Algorithm aversion: Difference between revisions

Revision as of 16:15, 8 September 2021

Revision as of 16:16, 8 September 2021

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==== Domain expertise ====

Expertise in a particular field has been shown to increase algorithm aversion<ref name=":1" /> and reducedreduce use of algorithmic decision rules.<ref>{{Cite journal|date=1986-02-01|title=Factors influencing the use of a decision rule in a probabilistic task|url=https://www.sciencedirect.com/science/article/abs/pii/0749597886900464|journal=Organizational Behavior and Human Decision Processes|language=en|volume=37|issue=1|pages=93–110|doi=10.1016/0749-5978(86)90046-4|issn=0749-5978}}</ref> Overconfidence may partially explain this effect; experts might feel that an algorithm is not capable of the types of judgments they make. Compared to non-experts, experts also have more knowledge of the field and therefore may be more critical of a recommendation. Where a non-expert might accept a recommendation ("The algorithm must know something I don't.") the expert might find specific fault with the algorithm's recommendation ("This recommendation does not account for a particular factor").

[[Decision-making]] research has shown that experts in a given field tend to think about decisions differently than a non-expert.<ref>{{Citation|last=Feltovich|first=Paul J.|title=Studies of Expertise from Psychological Perspectives|date=2006|url=https://www.cambridge.org/core/books/cambridge-handbook-of-expertise-and-expert-performance/studies-of-expertise-from-psychological-perspectives/3A7FF4C6F3426BE751C71EDF84927741|work=The Cambridge Handbook of Expertise and Expert Performance|pages=41–68|editor-last=Ericsson|editor-first=K. Anders|series=Cambridge Handbooks in Psychology|place=Cambridge|publisher=Cambridge University Press|doi=10.1017/cbo9780511816796.004|isbn=978-1-107-81097-6|access-date=2021-09-08|last2=Prietula|first2=Michael J.|last3=Ericsson|first3=K. Anders|editor2-last=Charness|editor2-first=Neil|editor3-last=Feltovich|editor3-first=Paul J.|editor4-last=Hoffman|editor4-first=Robert R.}}</ref> Experts chunk and group information; for example, expert chess players will see opening positions (e.g., the [[Queen's Gambit]]) instead of individual pieces on the board. Experts may see a situation as a functional representation (e.g., a doctor could see a trajectory and predicted outcome for a patient instead of a list of medications and symptoms). These differences may also partly account for the increased algorithm aversion seen in experts.