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Debiased machine learning, the currency of invoicing, and training good models with bad data: Meet the new experts bringing their knowledge and skill sets to the MIT Sloan School of Management.

MIT Sloan School of Management faculty members reflect on how innovations and ideas over the past 250 years influence business today.

Three levers — data architecture, data preparation, and data permissions — determine whether data becomes a reusable strategic asset or stays trapped in silos.

Freelancers, contractors, part-timers, gig workers, adjuncts, and other contingent workers deserve more respect, MIT Sloan professor emeritus Paul Osterman writes in his book “Disposable Workers.”

Artificial intelligence can make workers more capable and productive, but only if leaders design and deploy it to augment human judgment.

Researchers at the MIT Initiative on the Digital Economy share the latest insights about getting the most from working with AI, such as personality pairing and reorganizing job tasks.

As organizations scale generative AI, traditional governance models prove to be too rigid or too loose. Minimum viable governance calibrates oversight to risk, enabling responsible innovation.

In MIT’s international AI Negotiation Competition, “warmer” agents achieved better outcomes in negotiations with other AI agents.

A new paper explores how seeing economic value from artificial intelligence hinges on closing the gap between what AI can do and how humans can verify its outputs.

AI systems hold the promise of competitive advantage, but they can usher in cognitive decline among workers, says MIT Sloan School of Management’s Eric So. Learn how to protect cognitive capital.