{"id":"https://openalex.org/W7125427419","doi":"https://doi.org/10.48550/arxiv.2601.15064","title":"Incentive-Tuning: Understanding and Designing Incentives for Empirical Human-AI Decision-Making Studies","display_name":"Incentive-Tuning: Understanding and Designing Incentives for Empirical Human-AI Decision-Making Studies","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7125427419","doi":"https://doi.org/10.48550/arxiv.2601.15064"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.15064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.15064","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.15064","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123605164","display_name":"Simran Kaur","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kaur, Simran","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090642445","display_name":"Sara Salimzadeh","orcid":"https://orcid.org/0000-0001-8734-951X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salimzadeh, Sara","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5123545874","display_name":"Ujwal Gadiraju","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gadiraju, Ujwal","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5123605164"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.5460000038146973,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.5460000038146973,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.1712999939918518,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10803","display_name":"Innovative Human-Technology Interaction","score":0.037700001150369644,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.8877000212669373},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6274999976158142},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.5328999757766724},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.5321000218391418},{"id":"https://openalex.org/keywords/empirical-evidence","display_name":"Empirical evidence","score":0.487199991941452},{"id":"https://openalex.org/keywords/judgement","display_name":"Judgement","score":0.45399999618530273},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41690000891685486}],"concepts":[{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.8877000212669373},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6274999976158142},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.5328999757766724},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.5321000218391418},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.49559998512268066},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C2776548248","wikidata":"https://www.wikidata.org/wiki/Q12621536","display_name":"Judgement","level":2,"score":0.45399999618530273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44130000472068787},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C74196892","wikidata":"https://www.wikidata.org/wiki/Q7781188","display_name":"Thematic analysis","level":3,"score":0.38499999046325684},{"id":"https://openalex.org/C3859990","wikidata":"https://www.wikidata.org/wiki/Q382996","display_name":"Incentive program","level":3,"score":0.3725999891757965},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36880001425743103},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3564999997615814},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3456999957561493},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.336899995803833},{"id":"https://openalex.org/C2776889888","wikidata":"https://www.wikidata.org/wiki/Q1135789","display_name":"Unintended consequences","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.32919999957084656},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3149999976158142},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.2660999894142151},{"id":"https://openalex.org/C8858961","wikidata":"https://www.wikidata.org/wiki/Q7068367","display_name":"Nudge theory","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.26019999384880066},{"id":"https://openalex.org/C189708586","wikidata":"https://www.wikidata.org/wiki/Q1504425","display_name":"Systematic review","level":3,"score":0.2547000050544739},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.15064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.15064","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.15064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.15064","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.7098581194877625,"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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"AI":[0,25,46],"has":[1,16],"revolutionised":[2],"decision-making":[3,21,49,121,152],"across":[4],"various":[5],"fields.":[6],"Yet":[7],"human":[8],"judgement":[9],"remains":[10],"paramount":[11],"for":[12,48,117,150,205,227,250],"high-stakes":[13],"decision-making.":[14,261],"This":[15],"fueled":[17],"explorations":[18],"of":[19,32,59,66,75,82,98,114,135,167,195,259],"collaborative":[20],"between":[22],"humans":[23,44],"and":[24,50,100,127,144,178,219,236,253],"systems,":[26],"aiming":[27],"to":[28,109,197,233,246],"leverage":[29],"the":[30,64,80,83,111,140,165,179,188,209,221,248,257],"strengths":[31],"both.":[33],"To":[34],"explore":[35],"this":[36,52,105],"dynamic,":[37],"researchers":[38,199,214],"conduct":[39],"empirical":[40,119,153],"studies,":[41,122,207],"investigating":[42],"how":[43,51,171,213],"use":[45],"assistance":[47],"collaboration":[53],"impacts":[54],"results.":[55],"A":[56],"critical":[57,112],"aspect":[58],"conducting":[60,118],"these":[61,76,92,102],"studies":[62,77],"is":[63],"role":[65,113],"participants,":[67,84],"often":[68],"recruited":[69],"through":[70],"crowdsourcing":[71],"platforms.":[72],"The":[73],"validity":[74],"hinges":[78],"on":[79,124,184],"behaviours":[81,93],"hence":[85],"effective":[86,202],"incentives":[87],"that":[88],"can":[89,182,215],"potentially":[90],"affect":[91],"are":[94,174],"a":[95,132,193,228],"key":[96],"part":[97],"designing":[99,201],"executing":[101],"studies.":[103,154],"In":[104],"work,":[106],"we":[107,138,191,244],"aim":[108],"address":[110],"incentive":[115,129,148,169,172,203,222,234],"design":[116,149,223,235],"human-AI":[120,151,260],"focusing":[123],"understanding,":[125,190],"designing,":[126],"documenting":[128],"schemes.":[130],"Through":[131],"thematic":[133],"review":[134],"existing":[136],"research,":[137],"explored":[139],"current":[141],"practices,":[142],"challenges,":[143],"opportunities":[145],"associated":[146],"with":[147,241],"We":[155],"identified":[156],"recurring":[157],"patterns,":[158],"or":[159],"themes,":[160],"such":[161],"as":[162],"what":[163],"comprises":[164],"components":[166],"an":[168],"scheme,":[170],"schemes":[173,204],"manipulated":[175],"by":[176],"researchers,":[177],"impact":[180],"they":[181],"have":[183],"research":[185],"outcomes.":[186],"Leveraging":[187],"acquired":[189],"curated":[192],"set":[194],"guidelines":[196],"aid":[198],"in":[200,256],"their":[206],"called":[208],"Incentive-Tuning":[210],"Framework,":[211],"outlining":[212],"undertake,":[216],"reflect":[217],"on,":[218],"document":[220],"process.":[224],"By":[225],"advocating":[226],"standardised":[229],"yet":[230],"flexible":[231],"approach":[232],"contributing":[237],"valuable":[238],"insights":[239],"along":[240],"practical":[242],"tools,":[243],"hope":[245],"pave":[247],"way":[249],"more":[251],"reliable":[252],"generalizable":[254],"knowledge":[255],"field":[258]},"counts_by_year":[],"updated_date":"2026-01-23T23:24:52.574035","created_date":"2026-01-23T00:00:00"}
