Studying and designing for human-AI collaborative work in real-world contexts
Across a range of real-world contexts, we are studying how AI is currently being designed and used to augment or transform worker practices. Moving beyond...
Ken Holstein, Anna Kawakami, Frederic Gmeiner, Luke Guerdan, Haiyi Zhu, Nikolas Martelaro, Steven Wu
Applied Machine Learning, Artificial Intelligence (AI), Computational Creativity, Design Research, Fairness, Accountability, Transparency, and Ethics (FATE), Future of Work, Human-Centered AI, Learning Sciences and Technologies, Societal Problems
Advancing Fairness in AI with Human-Algorithm Collaborations
Artificial intelligence (AI) systems are increasingly used to assist humans in making high-stakes decisions, such as online information curation, resume s...
Haiyi Zhu, Ken Holstein, Steven Wu
Artificial Intelligence (AI), Fairness, Accountability, Transparency, and Ethics (FATE), Human-Centered AI, Societal Problems
Understanding Mental Health with Mobile Sensing
Understanding how our family and friends affect our mental health People are social beings in nature and our friends and family play a crucial part in ou...
Jason Hong, Robert Kraut, Siyan Zhao
Healthcare, Societal Problems, Tools
Scaffolding Science Achievement in a Culturally Diverse Classroom
In this project, we aim to address the systematically-reduced standardized test scores of African American students compared to their Euro-American peers ...
Samantha Finkelstein, Justine Cassell,
Education, Learning Sciences and Technologies, Societal Problems