no code implementations • 5 Apr 2022 • Anna Kawakami, Venkatesh Sivaraman, Hao-Fei Cheng, Logan Stapleton, Yanghuidi Cheng, Diana Qing, Adam Perer, Zhiwei Steven Wu, Haiyi Zhu, Kenneth Holstein
AI-based decision support tools (ADS) are increasingly used to augment human decision-making in high-stakes, social contexts.
no code implementations • 30 Jun 2022 • Amanda Coston, Anna Kawakami, Haiyi Zhu, Ken Holstein, Hoda Heidari
Recent research increasingly brings to question the appropriateness of using predictive tools in complex, real-world tasks.
no code implementations • 13 Mar 2023 • Shreya Chowdhary, Anna Kawakami, Mary L. Gray, Jina Suh, Alexandra Olteanu, Koustuv Saha
Our mapping of what prevents workers from meaningfully consenting to workplace wellbeing technologies (challenges) and what they require to do so (interventions) illustrates how the lack of meaningful consent is a structural problem requiring socio-technical solutions.
no code implementations • 26 Mar 2023 • Anna Kawakami, Amanda Coston, Haiyi Zhu, Hoda Heidari, Kenneth Holstein
AI-based decision-making tools are rapidly spreading across a range of real-world, complex domains like healthcare, criminal justice, and child welfare.
no code implementations • 30 Aug 2023 • Anna Kawakami, Luke Guerdan, Yanghuidi Cheng, Matthew Lee, Scott Carter, Nikos Arechiga, Kate Glazko, Haiyi Zhu, Kenneth Holstein
A growing body of research has explored how to support humans in making better use of AI-based decision support, including via training and onboarding.