms and interfaces for real-time human-AI collaboration
  • Explicit protocols for dynamic task allocation and handoff
  • Methods for mutual understanding of capabilities and limitations
  • Techniques for combining human intuition with AI analysis
  • Approaches for handling disagreement and uncertainty
Adaptive Collaboration Frameworks
Systems that dynamically adjust based on ongoing interaction
  • Real-time assessment of human cognitive load
  • Learning mechanisms from human intervention
  • Dynamic adaptation of AI behavior
  • Context-aware collaboration strategies
Evaluation Methods
Novel approaches to measuring human-AI collaboration effectiveness
  • Metrics for assessing genuine partnership
  • Methods for evaluating joint decision quality
  • Techniques for measuring cognitive load and satisfaction
  • Frameworks for comparing different collaboration models
Implementation Architectures
Practical solutions for building collaborative systems
  • Software patterns for responsive interaction
  • Methods for maintaining human agency
  • Integration approaches for existing AI capabilities
  • Real-world case studies and lessons learned

We particularly welcome submissions that:

  1. Present concrete mechanisms for human-AI collaboration
  2. Provide empirical evaluation of collaborative systems
  3. Demonstrate novel interaction patterns
  4. Address practical implementation challenges

All submissions should demonstrate:

Contributing Your Work

Submissions should be minimum 5 pages long, following the CEUR-WS instructions for single column papers. Longer submissions may be considered, provided they remain within reasonable limits. Please note that submissions do not need to be anonymized.

The deadline for submissions is April 11, 2025 AoE. Submission website: Microsoft CMT.

Additionally, selected papers will be invited for submission in expanded form to a Special Issue in a leading journal. The topic of the special issue will be Hybrid Human-AI Systems. Further instructions regarding formatting and the review/publication process will be provided when the invitations are sent.

Please send any comments or questions to Tommaso Turchi, tommaso.turchi@unipi.it.

Organisers

Tommaso Turchi is an Assistant Professor at the University of Pisa (Italy). His research focuses on Human-Centered AI and End-User Development. He has worked on various research projects related to the interaction with AI systems and is currently investigating the use of Design Fiction for AI-as-a-service applications in the medical field. His most recent work includes the development of a co-design toolkit to identify and address bias in ML-based collaborative decision-making domains.

Alan Dix is Emeritus Professor of the Computational Foundry at Swansea University and Professorial Fellow at Cardiff Metropolitan University (United Kingdom). He is known for his HCI research, including a core textbook and pioneering work in mobile interfaces and machine learning bias. He is a member of the ACM SIGCHI Academy and his work includes both theoretical foundations and practical applications in diverse fields. Alan is known for his eclectic methods which combine technical, philosophical, and artistic insights, emphasizing the importance of technical creativity.

Matt Roach is a Senior Lecturer in Computer Science at Swansea University (United Kingdom), specializing in machine learning for smart city traffic management and fraud detection. His research interests include Machine Learning, Algorithmic Bias, and Human-Computer Interaction. He plays a key role in several large-scale collaborative projects and doctoral training initiatives. Prior to academia, Matt significantly contributed to computing skills development in industry and business sectors.

Alessio Malizia is an Associate Professor at the University of Pisa (Italy). His research focuses on Human-Centered AI and Design Fictions. He's involved in different National and International projects developing novel approaches for improving scientific methods to study Human-Artificial Intelligence Interaction.

Ben Wilson is a PhD candidate at Swansea University having done previous work in the UK National Health Service on health systems development, informatics, clinical outcomes capture and analysis. His current work is on human-machine synergy in relation to decision-making. He is a Research Officer on the Tango-Horizon project.

Program Committee

Acknowledgements

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency (HaDEA). Neither the European Union nor the granting authority can be held responsible for them.

This workshop is supported by the HORIZON Europe project TANGO - Grant Agreement n. 101120763.

The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

TANGO
Funded by the European Union