Workday Podcasts When AI Scales Expertise, Who Gets Paid? - Future of Work Podcast
Oct 28, 2025
Dr. Danielle Li, an MIT professor and AI researcher, joins Kathy Pham to discuss the implications of AI on workplace dynamics. They dive into the AI paradox where training machines requires recognizing employee contributions. Li highlights how AI can centralize expertise but warns it may inadvertently diminish top performers' advantages. She advocates for transparency in data use and proposes the creation of a Chief Work Officer to fairly integrate human efforts with AI, making work more productive and enjoyable.
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AI Converts Tacit Skill Into Shared Knowledge
- AI can observe top performers and encode tacit judgment into shared organizational knowledge.
- This turns scattered expertise into a communal repository that accelerates learning across the firm.
Call-Center Study Shows Unequal Gains
- Danielle Li recounts a study where AI raised productivity mostly for novice call-center workers.
- Top performers' conversations trained the model but they received little of the resulting benefit.
Skills Become Portable Through Models
- When expertise is extracted into models, a worker's skill no longer solely 'lives' in their body.
- That creates value portability and raises questions about ownership and fair reward.