Evidence map›Paper›PMID 40032709›Full record

ArticleArchives of sexual behavior2025

The Present and Future of Adult Entertainment: A Content Analysis of AI-Generated Pornography Websites.

Valerie A Lapointe, Simon Dubé, Sophia Rukhlyadyev, Tinhinane Kessai, David Lafortune

Abstract read
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In one paragraph

Article in Archives of sexual behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Valerie A LapointeDepartment of Psychology, Université du Québec à Montréal, Montreal, QC, H3C 3P8, Canada. lapointe.valerie.6@courrier.uqam.ca.ORCID http://orcid.org/0000-0001-9844-888X
Simon DubéKinsey Institute, Indiana University, Bloomington, IN, USA.ORCID http://orcid.org/0000-0003-4947-7937
Sophia RukhlyadyevDepartment of Psychology, Concordia University, Montréal, QC, Canada.
Tinhinane KessaiDepartment of Psychology, Concordia University, Montréal, QC, Canada.
David LafortuneDepartment of Sexology, Université du Québec à Montréal, Montréal, QC, Canada.ORCID http://orcid.org/0000-0003-2256-2584

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

AI-generated contentAI-pornArtificial agentsArtificial intelligencePornography

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.