The Human Black-Box: The Illusion of Understanding Human Better Than Algorithmic Decision-Making

被引:32
作者
Bonezzi, Andrea [1 ]
Ostinelli, Massimiliano [2 ]
Melzner, Johann [1 ]
机构
[1] NYU, Stern Sch Business, 40 West 4th St, New York, NY 10012 USA
[2] Winthrop Univ, Coll Business Adm, Rock Hill, SC 29733 USA
关键词
understanding; projection; illusion of explanatory depth; algorithms; algorithm aversion; SOCIAL PROJECTION; CATEGORIZATION; PERCEPTION; LIMITS; TREES;
D O I
10.1037/xge0001181
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
As algorithms increasingly replace human decision-makers, concerns have been voiced about the black-box nature of algorithmic decision-making. These concerns raise an apparent paradox. In many cases, human decision-makers are just as much of a black-box as the algorithms that are meant to replace them. Yet, the inscrutability of human decision-making seems to raise fewer concerns. We suggest that one of the reasons for this paradox is that people foster an illusion of understanding human better than algorithmic decision-making, when in fact, both are black-boxes. We further propose that this occurs, at least in part, because people project their own intuitive understanding of a decision-making process more onto other humans than onto algorithms, and as a result, believe that they understand human better than algorithmic decision-making, when in fact, this is merely an illusion.
引用
收藏
页码:2250 / 2258
页数:9
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