Human-Centered AI
Artificial Intelligence (AI) brings amazing capabilities and challenging risks. Human-centered AI (HAI) works to maximize AI’s benefits and minimize its harms by attending to AI capabilities and their impact on users, service providers, impacted stakeholders, and society at large. This area of research:
- Improves AI innovation processes to reduce project failure and bad outcomes
- Creates new methods for people to interact with computing systems
- Advances AI Literacy
- Informs policy and the regulation of AI systems
- Improves how innovators can team with AI to co-innovate
Machine Learning (ML) is a subset of artificial intelligence (AI) that involves training algorithms to learn from and make predictions or decisions based on data. Applied ML in the context of HAI focuses on designing AI systems with human needs, behaviors, and social contexts in mind.
Students who want to learn more about HAI might be interested in the following HCII courses:
Faculty Researchers
NIST Awards $6M to Carnegie Mellon University To Establish AI Cooperative Research Center
NEWSU.S. Secretary of Commerce Gina Raimondo announced Sept. 24 that the Department of Commerce’s National Institute of Standards and Technology (NIST) has awarded $6 million to Carnegie Mello...
People With Autism Turn to ChatGPT for Advice on Workplace Issues
NEWSA new study shows that many people with autism embrace ChatGPT and similar AI tools for help and advice as they confront problems in their workplaces. But does that use of AI make sense?Im...
CMU at CHI 2024
NEWSResearchers from the Human-Computer Interaction Institute (HCII) and several other Carnegie Mellon University schools and disciplines contributed to more than 40 papers accepted to the 202...
CMU Faculty and Staff Present at PASA Lunch and Learn
NEWSOn Tuesday, March 5, Ken Koedinger, Erin Gatz, and Nesra Yannier shared the exciting work they’ve been doing in the field of Artificial Intelligence in education during the Pennsylvania As...
Jigsaw: Supporting Designers to Prototype Multimodal Applications by Assembling AI Foundation Models
PROJECTRecent advancements in AI foundation models have made it possible for them to be utilized off-the-shelf for creative tasks, including ideating design conc...
Wikibench
PROJECTAI tools are increasingly deployed in community contexts. However, datasets used to evaluate AI are typically created by developers and annotators outside...
Forlizzi Briefs Senators on AI in the Workforce
NEWSCarnegie Mellon University School of Computer Science Professor Jodi Forlizzi on Tuesday shared four recommendations with U.S. senators to ensure that innovations in artificial intelligenc...
Eye into AI
PROJECTRecent developments in explainable AI (XAI) aim to improve the transparency of black-box models. However, empirically ...
Predicting and Visualizing Overdose Risk for Public Health
PROJECTOverdose due to opioid misuse and abuse is currently a critical public health issue in the United States and worldwide. Machine learning (ML) approaches h...
Learning Analytics and Data Sharing
PROJECTLearnSphere is a community data infrastructure to support learning improvement online. It integrates educational data and analysis repositories to offer ...
Mixed-Reality For Science Learning
PROJECTNoRILLA is a patented mixed-reality educational system bridging physical and virtual worlds to improve STEM learning. Research at Carnegie Mellon Universi...
Multiplier Effects in Math Education (MEME) Project
PROJECTThe MEME Project’s goal is to produce better educational outcomes by increasing motivation, learning, and self-regulation....