Lin Luo
Research title: Interactive machine learning fairness and explanations
Publications
2026
Di Campli San Vito, P. et al. (2026) Empowering Stakeholders with Participatory Auditing of Predictive AI: Perspectives from End-Users and Decision Subjects without AI Expertise. In: CHI' 2026, Barcelona, Spain, 13–17 April 2026, ISBN 9798400722783 (doi: 10.1145/3772318.3791757)
Luo, Lin ORCID: https://orcid.org/0000-0002-0310-3158, Nakao, Yuri, Chollet, Mathieu
ORCID: https://orcid.org/0000-0001-9858-6844, Inakoshi, Hiroya and Stumpf, Simone
ORCID: https://orcid.org/0000-0001-6482-1973
(2026)
"I think this is fair": Uncovering the Complexities of Stakeholder Decision-Making in AI Fairness Assessment.
In: ACM CHI Conference on Human Factors in Computing Systems (CHI 2026), Barcelona, Spain, 13–17 April 2026,
ISBN 9798400722783
(doi: 10.1145/3772318.3790770)
2025
Luo, Lin ORCID: https://orcid.org/0000-0002-0310-3158, Nakao, Yuri, Chollet, Mathieu
ORCID: https://orcid.org/0000-0001-9858-6844, Inakoshi, Hiroya and Stumpf, Simone
ORCID: https://orcid.org/0000-0001-6482-1973
(2025)
EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders.
In: 28th ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW), Bergen, Norway, 18-22 Oct 2025,
(doi: 10.1145/3710908)
2024
Stumpf, Simone ORCID: https://orcid.org/0000-0001-6482-1973, Taka, Evdoxia
ORCID: https://orcid.org/0000-0001-7011-3367, Nakao, Yuri, Luo, Lin
ORCID: https://orcid.org/0000-0002-0310-3158, Sonoda, Ryosuke and Yokota, Takuya
(2024)
The Need for User-centred Assessment of AI Fairness and Correctness.
In: UMAP '24: 32nd ACM Conference on User Modeling, Adaptation and Personalization, Cagliari, Italy, 01-04 Jul 2024,
pp. 523-527.
ISBN 9798400704666
(doi: 10.1145/3631700.3664912)
Conference Proceedings
Di Campli San Vito, P. et al. (2026) Empowering Stakeholders with Participatory Auditing of Predictive AI: Perspectives from End-Users and Decision Subjects without AI Expertise. In: CHI' 2026, Barcelona, Spain, 13–17 April 2026, ISBN 9798400722783 (doi: 10.1145/3772318.3791757)
Luo, Lin ORCID: https://orcid.org/0000-0002-0310-3158, Nakao, Yuri, Chollet, Mathieu
ORCID: https://orcid.org/0000-0001-9858-6844, Inakoshi, Hiroya and Stumpf, Simone
ORCID: https://orcid.org/0000-0001-6482-1973
(2026)
"I think this is fair": Uncovering the Complexities of Stakeholder Decision-Making in AI Fairness Assessment.
In: ACM CHI Conference on Human Factors in Computing Systems (CHI 2026), Barcelona, Spain, 13–17 April 2026,
ISBN 9798400722783
(doi: 10.1145/3772318.3790770)
Luo, Lin ORCID: https://orcid.org/0000-0002-0310-3158, Nakao, Yuri, Chollet, Mathieu
ORCID: https://orcid.org/0000-0001-9858-6844, Inakoshi, Hiroya and Stumpf, Simone
ORCID: https://orcid.org/0000-0001-6482-1973
(2025)
EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders.
In: 28th ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW), Bergen, Norway, 18-22 Oct 2025,
(doi: 10.1145/3710908)
Stumpf, Simone ORCID: https://orcid.org/0000-0001-6482-1973, Taka, Evdoxia
ORCID: https://orcid.org/0000-0001-7011-3367, Nakao, Yuri, Luo, Lin
ORCID: https://orcid.org/0000-0002-0310-3158, Sonoda, Ryosuke and Yokota, Takuya
(2024)
The Need for User-centred Assessment of AI Fairness and Correctness.
In: UMAP '24: 32nd ACM Conference on User Modeling, Adaptation and Personalization, Cagliari, Italy, 01-04 Jul 2024,
pp. 523-527.
ISBN 9798400704666
(doi: 10.1145/3631700.3664912)