{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T21:13:00Z","timestamp":1781298780343,"version":"3.54.1"},"reference-count":28,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2022,5,28]],"date-time":"2022-05-28T00:00:00Z","timestamp":1653696000000},"content-version":"vor","delay-in-days":365,"URL":"http:\/\/www.sagepub.com\/licence-information-for-chorus"}],"funder":[{"DOI":"10.13039\/100006602","name":"Air Force Research Laboratory","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006602","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Hum Factors"],"published-print":{"date-parts":[[2023,3]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The present meta-analysis sought to determine significant factors that predict trust in artificial intelligence (AI). Such factors were divided into those relating to (a) the human trustor, (b) the AI trustee, and (c) the shared context of their interaction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>There are many factors influencing trust in robots, automation, and technology in general, and there have been several meta-analytic attempts to understand the antecedents of trust in these areas. However, no targeted meta-analysis has been performed examining the antecedents of trust in AI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>Data from 65 articles examined the three predicted categories, as well as the subcategories of human characteristics and abilities, AI performance and attributes, and contextual tasking. Lastly, four common uses for AI (i.e., chatbots, robots, automated vehicles, and nonembodied, plain algorithms) were examined as further potential moderating factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Results showed that all of the examined categories were significant predictors of trust in AI as well as many individual antecedents such as AI reliability and anthropomorphism, among many others.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Overall, the results of this meta-analysis determined several factors that influence trust, including some that have no bearing on AI performance. Additionally, we highlight the areas where there is currently no empirical research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Application<\/jats:title>\n                    <jats:p>Findings from this analysis will allow designers to build systems that elicit higher or lower levels of trust, as they require.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/00187208211013988","type":"journal-article","created":{"date-parts":[[2021,5,28]],"date-time":"2021-05-28T14:16:07Z","timestamp":1622211367000},"page":"337-359","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":304,"title":["Trust in Artificial Intelligence: Meta-Analytic Findings"],"prefix":"10.1177","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0051-0150","authenticated-orcid":false,"given":"Alexandra D.","family":"Kaplan","sequence":"first","affiliation":[{"name":"University of Central Florida, Orlando, Florida, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Theresa T.","family":"Kessler","sequence":"additional","affiliation":[{"name":"Georgia Tech Research Institute, Atlanta, Georgia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. Christopher","family":"Brill","sequence":"additional","affiliation":[{"name":"Air Force Research Laboratory, Dayton, Ohio, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4936-066X","authenticated-orcid":false,"given":"P. A.","family":"Hancock","sequence":"additional","affiliation":[{"name":"University of Central Florida, Orlando, Florida, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2021,5,28]]},"reference":[{"key":"bibr3-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2017.3571053"},{"key":"bibr1-00187208211013988","volume-title":"Integrity-based trust violations within human-machine teaming","author":"Clark T","year":"2018"},{"key":"bibr2-00187208211013988","doi-asserted-by":"publisher","DOI":"10.7758\/9781610448864"},{"key":"bibr4-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1109\/THMS.2017.2717939"},{"key":"bibr27-00187208211013988","unstructured":"Green J. (2018). Tesla: Autopilot was on during deadly Mountain View crash.\n                      The Mercury News. Palo Alto\n                      . Retrieved November 13, 2019, from https:\/\/www.mercurynews.com\/2018\/03\/30\/tesla-autopilot-was-on-during-deadly-mountain-view-crash\/"},{"key":"bibr5-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1177\/1064804611415045"},{"key":"bibr6-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1177\/0018720811417254"},{"key":"bibr7-00187208211013988","author":"Hancock P. A.","year":"2020","journal-title":"Human Factors: The Journal of the Human Factors and Ergonomics Society"},{"key":"bibr8-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1805770115"},{"key":"bibr28-00187208211013988","volume-title":"Proceedings of the world Congress on engineering and computer science","volume":"1","author":"Haring K. S.","year":"2013"},{"key":"bibr9-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1177\/0018720814547570"},{"key":"bibr10-00187208211013988","unstructured":"Horwitz J., Timmons H. (2016). The scary similarities between Tesla\u2019s (TSLA) deadly autopilot crashes.\n                      Quartz. Atlantic Media\n                      . Retrieved November 13, 2019, from https:\/\/qz.com\/783009\/the-scary-similarities-between-teslas-tsla-deadly-autopilot-crashes\/"},{"key":"bibr11-00187208211013988","doi-asserted-by":"publisher","DOI":"10.4135\/9781412985031"},{"key":"bibr12-00187208211013988","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2018.00135"},{"key":"bibr13-00187208211013988","unstructured":"Lubben A. (2018). Self-driving Uber killed a pedestrian as human safety driver watched.\n                      Vice News. Vice Media.\n                      Retrieved November 13, 2019. https:\/\/www.vice.com\/en\/article\/kzxq3y\/self-driving-uber-killed-a-pedestrian-as-human-safety-driver-watched"},{"key":"bibr14-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1177\/0018720811406726"},{"key":"bibr15-00187208211013988","first-page":"2","volume":"27","author":"McCarthy J.","year":"1955","journal-title":"AI Magazine"},{"key":"bibr16-00187208211013988","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-151-4-200908180-00135"},{"key":"bibr18-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1037\/1076-898X.6.1.44"},{"key":"bibr17-00187208211013988","volume-title":"Proceedings of the human factors and ergonomics society annual meeting","author":"Morris D. M.","year":"2017"},{"key":"bibr19-00187208211013988","unstructured":"Ohlheiser A. (2016). Trolls turned Tay, Microsoft\u2019s fun millennial AI bot, into a genocidal maniac.\n                      Washington Post\n                      . Retrieved on June 24, 2020, from https:\/\/www.washingtonpost.com\/news\/the-intersect\/wp\/2016\/03\/24\/the-internet-turned-tay-microsofts-fun-millennial-ai-bot-into-a-genocidal-maniac\/"},{"key":"bibr20-00187208211013988","volume-title":"Computational intelligence","author":"Poole D.","year":"1998"},{"key":"bibr21-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1177\/0018720816634228"},{"key":"bibr22-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1177\/1064804618818592"},{"key":"bibr23-00187208211013988","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2019.01117"},{"key":"bibr24-00187208211013988","unstructured":"Suciu P. (2019). Data algorithms are being used on social media to track COVID-19\u2019s impact.\n                      Forbes\n                      . Retrieved March 19, 2020, from https:\/\/www.forbes.com\/sites\/petersuciu\/2020\/03\/12\/data-algorithms-are-being-used-on-social-media-to-track-covid-19s-impact\/#20bc4d0c68a9"},{"key":"bibr25-00187208211013988","doi-asserted-by":"publisher","DOI":"10.1145\/3319502.3374793"},{"key":"bibr26-00187208211013988","volume-title":"\u201cWe have to trust it, or else we can just throw it away\u201d: The use of decision support systems during extreme weather event","author":"Wang M. 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