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
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Business Model and Practices Business Model |
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Date Last Updated |
December 7, 2018
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