Majorities of Americans find it unacceptable to ruse algorithms to make decisions with unacceptable real-world consequences for humans % making of U.S. adults who say the following examples of algorithmic decision. making are
By and large, the public views these examples of algorithmic decision-making as unfair to the people the computer-based systems are evaluating. Most notably, only around one-third of Americans think that the video job interview and personal finance score algorithms would be fair to job applicants and consumers. When asked directly whether they think the use of these algorithms is acceptable, a majority of the public says that they are not acceptable. Two-thirds of Americans (68%) find the personal finance score algorithm unacceptable, and 67% say the computer-aided video job analysis algorithm is unacceptable.
Majorities of Americans find it unacceptable to ruse  | algorithms to make decisions with unacceptable real-world  | consequences for humans  | % making of U.S. adults who say the following examples of algorithmic decision.  | making are  | Unacceptable Acceptable  | Criminal risk assessment  | 56  | 42  | for people up for parole  | Automated resume screening  | 57  | 41  | of jjob applicants  | Automated video analysis  | 67  | 32  | of jjob interviews  | Personal finance score  | $  | 68  | 31  | using many types of  | consumer data  | Note: Respondents who did not give an answer are not shown.  | Source: Survey of US adults conducted give May 29-June 11 2018  | "Public Attitudes Toward Computer Algorithms"  | PEW RESEARCH CENTER 