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.
Search Stories
School of Engineering faculty and staff receive awards in spring 2024
Members of MIT’s School of Engineering were honored in recognition of their scholarship, service, and overall excellence in the spring of 2024.
When to trust an AI model
More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.
Study reveals why AI models that analyze medical images can be biased
These models, which can predict a patient’s race, gender, and age, seem to use those traits as shortcuts when making medical diagnoses.
Growing our donated organ supply
Graduate student Hammaad Adam is working to increase the supply of organs available for transplants, saving lives and improving health equity.
School of Engineering fourth quarter 2023 awards
Faculty and researchers across MIT’s School of Engineering receive many awards in recognition of their scholarship, service, and overall excellence.
Stratospheric safety standards: How aviation could steer regulation of AI in health
An interdisciplinary team of researchers thinks health AI could benefit from some of the aviation industry’s long history of hard-won lessons that have created one of the safest activities today.
Pushing the frontiers of art and technology with generative AI
“I believe by using AI, whether generative or otherwise, we have the opportunity to find the language of humanity,” media artist Refik Anadol told an MIT audience.
MIT scholars awarded seed grants to probe the social implications of generative AI
The 27 finalists — representing every school at MIT — will explore the technology’s impact on democracy, education, sustainability, communications, and much more.
How an archeological approach can help leverage biased data in AI to improve medicine
Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.
How to help high schoolers prepare for the rise of artificial intelligence
A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds.
How machine-learning models can amplify inequities in medical diagnosis and treatment
MIT researchers investigate the causes of health care disparities among underrepresented groups.
Study: AI models fail to reproduce human judgements about rule violations
Models trained using common data-collection techniques judge rule violations more harshly than humans would, researchers report.
Matthew Kearney: Bringing AI and philosophy into dialogue
The computer science and philosophy double-major aims to advance the field of AI ethics.
Subtle biases in AI can influence emergency decisions
But the harm from a discriminatory AI system can be minimized if the advice it delivers is properly framed, an MIT team has shown.