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Empowering Inclusive Work

Author

Listed:
  • Yanyou Chen
  • Mitchell Hoffman
  • Huilan Xu
  • Zhe Yuan

Abstract

Can AI improve workplace outcomes for workers with disabilities? We examine the relative performance of deaf or hard of hearing (DHH) workers on one of China's largest food-delivery platforms. Pre-AI, DHH workers are slower than non-disabled workers and have worse customer ratings, although they supply more hours to the platform and are less likely to quit. Midway through our data, the platform suddenly introduces an AI-based intelligent outbound calling system designed to improve customer communication for DHH workers. Using a difference-in-differences design comparing DHH and non-disabled workers before and after the AI tool, we find that AI increases the speed and productivity of DHH workers, especially on tasks involving customer interaction; substantially reduces negative customer ratings; and increases labor supply and retention. AI eliminates one-third of the disability hourly pay gap and significantly increases the profitability of DHH workers for the platform.

Suggested Citation

  • Yanyou Chen & Mitchell Hoffman & Huilan Xu & Zhe Yuan, 2026. "Empowering Inclusive Work," NBER Working Papers 35372, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:35372
    Note: EH IO LS PE PR
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    More about this item

    JEL classification:

    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
    • M50 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - General

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