
Tony Zhang
zhang@fortiss.org (preferred) tony.zhang@ifi.lmu.de |
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Phone | +49 89 3603522 196 |
Address | Tony Zhang fortiss GmbH Guerickestraße 25 80805 Munich, Germany |
Other | Google Scholar ResearchGate |
Research
My research at fortiss is about human-AI interaction. In particular, I am interested in how AI, despite its imperfection, can support human decision-making in high-stakes domains like aviation, finance, or healthcare. To this end, I am looking into how AI can augment human decision-making instead of recommending a decision without involving the human. If you want to write your thesis at the intersection between HCI and AI, please reach out to me via e-mail. If I have no open topic at the moment, you should ideally propose a topic yourself, the more concrete, the better. We can then sit together to discuss details. |
Theses
Open
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In Progress
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Completed
Publications
2024 | |
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Tony Zhang, Seniha Ketenci Argin, Mustafa Baha Bilen, Dogan Urgun, Sencer Melih Deniz, Yuanting Liu, Mariam Hassib
Measuring the Effect of Mental Workload and Explanations on Appropriate AI Reliance Using EEG The Version of Record of this manuscript has been published and is available in Behaviour & Information Technology, November 26, 2024, https://www.tandfonline.com/10.1080/0144929X.2024.2431055. (bib) |
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Tony Zhang, Sebastian Feger, Lucas Dullenkopf, Rulu Liao, Lou Süsslin, Yuanting Liu, Andreas Butz
Beyond Recommendations: From Backward to Forward AI Support of Pilots' Decision-Making Process Proceedings of the ACM on Human-Computer Interaction Vol. 8, No. CSCW2. DOI: https://doi.org/10.1145/3687024 (bib) |
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![]() You Can Only Verify When You Know the Answer: Feature-Based Explanations Reduce Overreliance on AI for Easy Decisions, but Not for Hard Ones Mensch und Computer 2024 (MuC '24). DOI: https://doi.org/10.1145/3670653.3670660 (bib) |
2023 | |
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Tony Zhang, Sven Tong, Yuanting Liu, Andreas Butz
Is Overreliance on AI Provoked by Study Design? 19th IFIP TC13 International Conference On Human-Computer Interaction (INTERACT 2023). The final publication is available at Springer via https://doi.org/10.1007/978-3-031-42286-7_3 (bib) |
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Tony Zhang, Yuanting Liu, Andreas Butz
Designing AI for Appropriation Will Calibrate Trust CHI TRAIT '23: Workshop on Trust and Reliance in AI-Assisted Tasks at CHI 2023 (bib) |
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Tony Zhang, Cara Storath, Yuanting Liu, Andreas Butz
Resilience Through Appropriation: Pilots' View on Complex Decision Support 28th International Conference on Intelligent User Interfaces (IUI '23). DOI: https://doi.org/10.1145/3581641.3584056 (bib) |
2022 | |
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Cara Storath, Tony Zhang, Yuanting Liu, Heinrich Hussmann
Building Trust by Supporting Situation Awareness: Exploring Pilots' Design Requirements for Decision Support Tools CHI TRAIT '22: Workshop on Trust and Reliance in Human-AI Teams at CHI 2022 (bib) |
2021 | |
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Tony Zhang, Yuanting Liu, Heinrich Hussmann
Pilot Attitudes Toward AI in the Cockpit: Implications for Design Proceedings of 2nd IEEE International Conference on Human-Machine Systems. DOI: https://www.doi.org/10.1109/ICHMS53169.2021.9582448 (bib) |
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Tony Zhang, Yuanting Liu, Heinrich Hussmann
Forward Reasoning Decision Support: Toward a More Complete View of the Human-AI Interaction Design Space CHItaly 2021: 14th Biannual Conference of the Italian SIGCHI Chapter. DOI: https://doi.org/10.1145/3464385.3464696 (bib) |
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Tony Zhang, Heinrich Hussmann
How to Manage Output Uncertainty: Targeting the Actual End User Problem in Interactions with AI IUI 2021 Workshop on Transparency and Explanations in Smart Systems (TExSS) (bib) |
Community
Committees
- MUM 2024 Posters: Program Committee
- CHI 2024 Workshop on Trust and Reliance in Evolving Human-AI Workflows (TREW): Program Committee
- FAccT 2023: Program Committee
- CHI 2023 Workshop on Trust and Reliance in AI-Assisted Tasks (TRAIT): Program Committee
- CHI 2022 Workshop on Trust and Reliance in AI-Human Teams (TRAIT): Program Committee
- IUI 2022 Workshop on Transparency and Explanations in Smart Systems (TExSS): Program Committee
Peer Reviews
- CHI 2025
- CSCW 2024
- CHI 2024 Late-Breaking Work
- CHI 2023 Late-Breaking Work
- TiiS, Special Issue on Human-centered Explainable AI