| Keyword search (4,163 papers available) | ![]() |
"Pornography" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | The Present and Future of Adult Entertainment: A Content Analysis of AI-Generated Pornography Websites | Lapointe VA; Dubé S; Rukhlyadyev S; Kessai T; Lafortune D; | 40032709 PSYCHOLOGY |
| 2 | Identification and comprehensive characterization of moral disapproval and behavioral dysregulation-based pornography-use profiles across 42 countries | Bothe B; Tóth-Király I; Popova N; Nagy L; Koós M; Demetrovics Z; Potenza MN; Kraus SW; Ballester-Arnal R; Batthyány D; Bergeron S; Billieux J; Briken P; Burkauskas J; Cárdenas-López G; Carvalho J; Castro-Calvo J; Chen L; Ciocca G; Corazza O; Csako RI; Czakó A; Fernandez DP; Fernandez EF; Fujiwara H; Fuss J; Gabrhelík R; Gewirtz-Meydan A; Gjoneska B; Gola M; Hashim HT; Islam MS; Ismail M; Jiménez-Martínez MC; Jurin T; Kalina O; Klein V; Költo A; Lee CT; Lee SK; Lewczuk K; Lin CY; Lochner C; López-Alvarado S; Lukavská K; Mayta-Tristán P; Miller DJ; Orosová O; Orosz G; Ponce FP; Quintana GR; Quintero Garzola GC; Ramos-Diaz J; Rigaud K; Rousseau A; Scanavino MT; Schulmeyer MK; Sharan P; Shibata M; Shoib S; Sigre-Leirós V; Sniewski L; Spasovski O; Steibliene V; Stein DJ; Štulhofer A; Ünsal BC; Vaillancourt-Morel MP; Van Hout MC; Grubbs JB; | 39945767 PSYCHOLOGY |
| 3 | A Longitudinal Study of Adolescents' Pornography Use Frequency, Motivations, and Problematic Use Before and During the COVID-19 Pandemic | Bothe B; Vaillancourt-Morel MP; Dion J; Paquette MM; Massé-Pfister M; Tóth-Király I; Bergeron S; | 35059944 PSYCHOLOGY |
| 4 | Are sexual functioning problems associated with frequent pornography use and/or problematic pornography use? Results from a large community survey including males and females. | Bothe B, Tóth-Király I, Griffiths MD, Potenza MN, Orosz G, Demetrovics Z | 32810799 PSYCHOLOGY |
| 5 | High-Frequency Pornography Use May Not Always Be Problematic. | Bothe B, Tóth-Király I, Potenza MN, Orosz G, Demetrovics Z | 32033863 PSYCHOLOGY |
| Title: | The Present and Future of Adult Entertainment: A Content Analysis of AI-Generated Pornography Websites | ||||
| Authors: | Lapointe VA, Dubé S, Rukhlyadyev S, Kessai T, Lafortune D | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/40032709/ | ||||
| DOI: | 10.1007/s10508-025-03099-1 | ||||
| Publication: | Archives of sexual behavior | ||||
| Keywords: | AI-generated content; AI-porn; Artificial agents; Artificial intelligence; Pornography; | ||||
| PMID: | 40032709 | Category: | Date Added: | 2025-03-04 | |
| Dept Affiliation: |
PSYCHOLOGY
1 Department of Psychology, Université du Québec à Montréal, Montreal, QC, H3C 3P8, Canada. lapointe.valerie.6@courrier.uqam.ca. 2 Kinsey Institute, Indiana University, Bloomington, IN, USA. 3 Department of Psychology, Concordia University, Montréal, QC, Canada. 4 Department of Sexology, Université du Québec à Montréal, Montréal, QC, Canada. |
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Description: |
Fueled by advances in artificial intelligence (AI), the adult entertainment industry is undergoing a significant transformation. AI-generated pornography-or AI porn-is reshaping how people create and consume sexually explicit content, progressively offering rapid, mass access to large quantities of interactive and highly customizable experiences. Yet, despite its accelerated growth and potential implications for human eroticism, the current state of AI porn remains underexplored. Using a qualitative inductive content analysis, this study examined the functionalities, production strategies, and customization options available on websites allowing AI porn generation (n = 36). All websites included an English language option, which was used for this analysis. Following systematic open coding, categorization, and inter-rater validation, the prevalence of each category was quantified across website data. Results suggest that most sites presently enable image generation (80.6%), with others allowing video generation (41.7%), content alteration (e.g., deepnude, upscaling, facemorphing; 2.8-55.6%), and interactions with artificial agents (44.4%). AI porn generation also predominantly relies on feature selection (97.2%) and/or prompting (72.2%) to customize content elements, including character bases (e.g., human, fictional; 11.1-94.4%), sociodemographic characteristics (27.8-86.1%), body features (72.2%), clothing (75.0%), as well as foundational (resolution, theme, point-of-view; 22.2-69.4%) and contextual aspects (e.g., weather, setting, lighting; 11.1-63.9%). Carrying significant social and ethical implications, these findings point to a gradual evolution toward an AI-driven porn landscape where individuals can create and interact with sexual content tailored to their preferences and fantasies. |



