{"id":"https://openalex.org/W4415089829","doi":"https://doi.org/10.1145/3772318.3791762","title":"Beyond PII: How Users Attempt to Estimate and Mitigate Implicit LLM Inference","display_name":"Beyond PII: How Users Attempt to Estimate and Mitigate Implicit LLM Inference","publication_year":2026,"publication_date":"2026-04-13","ids":{"openalex":"https://openalex.org/W4415089829","doi":"https://doi.org/10.1145/3772318.3791762"},"language":"en","primary_location":{"id":"doi:10.1145/3772318.3791762","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3772318.3791762","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3772318.3791762","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055544107","display_name":"Synthia Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]},{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Synthia Qia Wang","raw_affiliation_strings":["Computer Science Department, University of Chicago, Chicago, Illinois, USA"],"raw_orcid":"https://orcid.org/0009-0004-7420-7052","affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Chicago, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I39422238","https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062970601","display_name":"Sai Teja Peddinti","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sai Teja Peddinti","raw_affiliation_strings":["Google Inc., Mountain View, California, USA"],"raw_orcid":"https://orcid.org/0009-0007-3242-9353","affiliations":[{"raw_affiliation_string":"Google Inc., Mountain View, California, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061868730","display_name":"Nina Taft","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nina Taft","raw_affiliation_strings":["Google, Sunnyvale, California, USA"],"raw_orcid":"https://orcid.org/0009-0008-8450-9627","affiliations":[{"raw_affiliation_string":"Google, Sunnyvale, California, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068586837","display_name":"Nick Feamster","orcid":"https://orcid.org/0000-0001-9315-5201"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nick Feamster","raw_affiliation_strings":["Department of Computer Science, University of Chicago, Chicago, Illinois, USA"],"raw_orcid":"https://orcid.org/0000-0001-9315-5201","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Chicago, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I40347166"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":20.1957,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.96477051,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8461999893188477,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8461999893188477,"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/T11719","display_name":"Data Quality and Management","score":0.7775999903678894,"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"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.7530999779701233,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.7412999868392944},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7070000171661377},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.5364000201225281},{"id":"https://openalex.org/keywords/rewriting","display_name":"Rewriting","score":0.41819998621940613},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.35850000381469727},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.3082999885082245},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.28529998660087585}],"concepts":[{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.7412999868392944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7390999794006348},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7070000171661377},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.5364000201225281},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.43709999322891235},{"id":"https://openalex.org/C154690210","wikidata":"https://www.wikidata.org/wiki/Q1668499","display_name":"Rewriting","level":2,"score":0.41819998621940613},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40880000591278076},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.35850000381469727},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33649998903274536},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.3330000042915344},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.30660000443458557},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3005000054836273},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2822999954223633},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2612000107765198},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25949999690055847},{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3772318.3791762","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3772318.3791762","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2509.12152","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.12152","pdf_url":"https://arxiv.org/pdf/2509.12152","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2509.12152","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.12152","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.1145/3772318.3791762","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3772318.3791762","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"such":[4],"as":[5],"ChatGPT":[6,70],"can":[7],"infer":[8],"personal":[9],"attributes":[10],"from":[11],"seemingly":[12],"innocuous":[13],"text,":[14],"raising":[15],"privacy":[16],"risks":[17],"beyond":[18],"memorized":[19],"data":[20],"leakage.":[21],"While":[22],"prior":[23],"work":[24,139],"has":[25],"demonstrated":[26],"these":[27],"risks,":[28,52],"little":[29,87],"is":[30,125],"known":[31],"about":[32],"how":[33],"users":[34],"estimate":[35],"and":[36,56,71,114,132],"respond.":[37],"We":[38,62,108],"conducted":[39],"a":[40,73,86],"survey":[41],"with":[42,66],"240":[43],"U.S.":[44],"participants":[45,80],"who":[46],"judged":[47],"text":[48],"snippets":[49],"for":[50],"inference":[51],"reported":[53],"concern":[54],"levels,":[55],"attempted":[57],"rewrites":[58,65,92],"to":[59,82],"block":[60],"inference.":[61],"compared":[63],"their":[64],"those":[67],"generated":[68],"by":[69],"Rescriber,":[72],"state-of-the-art":[74],"sanitization":[75],"tool.":[76],"Results":[77],"show":[78],"that":[79,116],"struggled":[81],"anticipate":[83],"inference,":[84],"performing":[85],"better":[88,101],"than":[89,102,106],"chance.":[90],"User":[91],"were":[93,135],"effective":[94],"in":[95,146],"just":[96],"28%":[97],"of":[98,143],"cases":[99],"-":[100],"Rescriber":[103],"but":[104],"worse":[105],"ChatGPT.":[107],"examined":[109],"our":[110],"participants\u2019":[111],"rewriting":[112],"strategies,":[113],"observed":[115],"while":[117],"paraphrasing":[118],"was":[119],"the":[120,127,141],"most":[121],"common":[122],"strategy":[123],"it":[124],"also":[126],"least":[128],"effective;":[129],"instead":[130],"abstraction":[131],"adding":[133],"ambiguity":[134],"more":[136],"successful.":[137],"Our":[138],"highlights":[140],"importance":[142],"inference-aware":[144],"design":[145],"LLM":[147],"interactions.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-12T00:00:00"}
