{"id":"https://openalex.org/W4406612489","doi":"https://doi.org/10.1109/smc54092.2024.10831383","title":"Hype or Revolution: How GPT4, Claude3 Opus, and GPT3.5 Exaggerate Their Influence on HRM Occupations Exposed in Practice","display_name":"Hype or Revolution: How GPT4, Claude3 Opus, and GPT3.5 Exaggerate Their Influence on HRM Occupations Exposed in Practice","publication_year":2024,"publication_date":"2024-10-06","ids":{"openalex":"https://openalex.org/W4406612489","doi":"https://doi.org/10.1109/smc54092.2024.10831383"},"language":"en","primary_location":{"id":"doi:10.1109/smc54092.2024.10831383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":null,"display_name":"Yuanhan Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yuanhan Xie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100681435","display_name":"Tao Wang","orcid":"https://orcid.org/0000-0003-0944-4583"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100540332","display_name":"Jiayuan Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiayuan Sun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074623289","display_name":"Dayong Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dayong Shen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115947370","display_name":"Zhongshan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhongshan Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101373408","display_name":"Feng Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng Yao","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50356099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4574","last_page":"4580"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11631","display_name":"Retirement, Disability, and Employment","score":0.967199981212616,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11631","display_name":"Retirement, Disability, and Employment","score":0.967199981212616,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13812","display_name":"AI and HR Technologies","score":0.9624000191688538,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10517","display_name":"Financial Literacy, Pension, Retirement Analysis","score":0.9014999866485596,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/opus","display_name":"Opus","score":0.6626921892166138},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.34755051136016846},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.3438323736190796},{"id":"https://openalex.org/keywords/art","display_name":"Art","score":0.23647579550743103},{"id":"https://openalex.org/keywords/literature","display_name":"Literature","score":0.200298011302948}],"concepts":[{"id":"https://openalex.org/C2778950570","wikidata":"https://www.wikidata.org/wiki/Q1466199","display_name":"Opus","level":2,"score":0.6626921892166138},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34755051136016846},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.3438323736190796},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.23647579550743103},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.200298011302948}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc54092.2024.10831383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2584164347","https://openalex.org/W3149252920","https://openalex.org/W4313678819","https://openalex.org/W4381684347","https://openalex.org/W4386178880","https://openalex.org/W4391689754","https://openalex.org/W6849172373","https://openalex.org/W6850619096","https://openalex.org/W6853958782"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4242637632","https://openalex.org/W359817683","https://openalex.org/W584212684","https://openalex.org/W2484473596","https://openalex.org/W639542208","https://openalex.org/W591775547","https://openalex.org/W3149970553"],"abstract_inverted_index":{"This":[0,110],"study":[1],"investigates":[2],"the":[3,27,59,71,88,98,113,141,147],"actual":[4],"impact":[5,129],"of":[6,61,76,104,115],"ChatGPT":[7],"on":[8,130,154],"human":[9],"resource":[10],"management":[11],"(HRM)":[12],"occupations":[13],"and":[14,49,67,133,160],"compares":[15],"it":[16],"with":[17,44,74],"assessments":[18,95,156],"from":[19,26,40,46],"large":[20],"language":[21],"models":[22],"(LLMs).":[23],"Using":[24],"data":[25],"Occupational":[28],"Information":[29],"Network":[30],"(O*NET),":[31],"we":[32],"developed":[33],"a":[34],"novel":[35],"methodology":[36],"combining":[37],"real-world":[38,108],"evidence":[39],"Google":[41],"search":[42],"results":[43],"evaluations":[45],"GPT-4,":[47],"GPT-3.5,":[48],"Claude":[50],"3":[51],"Opus.":[52],"Our":[53,123],"findings":[54],"reveal":[55],"significant":[56],"variations":[57],"in":[58,120],"degree":[60],"exposure":[62,99],"among":[63],"HRM":[64,131],"occupations.":[65],"Training":[66],"Development":[68],"Managers":[69],"were":[70,87],"most":[72],"exposed,":[73],"86.52%":[75],"their":[77],"tasks":[78],"potentially":[79],"automated":[80],"by":[81,101],"ChatGPT,":[82],"while":[83],"Labor":[84],"Relations":[85],"Specialists":[86],"least":[89],"exposed":[90],"at":[91],"11.08%.":[92],"Notably,":[93],"LLM":[94,118,155],"consistently":[96],"overestimated":[97],"levels":[100],"an":[102],"average":[103],"30%":[105],"compared":[106],"to":[107,126,140],"evidence.":[109],"discrepancy":[111],"highlights":[112],"importance":[114],"critically":[116],"evaluating":[117],"capabilities":[119],"task":[121],"automation.":[122],"research":[124],"contributes":[125],"understanding":[127],"AI's":[128],"practices":[132],"provides":[134],"valuable":[135],"insights":[136],"for":[137,149,157],"professionals":[138],"adapting":[139],"AI":[142],"era.":[143],"It":[144],"also":[145],"underscores":[146],"need":[148],"caution":[150],"when":[151],"relying":[152],"solely":[153],"workforce":[158],"planning":[159],"development.":[161]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}