Task-Dependent Algorithm Aversion
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Abstract
Research suggests that consumers are averse to relying on algorithms to perform tasks that are typically done by humans, despite the fact that algorithms often perform better. The authors explore when and why this is true in a wide variety of domains. They find that algorithms are trusted and relied on less for tasks that seem subjective (vs. objective) in nature. However, they show that perceived task objectivity is malleable and that increasing a task’s perceived objectivity increases trust in and use of algorithms for that task. Consumers mistakenly believe that algorithms lack the abilities required to perform subjective tasks. Increasing algorithms’ perceived affective human-likeness is therefore…
Citation impact
1,217
total citations
- FWCI
- 73.10
- Percentile
- 100%
- References
- 50
Citations per year
Authors
3Topics & keywords
Topics
Keywords
- Computer science
- Objectivity (philosophy)
- Task (project management)
- Variety (cybernetics)
- Loss aversion
- Artificial intelligence
- Machine learning
- Cognitive psychology
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