Making it easier to verify an AI model’s responses
By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.
AI simulation gives people a glimpse of their potential future self
By enabling users to chat with an older version of themselves, Future You is aimed at reducing anxiety and guiding young people to make better choices.
MIT launches new Music Technology and Computation Graduate Program
The program will invite students to investigate new vistas at the intersection of music, computing, and technology.
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.
Study: AI could lead to inconsistent outcomes in home surveillance
Researchers find large language models make inconsistent decisions about whether to call the police when analyzing surveillance videos.
Study: Transparency is often lacking in datasets used to train large language models
Researchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.
First AI + Education Summit is an international push for “AI fluency”
The three-day, hands-on conference hosted by the MIT RAISE Initiative welcomed youths and adults from nearly 30 countries.
MIT researchers use large language models to flag problems in complex systems
The approach can detect anomalies in data recorded over time, without the need for any training.
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.
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.
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.
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.
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.
“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.
How a quantum scientist, a nurse, and an economist are joining the fight against global poverty
The MITx MicroMasters in Data, Economics, and Design of Policy program educates learners around the world using its data-driven approach to poverty alleviation.