Democratic regulation of AI in the workplace

Jaideep Roy, Bibhas Saha

Research output: Contribution to journalArticlepeer-review

Abstract

When artificial intelligence (AI) displaces lower-skilled workers with higher intensity, electoral democracies may slow down automation in fear of unemployment and voter resentment. Using a Downsian model of elections where parties promise to limit automation and redistribute automation surplus, we show that when automation is highly productive democracies implement maximum automation, making all workers vulnerable to redundancy and distribute the entire surplus among the working population. Majority of the workers are gainers in the sense that their expected earnings exceed their (pre-automation) wage. When the automation surplus is low, democracies restrict automation and protect the high-skilled workers (including the median-skilled worker) but redistribute nothing to the vulnerable workers. Here, because of no compensation for redundancy all vulnerable workers become losers as their expected earnings fall below their basic wage. For highly productive automation, democracies achieve the first best worker welfare but otherwise may over- or under-provide automation.
Original languageEnglish
Pages (from-to)113-132
Number of pages20
JournalGames and Economic Behavior
Volume152
Early online date15 Apr 2025
DOIs
Publication statusE-pub ahead of print - 15 Apr 2025

Data Availability Statement

No data was used for the research described in the article.

Keywords

  • Artificial intelligence
  • Electoral competition
  • Regulation
  • Unemployment
  • Worker welfare

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

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