6 citations · 14 across the 6 of their papers we have counts for
6 papers
Human-in-the-loop Fairness: Integrating Stakeholder Feedback to Incorporate Fairness Perspectives in Responsible AI
Evdoxia Taka, Yuri Nakao, Ryosuke Sonoda +3
Fairness is a growing concern for high-risk decision-making using Artificial Intelligence (AI) but ensuring it through purely technical means is challenging: there is no universall…
Stakeholder-in-the-Loop Fair Decisions: A Framework to Design Decision Support Systems in Public and Private Organizations
Yuri Nakao, Takuya Yokota
Due to the opacity of machine learning technology, there is a need for explainability and fairness in the decision support systems used in public or private organizations. Although…
Technical Understanding from IML Hands-on Experience: A Study through a Public Event for Science Museum Visitors
Wataru Kawabe, Yuri Nakao, Akihisa Shitara +1
While AI technology is becoming increasingly prevalent in our daily lives, the comprehension of machine learning (ML) among non-experts remains limited. Interactive machine learnin…
Towards Responsible AI: A Design Space Exploration of Human-Centered Artificial Intelligence User Interfaces to Investigate Fairness
Yuri Nakao, Lorenzo Strappelli, Simone Stumpf +3
With Artificial intelligence (AI) to aid or automate decision-making advancing rapidly, a particular concern is its fairness. In order to create reliable, safe and trustworthy syst…
Towards Involving End-users in Interactive Human-in-the-loop AI Fairness
Yuri Nakao, Simone Stumpf, Subeida Ahmed +2
Ensuring fairness in artificial intelligence (AI) is important to counteract bias and discrimination in far-reaching applications. Recent work has started to investigate how humans…
One-vs.-One Mitigation of Intersectional Bias: A General Method to Extend Fairness-Aware Binary Classification
Kenji Kobayashi, Yuri Nakao
With the widespread adoption of machine learning in the real world, the impact of the discriminatory bias has attracted attention. In recent years, various methods to mitigate the…