U.S. Adults Perceived Fairness of Algorithmic Decision-Making Programs

Proof Point

Pew Research Center study found more than half of U.S. adults concerned about fairness of algorithmic decision-making in 2018, particularly in determining credit scores and analyzing job interviews

U.S. Adults Perceived Fairness of Algorithmic Decision-Making Programs

June 2018 (percentage)

Note: Data from Pew Research Center’s Public Attitudes Toward Computer Algorithms Survey of 4,594 U.S adults last June 2018

Proof Point Findings

  • Algorithmic Decision-Making Programs – Technologies using artificial intelligence (AI) to analyze data and complex analytics to make decisions without human intervention
  • Overall Concern – At least half of respondents in Pew Research Center survey believe algorithmic decision-making programs are not fair to people they evaluated in 2018
  • Most Unfair Systems – Automated personal finance scoring and automated video analysis of job interviews identified by highest percentage of respondents to be unfair
  • Key Growth Drivers – Include increasing industry adoption of AI technologies to automate processes, accelerating sophistication of AI-based applications, and growing consciousness and aversion toward discriminating business practices


Business Model and Practices

Business Model
and Practices


Date Last Updated

December 7, 2018

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