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Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Defense Advanced Research Projects Agency (DARPA) Electrical engineering and computer science (EECS) Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering

Researchers reduce bias in AI models while preserving or improving accuracy

A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.

Artificial Intelligence Computer science and technology Data machine learning Media Lab Research School of Architecture and Planning Technology and society

Study: Some language reward models exhibit political bias

Research from the MIT Center for Constructive Communication finds this effect occurs even when reward models are trained on factual data.

Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering

Enabling AI to explain its predictions in plain language

Using LLMs to convert machine-learning explanations into readable narratives could help users make better decisions about when to trust a model.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Research School of Engineering

Citation tool offers a new approach to trustworthy AI-generated content

Researchers develop “ContextCite,” an innovative method to track AI’s source attribution and detect potential misinformation.

Artificial Intelligence Automobiles Computer modeling Data Design Electric vehicles Energy efficiency Fluid dynamics machine learning Mechanical engineering Research School of Engineering

Want to design the car of the future? Here are 8,000 designs to get you started.

MIT engineers developed the largest open-source dataset of car designs, including their aerodynamics, that could speed design of eco-friendly cars and electric vehicles.

Artificial Intelligence Computer chips Computer science and technology Data Electrical engineering and computer science (EECS) Electronics machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Optics Photonics Research Research Laboratory of Electronics School of Engineering

Photonic processor could enable ultrafast AI computations with extreme energy efficiency

This new device uses light to perform the key operations of a deep neural network on a chip, opening the door to high-speed processors that can learn in real-time.

Alumni/ae Artificial Intelligence Data Equity and inclusion Faculty Latin America Media Lab Profile Race and gender School of Architecture and Planning Urban studies and planning Women

A data designer driven to collaborate with communities

Associate Professor Catherine D’Ignazio thinks carefully about how we acquire and display data — and why we lack it for many things.

AgeLab Artificial Intelligence Automobiles Autonomous vehicles Behavior Center for Transportation and Logistics Collaboration Data Industry Logistics Safety Transportation

Building an understanding of how drivers interact with emerging vehicle technologies

The MIT Advanced Vehicle Technology Consortium provides data-driven insights into driver behavior, along with trust in AI and advance vehicle technology.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering

Can robots learn from machine dreams?

MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI’s potential for creating robotics training data.

Algorithms Artificial Intelligence Computer science and technology Data Design Human-computer interaction Interview machine learning Mechanical engineering MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

3 Questions: Inverting the problem of design

MIT and IBM researchers are creating linkage mechanisms to innovate human-AI kinematic engineering.