3 Questions: How to help students recognize potential bias in their AI datasets
Courses on developing AI models for health care need to focus more on identifying and addressing bias, says Leo Anthony Celi.
Interview
Q&A: A roadmap for revolutionizing health care through data-driven innovation
A new book coauthored by MIT’s Dimitris Bertsimas explores how analytics is driving decisions and outcomes in health care.
3 Questions: Visualizing research in the age of AI
Felice Frankel discusses the implications of generative AI when communicating science visually.
3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities
MIT CSAIL Principal Research Scientist Una-May O’Reilly discusses how she develops agents that reveal AI models’ security weaknesses before hackers do.
Q&A: The climate impact of generative AI
As the use of generative AI continues to grow, Lincoln Laboratory's Vijay Gadepally describes what researchers and consumers can do to help mitigate its environmental impact.
3 Questions: Inverting the problem of design
MIT and IBM researchers are creating linkage mechanisms to innovate human-AI kinematic engineering.
Q&A: A new initiative to help strengthen democracy
David Singer, head of the MIT Department of Political Science, discusses the Strengthening Democracy Initiative, focused on the rigorous study of elections, public opinion, and political participation.
3 Questions: Should we label AI systems like we do prescription drugs?
Researchers argue that in health care settings, “responsible use” labels could ensure AI systems are deployed appropriately.
3 Questions: How to prove humanity online
AI agents could soon become indistinguishable from humans online. Could “personhood credentials” protect people against digital imposters?
3 Questions: Enhancing last-mile logistics with machine learning
MIT Center for Transportation and Logistics Director Matthias Winkenbach uses AI to make vehicle routing more efficient and adaptable for unexpected events.