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Leading with AI
Insights for success in AI-driven organizations.
The Latest
How AI-empowered ‘citizen developers’ drive digital transformation
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A new book explains how organizations are tapping AI-savvy front-line employees to create applications, mobile apps, automated workflows, and data analyses.
Our top 5 ‘Working Definitions‘ of 2024
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Terms that caught readers’ attention this year include low-ego leadership, glass cliff, financial nihilism, greenhushing, and exaptation strategy.
How to manage two types of generative AI
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Businesses have identified two types of generative AI: broadly applicable tools that boost personal productivity, and tailored solutions for specific purposes.
The top 10 MIT Sloan articles of 2024
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Once again, AI was everywhere. But research about federal spending leads the list.
8 MIT sustainability startups to watch
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From liquid green fuels to air-cooled nuclear batteries, here are new technologies that aim to reduce carbon emissions and transform heavy industry.
New database details AI risks
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The AI Risk Repository, a database of over 700 risks posed by AI, aims to provide a shared framework for monitoring and maintaining AI risk oversight.
How to redesign work for the age of AI
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Leaders from Google, ING, and Capital One advise avoiding the “gold rush mentality” around artificial intelligence and following these six steps instead.
MIT Sloan reading list: 7 books from 2024
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New books this year include a retirement how-to, the reissue of a classic entrepreneurship guide, and a look back at the California energy crisis.
‘Energy poverty’ hits US residents more in the South and Southwest
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The LIHEAP formula for calculating energy aid was written in the 1980s. Researchers propose a solution that recognizes the cost of cooling a warming south.
To help improve the accuracy of generative AI, add speed bumps
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Introducing “targeted friction” into AI workflows can improve overall accuracy and reduce uncritical adoption.