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Event

CHI 2025: Human-AI Interaction for Augmented Reasoning

Valdemar Danry

Saturday
April 26, 2025
9:00am — 5:00pm ET

Human-AI Interaction for Augmented Reasoning

Improving Human Reflective and Critical Thinking with Artificial Intelligence

April 26, 2025 | 9:00-17:00 JST | CHI 2025, Yokohama, Japan

AI-Augmented Reasoning systems are cognitive assistants that support human reasoning by providing AI-based feedback that can help users improve their critical reasoning skills. Made possible with new techniques like argumentation mining, fact-checking, crowdsourcing, attention nudging, and large language models, AI augmented reasoning systems can provide real-time feedback on logical reasoning, help users identify and avoid flawed arguments and misinformation, suggest counter-arguments, provide evidence-based explanations, and foster deeper reflection.

The goal of this workshop is to bring together researchers from AI, HCI, cognitive and social science to discuss recent advances in AI-augmented reasoning, to identify open problems in this area, and to cultivate an emerging community on this important topic.

Copyright

MIT Media Lab

What is AI Augmented Reasoning?

AI Augmented Reasoning refers to the application of artificial intelligence (AI) systems to support, facilitate and improve human reasoning capabilities by providing insights, identifying patterns, uncovering biases, and offering guidance that is intuitive to the user and which enables them to make better-informed decisions that they feel that they arrived at through their own thinking processes.

AI-enhanced reasoning systems differ from other AI information-processing systems in that they focus not only on providing accurate information or optimize decision outcomes but also on actively engaging users in reflective thinking or building strong, appropriate intuitions.

Copyright

MIT Media Lab

Workshop Goals

The workshop’s primary goals are:

  • Share State-of-the-Art Research: Present and discuss recent advances in AI-augmented reasoning and human-AI interaction. This includes new techniques, tools, and methodologies developed to enhance critical and reflective thinking.
  • Identify Challenges and Opportunities:
    Highlight the current challenges, limitations, and potential risks associated with AI-augmented reasoning systems. Discuss opportunities for future research and development.
  • Interdisciplinary Collaboration:
    Foster collaboration between researchers from AI, HCI, cognitive science, social science, and other relevant fields to create a multidisciplinary approach to developing AI-augmented reasoning systems.
  • Ethical and Social Implications:
    Delve into the ethical and social issues surrounding AI-augmented reasoning like accidental overreliance, and potential misuses of modeling user reasoning.
  • Design Principles and Guidelines:
    Develop design principles and guidelines for creating AI-augmented reasoning systems that prioritize human agency, autonomy, and long-term learning. Consider the balance between AI assistance and human decision-making.
  • Evaluation Methods:
    Discuss and propose effective methods for evaluating the effectiveness of AI-augmented reasoning systems. This includes metrics for assessing improvement in critical thinking skills and the impact on decision-making quality.

Topics

Topics of interest include but are not limited to:

  • AI-based reasoning interventions and critical thinking support
  • Studies on misinformation related to AI and mitigation
  • Political/Democratic reasoning
  • Argument mining and argument synthesis
  • Fact-checking, attention nudging and information validation
  • Human-computer interaction (HCI) methods that boost reasoning
  • User modeling and information delivery
  • Human-AI Interaction methods for critical thinking
  • Wearable systems for cognitive support
  • Cognitive theories of reflection and intuitive decision making

Keynote Speakers

Dr. Thomas Costello

Thomas Costello is an Assistant Professor of Psychology at American University and Research Associate at the MIT Sloan School of Management. He studies where political and social beliefs come from, how they differ from person to person–and, ultimately, why they change–using the tools of personality, cognitive, clinical, and political science. He is best known for his work on (a) leveraging artificial intelligence to reduce conspiracy theory beliefs and (b) the psychology of authoritarianism. He has published dozens of research papers in peer-reviewed outlets, including Science, Journal of Personality and Social Psychology, Psychological Bulletin, and Trends in Cognitive Sciences. Thomas developed DebunkBot.com, a public tool for combatting conspiracy theories with AI.

Dr. Paolo Torroni

Dr. Paolo Torroni has been an associate professor at the University of Bologna since 2015. His primary research focuses on artificial intelligence, particularly in natural language processing, multi-agent systems, and computational logics. He authored over 180 scientific publications. He is the head of the Language Technologies Lab and past director of the Master’s Degree in Artificial Intelligence in Bologna and a visiting fellow at the European University Institute in Florence.

Call for Participation

If you are interested in the workshop, please submit your application below for virtual or in-person participation. The submission deadline is March 2nd, 2025. We will notify the accepted participants by March 24th 2025. The list of participants will be posted on the workshop website.

At least one author of each accepted position paper must attend the workshop and all participants must register for at least one day of the conference. We will host accepted papers on the workshop’s website for participants and others to review prior to the meeting.

Registration Deadline: March 2, 2025

Key Dates

Position paper submission deadline: February 7th, 2025 Sunday, March 2nd 2025 AoE

Notification of acceptance: Monday, March 24th 2025

Workshop date: Saturday, April 26th 2025

Workshop Organizers

Valdemar Danry
MIT Media Lab, United States

Pat Pataranutaporn
MIT Media Lab, United States

Christopher Cui
University of California, San Diego, United States

Jui-Tse (Ray) Hung
Georgia Institute of Technology, United States

Lancelot Blanchard
MIT Media Lab, United States

Zana Buçinca
Harvard University, United States

Chenhao Tan
University of Chicago, United States

Thad Starner
Georgia Institute of Technology, United States

Pattie Maes
MIT Media Lab, United States

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