The Hidden Causes of AI Workslop—and How to Fix Them
About this episode
The episode discusses the issue of AI-generated workslop and its impact on team efficiency, featuring insights from experts on management's role in the problem.
As organizations and their employees ramp up their generative AI experimentation, leaders are facing a new problem: the rise of AI-generated "workslop," which seems okay on the surface but doesn't actually pass muster and, when passed on to colleagues, ultimately hurts team efficiency, performance, trust and morale. Kate Niederhoffer, chief scientist at BetterUp, and Jeff Hancock, professor of communication at Stanford, say that while it's tempting to blame individuals for this kind of misuse of ChatGPT and other tools, management is more often that not contributing to the workslop epidemic by putting pressure on employees to produce more and to use AI when possible without offering clear training or guidelines. Niederhoffer and Hancock offer advice on how to stem the tide of workslop. They are coauthors of the HBR articles "AI-Generated “Workslop” Is Destroying Productivity" and "Why People Create AI “Workslop”—and How to Stop It."
People in this episode
Guests: Kate Niederhoffer, Jeff Hancock
Topics covered
- AI workslop
- productivity
- team efficiency
- management
- generative AI
- employee training
Keywords
- AI
- workslop
- productivity
- management
- employee training
- generative AI
- efficiency
Mentioned in this episode
Organizations: BetterUp, Stanford
Books & works: AI-Generated “Workslop” Is Destroying Productivity, Why People Create AI “Workslop”—and How to Stop It
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