{"id":"https://openalex.org/W7167097990","doi":"https://doi.org/10.48550/arxiv.2607.00395","title":"Child Safety in Generative AI: An Expert-Guided and Incident-Grounded Evaluation Framework","display_name":"Child Safety in Generative AI: An Expert-Guided and Incident-Grounded Evaluation Framework","publication_year":2026,"publication_date":"2026-07-01","ids":{"openalex":"https://openalex.org/W7167097990","doi":"https://doi.org/10.48550/arxiv.2607.00395"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.00395","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00395","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.00395","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120793405","display_name":"Haein Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kong, Haein","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5120793405"],"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":0.20010000467300415,"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":0.20010000467300415,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.17219999432563782,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0997999981045723,"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/guard","display_name":"Guard (computer science)","score":0.6384000182151794},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5527999997138977},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4997999966144562},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.48840001225471497},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.46320000290870667},{"id":"https://openalex.org/keywords/risk-assessment","display_name":"Risk assessment","score":0.4316999912261963},{"id":"https://openalex.org/keywords/hazard","display_name":"Hazard","score":0.4309999942779541},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.375900000333786}],"concepts":[{"id":"https://openalex.org/C141141315","wikidata":"https://www.wikidata.org/wiki/Q2379942","display_name":"Guard (computer science)","level":2,"score":0.6384000182151794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5583000183105469},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5527999997138977},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4997999966144562},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.48840001225471497},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.46320000290870667},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.46050000190734863},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C49261128","wikidata":"https://www.wikidata.org/wiki/Q1132455","display_name":"Hazard","level":2,"score":0.4309999942779541},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34950000047683716},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.34779998660087585},{"id":"https://openalex.org/C105002631","wikidata":"https://www.wikidata.org/wiki/Q4833645","display_name":"Subject-matter expert","level":3,"score":0.3458000123500824},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3037000000476837},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C56995899","wikidata":"https://www.wikidata.org/wiki/Q1126687","display_name":"Focus group","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26989999413490295},{"id":"https://openalex.org/C3018395757","wikidata":"https://www.wikidata.org/wiki/Q1379672","display_name":"Evaluation methods","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.00395","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00395","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:10.48550/arxiv.2607.00395","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00395","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"generative":[1],"AI":[2,58,73],"is":[3,11],"increasingly":[4],"used":[5],"by":[6,129],"children":[7],"and":[8,72,76,98,142],"adolescents,":[9],"there":[10],"a":[12,82],"growing":[13],"need":[14],"for":[15,21,61,86],"risk":[16,54,140],"evaluation":[17,28,49,137,148],"frameworks":[18,29],"that":[19,51,115],"account":[20],"child-specific":[22],"harms.":[23],"However,":[24],"most":[25],"existing":[26],"safety":[27],"focus":[30],"on":[31,104],"general":[32],"user":[33,110,125],"populations,":[34],"often":[35],"overlooking":[36],"risks":[37],"unique":[38],"to":[39,80,94,107,121,138],"younger":[40],"users.":[41],"To":[42],"address":[43],"this":[44,78],"gap,":[45],"we":[46,90],"propose":[47],"an":[48],"framework":[50,65,93],"integrates":[52],"expert-guided":[53],"factors":[55],"with":[56],"real-world":[57],"incident":[59,74],"data":[60],"child":[62],"safety.":[63],"The":[64],"identifies":[66],"hazard":[67],"categories":[68,141],"from":[69],"expert":[70],"guidelines":[71],"databases":[75],"uses":[77],"information":[79],"construct":[81],"synthetic":[83],"test":[84],"set":[85],"model":[87],"evaluation.":[88],"Particularly,":[89],"apply":[91],"the":[92,95,136,147],"education":[96],"domain":[97,144],"evaluate":[99],"three":[100],"Llama":[101,117],"Guard":[102,118],"models":[103,119],"their":[105],"ability":[106],"detect":[108],"unsafe":[109,124],"prompts.":[111,126],"Our":[112],"results":[113],"show":[114],"current":[116],"struggle":[120],"identify":[122],"education-related":[123],"We":[127],"conclude":[128],"discussing":[130],"how":[131],"future":[132],"work":[133],"can":[134],"extend":[135],"additional":[139],"incorporate":[143],"experts":[145],"throughout":[146],"pipeline.":[149]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-03T00:00:00"}
