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Alex Pentland

As seen in: slideshare.net, Nature, CNBC, PLOS, PLOS ONE, WIRED Magazine, Communications of the ACM, Harvard Business Review, IEEE Spectrum, New Scientist and
HAI Stanford, ToshibavProfessor, MIT, MembervUS National Academies
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Articles

Evaluating Amazon effects and the limited impact of COVID-19 with purchases crowdsourced from US consumers

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By Alex Berke, Dana Calacci, Alex Pentland, Kent Larson
| PLOS ONE
Citation: Berke A, Calacci D, Pentland A, Larson K (2025) Evaluating Amazon effects and the limited impact of COVID-19 with purchases crowdsourced from US consumers. PLoS One 20(11): e0336571. https://doi.org/10.1371/journal.pone.0336571 Editor: Zhifeng Gao, University of Florida, UNITED STATES OF AMERICA Received: January 22, 2025; Accepted: October 28, 2025; Published: November 7, 2025 Copyright: © 2025 Berke et al.
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MIT Media Lab Launches sAIpien: A Bold New Framework for Responsible AI – MIT Media Lab

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By Alex Pentland
| media.mit.edu
Cambridge, MA – October 16, 2025 — The MIT Media Lab announces the launch of sAIpien (Scalable AI Program for the Intelligent Evolution of Networks), a new program defining a responsible global spectrum for Artificial Intelligence. sAIpien supports organizations seeking to shape the future of AI through impact, trust, auditability, and human-empowered design.
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Study: Transparency is often lacking in datasets used to train large language models – MIT Media Lab

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By Adam Zewe, Alex Pentland
| media.mit.edu
By Adam Zewe | MIT News In order to train more powerful large language models, researchers use vast dataset collections that blend diverse data from thousands of web sources. But as these datasets are combined and recombined into multiple collections, important information about their origins and restrictions on how they can be used are often lost or confounded in the shuffle. Not only does this raise legal and ethical concerns, it can also damage a model’s performance.
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