Institute for Data Systems and Society (IDSS)

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Unpacking the bias of large language models

June 20, 2025

In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.

Melding data, systems, and society

June 11, 2025

A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.

Tracking gene expression changes through cell lineage progression with PORCELAN

February 19, 2025

A new method for detecting gene-expression patterns linked to lineage progression, providing a powerful tool for studying cell state memory across biological systems.

Validation technique could help scientists make more accurate forecasts

February 7, 2025

MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.

Toward video generative models of the molecular world

January 24, 2025

Starting with a single frame in a simulation, a new system uses generative AI to emulate the dynamics of molecules, connecting static molecular structures and developing blurry pictures into videos.

Beery, Farina, Ghassemi, Kim named AI2050 Early Career Fellows

December 10, 2024

The new crop of AI2050 Early Career Fellows was announced Dec. 10th.

MIT researchers develop an efficient approach for training more reliable reinforcement learning models, focusing on complex tasks that involve variability. Image credits: MIT News; iStock

MIT researchers develop an efficient way to train more reliable AI agents

December 6, 2024

The technique could make AI systems better at complex tasks that involve variability.

A causal theory for studying the cause-and-effect relationships of genes

November 12, 2024

By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.

Caption:The new ICSR Data Hub serves as an evolving, public web depository of datasets gathered by MIT researchers examining racial bias in American society and institutions.

Empowering systemic racism research at MIT and beyond

November 6, 2024

Researchers in the MIT Initiative on Combatting Systemic Racism are building an open data repository to advance research on racial inequity in domains like policing, housing, and health care.

Study: AI could lead to inconsistent outcomes in home surveillance

October 2, 2024

Researchers find large language models make inconsistent decisions about whether to call the police when analyzing surveillance videos.