
How AI Will Change the Workplace
IDSS affiliate Stuart Madnick explores how artificial intelligence could make scamming easier and more dangerous.
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An AI challenge only humans can solve
In their new book, “Power and Progress,” Daron Acemoglu and Simon Johnson ask whether the benefits of AI will be shared widely or feed inequality.
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A better way to study ocean currents
A new machine-learning model from researchers including IDSS affiliate Tamara Broderick makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.
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Advocating for science budget and policy
Mahmoud Ramadan (TPP ’23), a member of MIT’s Science Policy Initiative Executive Board, organized a trip to Capitol Hill to advocate for continued and increased federal support for scientific research. The delegation included TPP students Nirmal Bhatt, Amy Huynh, and Graham Turk.
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Will robots and AI take our jobs?
IDSS affiliate Yossi Sheffi discusses his new book “The Magic Conveyor Belt,” and his research examining the potential impact of AI on the future of work.
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New research: Twitter bot detection tools aren’t very good
When is a bot not a bot? When it likes a tweet, according to a new paper by researchers including IDSS postdoc Zachary Schutzman that pokes holes in bot detection methodology.
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David Gamarnik named IMS Fellow
Gamarnik received the award for contributions to discrete probability, including the theory of random graphs, algorithms and computations, as well as queueing theory.
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Will artificial intelligence help — or hurt — medicine?
Assistant Professor Marzyeh Ghassemi examines how the increasing use of artificial intelligence could impact medical care.
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Opinion: The writers’ strike is partly about AI. They’re right to worry
IDSS core faculty Daron Acemoglu encourages creating incentives for innovators to apply AI-related technology to address real human problems — and to shift away from developing the tools of social oppression.
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Researchers create a tool for accurately simulating complex systems
System developed by researchers including IDSS core faculty Devavrat Shah eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.
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