Eye into AI
Recent developments in explainable AI (XAI) aim to improve the transparency of black-box models. How...
Predicting and Visualizing Overdose Risk for Public Health
Overdose due to opioid misuse and abuse is currently a critical public health issue in the United States and worldwide. Machine learning (ML) ...
Adam Perer
Learning Analytics and Data Sharing
LearnSphere is a community data infrastructure to support learning improvement online. It integrates educational data and analysis repositori...
Mixed-Reality For Science Learning
NoRILLA is a patented mixed-reality educational system bridging physical and virtual worlds to improve STEM learning. Research at Carnegie Mel...
Multiplier Effects in Math Education (MEME) Project
The MEME Project’s goal is to produce better educational outcomes by increasing motivation, learning, and self-regulation....
Personalized Learning Squared (PLUS)
The PLUS project is improving the learning outcomes for marginalized students by "squaring" the power of both human and computer tutoring. Our...
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. M...
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 curati...
Artificial Intelligence (AI), Fairness, Accountability, Transparency, and Ethics (FATE), Human-Centered AI, Societal Problems
Incorporating and Balancing Stakeholder Values in Algorithm Design
This project will create a general method for value-sensitive algorithm design and develop tools and techniques to help incorporate the tacit ...
Haiyi Zhu