{"id":{"repo_id":"nps","oai_identifier":"oai:calhoun.nps.edu:10945/74995"},"canonical_url":"https://search.dev.ndltd.org/etd/nps/oai:calhoun.nps.edu:10945/74995","repository":{"repo_id":"nps","name":"Naval Postgraduate School","base_url":"https://calhoun.nps.edu/server/oai/request"},"display":{"title":"A NEW ENEMY: AN EXPLORATION OF GENERATIVE ARTIFICIAL INTELLIGENCE WITHIN LAW ENFORCEMENT'S FIGHT AGAINST CHILD EXPLOITATION","abstract":"Advances in generative artificial intelligence (GAI) have enabled the creation of highly realistic images and videos of child sexual abuse material (CSAM) without the involvement of an actual child. Its growth and future capabilities pose significant challenges for U.S. law enforcement agencies operating under statutory frameworks that were not designed to address artificial intelligence (AI)–generated CSAM. This thesis asks: How can U.S. law enforcement agencies overcome the problems that GAI poses to CSAM investigations and prosecutions and bring justice to the victimized individuals? Using a qualitative legal and policy analysis, this study examines the technological foundations of GAI, evaluates U.S. federal and Massachusetts CSAM statutes and case law, and identifies enforcement gaps created by constitutional constraints and evidentiary requirements. It then conducts a comparative analysis of the United Kingdom's statutory approach to CSAM. Overall, the U.S. legal framework remains limited in addressing AI–generated CSAM, forcing reliance on obscenity doctrines ill-suited to GAI. In contrast, the UK’s broader statutory definitions and preventive regulatory model show how AI-generated CSAM can be addressed as a child-protection risk rather than a speech-based exception. The thesis recommends statutory clarification and policy adaptations to better align U.S. law enforcement capabilities with the threats of GAI, strengthening child protection in the digital age.","abstract_html":"Advances in generative artificial intelligence (GAI) have enabled the creation of highly realistic images and videos of child sexual abuse material (CSAM) without the involvement of an actual child. Its growth and future capabilities pose significant challenges for U.S. law enforcement agencies operating under statutory frameworks that were not designed to address artificial intelligence (AI)–generated CSAM. This thesis asks: How can U.S. law enforcement agencies overcome the problems that GAI poses to CSAM investigations and prosecutions and bring justice to the victimized individuals? Using a qualitative legal and policy analysis, this study examines the technological foundations of GAI, evaluates U.S. federal and Massachusetts CSAM statutes and case law, and identifies enforcement gaps created by constitutional constraints and evidentiary requirements. It then conducts a comparative analysis of the United Kingdom's statutory approach to CSAM. Overall, the U.S. legal framework remains limited in addressing AI–generated CSAM, forcing reliance on obscenity doctrines ill-suited to GAI. In contrast, the UK’s broader statutory definitions and preventive regulatory model show how AI-generated CSAM can be addressed as a child-protection risk rather than a speech-based exception. The thesis recommends statutory clarification and policy adaptations to better align U.S. law enforcement capabilities with the threats of GAI, strengthening child protection in the digital age.","abstract_has_math":false,"creators":["Hannigan, Matthew G."],"institution":"Monterey, CA; Naval Postgraduate School","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Matei, Cristiana","Peters, Lynda A."],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026-03","date_published":"2026-03","updated_at":"2026-07-27T20:26:05Z","subjects":[],"languages":[],"rights":["Copyright is reserved by the copyright owner."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10945/74995","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Matei, Cristiana","Peters, Lynda A."]},{"key":"dc:creator","label":"Author","values":["Hannigan, Matthew G."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-05-12T16:52:10Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-05-12T16:52:10Z"]},{"key":"dc:date.issued","label":"Date","values":["2026-03"]},{"key":"dc:publisher","label":"Institution","values":["Monterey, CA; Naval Postgraduate School"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Copyright is reserved by the copyright owner."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10945/74995"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Advances in generative artificial intelligence (GAI) have enabled the creation of highly realistic images and videos of child sexual abuse material (CSAM) without the involvement of an actual child. Its growth and future capabilities pose significant challenges for U.S. law enforcement agencies operating under statutory frameworks that were not designed to address artificial intelligence (AI)–generated CSAM. This thesis asks: How can U.S. law enforcement agencies overcome the problems that GAI poses to CSAM investigations and prosecutions and bring justice to the victimized individuals? Using a qualitative legal and policy analysis, this study examines the technological foundations of GAI, evaluates U.S. federal and Massachusetts CSAM statutes and case law, and identifies enforcement gaps created by constitutional constraints and evidentiary requirements. It then conducts a comparative analysis of the United Kingdom's statutory approach to CSAM. Overall, the U.S. legal framework remains limited in addressing AI–generated CSAM, forcing reliance on obscenity doctrines ill-suited to GAI. In contrast, the UK’s broader statutory definitions and preventive regulatory model show how AI-generated CSAM can be addressed as a child-protection risk rather than a speech-based exception. The thesis recommends statutory clarification and policy adaptations to better align U.S. law enforcement capabilities with the threats of GAI, strengthening child protection in the digital age."]},{"key":"dc:title","label":"Title","values":["A NEW ENEMY: AN EXPLORATION OF GENERATIVE ARTIFICIAL INTELLIGENCE WITHIN LAW ENFORCEMENT'S FIGHT AGAINST CHILD EXPLOITATION"]}]}],"canonical_facts":{"dc:contributor.advisor":["Matei, Cristiana","Peters, Lynda A."],"dc:creator":["Hannigan, Matthew G."],"dc:date.accessioned":["2026-05-12T16:52:10Z"],"dc:date.available":["2026-05-12T16:52:10Z"],"dc:date.issued":["2026-03"],"dc:description.abstract":["Advances in generative artificial intelligence (GAI) have enabled the creation of highly realistic images and videos of child sexual abuse material (CSAM) without the involvement of an actual child. Its growth and future capabilities pose significant challenges for U.S. law enforcement agencies operating under statutory frameworks that were not designed to address artificial intelligence (AI)–generated CSAM. This thesis asks: How can U.S. law enforcement agencies overcome the problems that GAI poses to CSAM investigations and prosecutions and bring justice to the victimized individuals? Using a qualitative legal and policy analysis, this study examines the technological foundations of GAI, evaluates U.S. federal and Massachusetts CSAM statutes and case law, and identifies enforcement gaps created by constitutional constraints and evidentiary requirements. It then conducts a comparative analysis of the United Kingdom's statutory approach to CSAM. Overall, the U.S. legal framework remains limited in addressing AI–generated CSAM, forcing reliance on obscenity doctrines ill-suited to GAI. In contrast, the UK’s broader statutory definitions and preventive regulatory model show how AI-generated CSAM can be addressed as a child-protection risk rather than a speech-based exception. The thesis recommends statutory clarification and policy adaptations to better align U.S. law enforcement capabilities with the threats of GAI, strengthening child protection in the digital age."],"dc:identifier.uri":["https://hdl.handle.net/10945/74995"],"dc:publisher":["Monterey, CA; Naval Postgraduate School"],"dc:rights":["Copyright is reserved by the copyright owner."],"dc:title":["A NEW ENEMY: AN EXPLORATION OF GENERATIVE ARTIFICIAL INTELLIGENCE WITHIN LAW ENFORCEMENT'S FIGHT AGAINST CHILD EXPLOITATION"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T20:26:05Z"}