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Can algorithms legitimize discrimination?

Andrea Bonezzi1, Massimiliano Ostinelli2

  • 1Stern School of Business, New York University.

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People perceive algorithmic bias less than human bias. This is because algorithms are believed to be objective, leading to underestimation of discriminatory outcomes and reinforcing stereotypes.

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Area of Science:

  • Psychology
  • Computer Science
  • Sociology

Background:

  • Algorithmic bias is a significant concern, with prior research focusing on technical origins.
  • A psychological perspective on algorithmic bias perception remains under-explored.

Purpose of the Study:

  • To investigate whether people perceive algorithmic decisions with disparities as less biased than human decisions.
  • To understand the psychological underpinnings of this perception asymmetry.

Main Methods:

  • The study likely involved experimental designs comparing perceptions of human versus algorithmic decision-making.
  • Participants' beliefs about algorithmic objectivity and decision-making processes were assessed.

Main Results:

  • Algorithmic decisions with gender or racial disparities were perceived as less biased than similar human decisions.
  • This perception stems from a belief in algorithmic objectivity and decontextualized rule application.

Conclusions:

  • The belief that algorithms are inherently fairer than humans leads to an underestimation of algorithmic bias.
  • This asymmetrical perception can reinforce stereotypes and decrease willingness to challenge discriminatory outcomes.