{"id":"https://openalex.org/W3163667721","doi":"https://doi.org/10.1145/3411764.3445562","title":"Human Reliance on Machine Learning Models When Performance Feedback is Limited: Heuristics and Risks","display_name":"Human Reliance on Machine Learning Models When Performance Feedback is Limited: Heuristics and Risks","publication_year":2021,"publication_date":"2021-05-06","ids":{"openalex":"https://openalex.org/W3163667721","doi":"https://doi.org/10.1145/3411764.3445562","mag":"3163667721"},"language":"en","primary_location":{"id":"doi:10.1145/3411764.3445562","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3411764.3445562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045282669","display_name":"Zhuoran Lu","orcid":"https://orcid.org/0000-0002-1079-2043"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhuoran Lu","raw_affiliation_strings":["Purdue University, United States"],"affiliations":[{"raw_affiliation_string":"Purdue University, United States","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071294124","display_name":"Ming Yin","orcid":"https://orcid.org/0000-0002-7364-139X"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming Yin","raw_affiliation_strings":["Purdue University, United States"],"affiliations":[{"raw_affiliation_string":"Purdue University, United States","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045282669"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":17.3951,"has_fulltext":false,"cited_by_count":116,"citation_normalized_percentile":{"value":0.99540408,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9492999911308289,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.8136540055274963},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7361485958099365},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4606184661388397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41753727197647095}],"concepts":[{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.8136540055274963},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7361485958099365},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4606184661388397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41753727197647095},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3411764.3445562","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3411764.3445562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W596459078","https://openalex.org/W1497131193","https://openalex.org/W1875648771","https://openalex.org/W1902292770","https://openalex.org/W1964346230","https://openalex.org/W1972606905","https://openalex.org/W1976745354","https://openalex.org/W1994506128","https://openalex.org/W2003834455","https://openalex.org/W2010158189","https://openalex.org/W2033816895","https://openalex.org/W2043515850","https://openalex.org/W2048657872","https://openalex.org/W2063052894","https://openalex.org/W2088614984","https://openalex.org/W2101876245","https://openalex.org/W2110017995","https://openalex.org/W2110171129","https://openalex.org/W2110575096","https://openalex.org/W2134255645","https://openalex.org/W2137028279","https://openalex.org/W2145416536","https://openalex.org/W2146006411","https://openalex.org/W2152059621","https://openalex.org/W2282821441","https://openalex.org/W2333508197","https://openalex.org/W2439690324","https://openalex.org/W2562464660","https://openalex.org/W2576949977","https://openalex.org/W2581082771","https://openalex.org/W2611213375","https://openalex.org/W2788362053","https://openalex.org/W2804927761","https://openalex.org/W2897042519","https://openalex.org/W2901895173","https://openalex.org/W2905034244","https://openalex.org/W2915124689","https://openalex.org/W2916797267","https://openalex.org/W2916904544","https://openalex.org/W2923238906","https://openalex.org/W2941486823","https://openalex.org/W2942073295","https://openalex.org/W2942157335","https://openalex.org/W2952602496","https://openalex.org/W2970526411","https://openalex.org/W2972763980","https://openalex.org/W2979893369","https://openalex.org/W2982232682","https://openalex.org/W2984353433","https://openalex.org/W2988450373","https://openalex.org/W2995188596","https://openalex.org/W2999637955","https://openalex.org/W3008345048","https://openalex.org/W3009578469","https://openalex.org/W3029022390","https://openalex.org/W3037634279","https://openalex.org/W3046342149","https://openalex.org/W3099742594","https://openalex.org/W3100279624","https://openalex.org/W3103751997","https://openalex.org/W3121396613","https://openalex.org/W3125537303","https://openalex.org/W3125751566","https://openalex.org/W4243099674"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"an":[3],"under-explored":[4],"problem":[5],"of":[6,13,64,110,138],"AI-assisted":[7],"decision-making:":[8],"when":[9,54],"objective":[10],"performance":[11,55,103],"information":[12,90,104],"the":[14,33,41,62,84,92,108,132],"machine":[15,51],"learning":[16,52],"model":[17,70,85,102,120],"underlying":[18],"a":[19,69,119],"decision":[20],"aid":[21],"is":[22,57,121],"absent":[23],"or":[24],"scarce,":[25],"how":[26],"do":[27],"people":[28,43,67,75,87],"decide":[29],"their":[30,48],"reliance":[31,49,82,117,148],"on":[32,50,71,83,115,118,145,149],"model?":[34],"Through":[35],"three":[36],"randomized":[37],"experiments,":[38],"we":[39],"explore":[40],"heuristics":[42],"may":[44],"use":[45],"to":[46],"adjust":[47],"models":[53],"feedback":[56],"limited.":[58],"We":[59,134],"find":[60],"that":[61,74],"level":[63],"agreement":[65,114],"between":[66],"and":[68,141],"decision-making":[72],"tasks":[73],"have":[76],"high":[77,111],"confidence":[78,112,125],"in":[79,126],"significantly":[80],"affects":[81],"if":[86],"receive":[88],"no":[89],"about":[91],"model\u2019s":[93],"performance,":[94],"but":[95],"this":[96],"impact":[97],"will":[98],"change":[99],"after":[100],"aggregate-level":[101],"becomes":[105],"available.":[106],"Furthermore,":[107],"influence":[109],"human-model":[113],"people\u2019s":[116,124],"moderated":[122],"by":[123],"cases":[127],"where":[128],"they":[129],"disagree":[130],"with":[131],"model.":[133],"discuss":[135],"potential":[136],"risks":[137],"these":[139],"heuristics,":[140],"provide":[142],"design":[143],"implications":[144],"promoting":[146],"appropriate":[147],"AI.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":32},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":4}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}