Human-computer interaction
Human-computer interaction

Human-computer interaction

Algorithms Artificial Intelligence Data Electrical Engineering & Computer Science (eecs) Human-computer interaction machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research Research Laboratory of Electronics School of Engineering

Method prevents an AI model from being overconfident about wrong answers

More efficient than other approaches, the “Thermometer” technique could help someone know when they should trust a large language model.

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

Study: When allocating scarce resources with AI, randomization can improve fairness

Introducing structured randomization into decisions based on machine-learning model predictions can address inherent uncertainties while maintaining efficiency.

Algorithms Artificial Intelligence Computer science and technology Economics Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering School of Humanities Arts and Social Sciences

Large language models don’t behave like people, even though we may expect them to

A new study shows someone’s beliefs about an LLM play a significant role in the model’s performance and are important for how it is deployed.

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

How to assess a general-purpose AI model’s reliability before it’s deployed

A new technique enables users to compare several large models and choose the one that works best for their task.

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

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.

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“They can see themselves shaping the world they live in”

Developed by MIT RAISE, the Day of AI curriculum empowers K-12 students to collaborate on local and global challenges using AI.

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Mouth-based touchpad enables people living with paralysis to interact with computers

The startup Augmental allows users to operate phones and other devices using their tongue, mouth, and head gestures.

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School of Engineering welcomes new faculty

Fifteen new faculty members join six of the school’s academic departments.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) Game theory Human-computer interaction machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Natural language processing Research Robotics School of Engineering

Using ideas from game theory to improve the reliability of language models

A new “consensus game,” developed by MIT CSAIL researchers, elevates AI’s text comprehension and generation skills.

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President Sally Kornbluth and OpenAI CEO Sam Altman discuss the future of AI

The conversation in Kresge Auditorium touched on the promise and perils of the rapidly evolving technology.