Marzyeh Ghassemi

New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.

The inaugural MIT Human Insight Collaborative (MITHIC) Annual Event showcased the breadth of projects supported in the first year of the presidential initiative.

New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.

Large language models can learn to mistakenly link certain sentence patterns with specific topics — and may then repeat these patterns instead of reasoning.

MIT PhD students who interned with the MIT-IBM Watson AI Lab Summer Program are pushing AI tools to be more flexible, efficient, and grounded in truth.