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==== Algorithm Process and the role of System Transparency ====
One reason people display resistance to algorithms is a lack of understanding about how the algorithm is arriving at its recommendation.<ref name=":2" /> People also seem to have a better intuition for how another human would make recommendations. Whereas people assume that other humans will account for unique differences between situations, they sometimes perceive algorithms as incapable of considering individual differences and resist the algorithms accordingly.<ref>{{Cite journal|last1=Longoni|first1=Chiara|last2=Bonezzi|first2=Andrea|last3=Morewedge|first3=Carey K|date=2019-05-03|title=Resistance to Medical Artificial Intelligence|url=https://doi.org/10.1093/jcr/ucz013|journal=Journal of Consumer Research|volume=46|issue=4|pages=629–650|doi=10.1093/jcr/ucz013|issn=0093-5301|doi-access=free}}</ref>
==== Decision Domain ====
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==== Age ====
[[Digital natives]] are younger and have known technology their whole lives, while digital immigrants have not. Age is a commonly-cited factor hypothesized to affect whether or not people accept algorithmic recommendations. For example, one study found that trust in an algorithmic financial advisor was lower among older people compared with younger study participants.<ref>{{Cite journal|date=2020-02-01|title=Whose Algorithm Says So: The Relationships Between Type of Firm, Perceptions of Trust and Expertise, and the Acceptance of Financial Robo-Advice|url=https://www.sciencedirect.com/science/article/pii/S1094996819301112|journal=Journal of Interactive Marketing|language=en|volume=49|pages=107–124|doi=10.1016/j.intmar.2019.10.003|issn=1094-9968|hdl=1765/123799|hdl-access=free}}</ref> However, other research has found that algorithm aversion does not vary with age.<ref name=":1" />
== Proposed Methods to Overcome Algorithm Aversion ==
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