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Abstract

With the rise of generative artificial intelligence (AI), a new form of pornography has emerged: AI-generated pornography (AI pornography, AI adult content, synthetic pornography). This phenomenon encompasses both entirely fictional content and deepfake pornography, which involves non-consensual depictions of celebrities and private individuals. While non-consensual deepfake pornography has sparked widespread concern, the broader range of experiences associated with AI pornography remains under-researched. This study aimed to address this gap by examining the spectrum of AI pornography experiences as shared on Reddit, adopting a communication process perspective. Specifically, it explored the following research questions (RQ): How do Reddit users address the production (RQ1), content (RQ2), use (RQ3), effects (RQ4), and ethical–legal implications (RQ5) of AI pornography in their posts? A total of 390 English-language public Reddit posts related to AI pornography were collected in August 2024 and analyzed using a manual quantitative content analysis guided by a reliability-tested codebook (mean Cohen’s kappa = 0.88). The analysis revealed that the production (RQ1: 59.5%) and content (RQ2: 60.8%) of AI pornography were the most frequently discussed topics, while use experiences (RQ3: 12.8%) were the least represented. Effects (RQ4: 37.2%) and ethical–legal implications (RQ5: 35.1%) were addressed in approximately one-third of posts. The AI pornography experiences addressed in Reddit posts ranged from outrage and concern regarding its actual and potential harms to curiosity, enjoyment, and economic benefits, underscoring the need for a nuanced response from policymakers, technology developers, educators, and mental health professionals.

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Introduction

The rise of generative artificial intelligence (AI) has enabled a new form of pornography: AI-generated pornography (also: AI-generated adult content; AI-generated NSFW [Not Safe for Work] content; AI pornography; synthetic pornography; Döring et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR9 “Döring, N., Le, T. D., Vowels, L. M., Vowels, M. J., & Marcantonio, T. L. (2025). The impact of artificial intelligence on human sexuality: A five-year literature review 2020–2024. Current Sexual Health Reports, 17(1), 4. https://doi.org/10.1007/s11930-024-00397-y

“)). AI pornography entails both purely fictional content without any attempt to represent existing individuals, including depictions of non-existing human beings (e.g., AI-generated “dream partners”) and fantasy creatures, as well as so-called deepfake pornography of celebrities and private persons. This content may be text-, audio-, or image-based, or a combination of these (Jacobsen & Simpson, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR20 “Jacobsen, B. N., & Simpson, J. (2024). The tensions of deepfakes. Information, Communication & Society, 27(6), 1095–1109. https://doi.org/10.1080/1369118X.2023.2234980

“); Karasavva & Noorbhai, [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR21 “Karasavva, V., & Noorbhai, A. (2021). The real threat of deepfake pornography: A review of Canadian policy. Cyberpsychology, Behavior, and Social Networking, 24(3), 203–209. https://doi.org/10.1089/cyber.2020.0272

“); Lapointe et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR31 “Lapointe, V. A., Dubé, S., Rukhlyadyev, S., Kessai, T., & Lafortune, D. (2025). The present and future of adult entertainment: A content analysis of AI-generated pornography websites. Archives of Sexual Behavior. https://doi.org/10.1007/s10508-025-03099-1

“); Mania, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR36 “Mania, K. (2024). Legal protection of revenge and deepfake porn victims in the European Union: Findings from a comparative legal study. Trauma, Violence, & Abuse, 25(1), 117–129. https://doi.org/10.1177/15248380221143772

“)). A recent literature review examined scholarly publications from 2020 to 2024 on the intersection of artificial intelligence and human sexuality, including the field of AI pornography (Döring et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR9 “Döring, N., Le, T. D., Vowels, L. M., Vowels, M. J., & Marcantonio, T. L. (2025). The impact of artificial intelligence on human sexuality: A five-year literature review 2020–2024. Current Sexual Health Reports, 17(1), 4. https://doi.org/10.1007/s11930-024-00397-y

“)). Of the 36 publications reporting on 41 AI pornography studies, nearly all concentrated exclusively on non-consensual deepfake pornography, highlighting a gap in research on other forms of AI-generated sexual content.

Against this backdrop, the current study aims to empirically examine a broad spectrum of consensual and non-consensual experiences with AI pornography. To gather organic accounts of such experiences, we selected Reddit, the largest English language forum platform (Rocha-Silva et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR51 “Rocha-Silva, T., Nogueira, C., & Rodrigues, L. (2024). Passive data collection on Reddit: A practical approach. Research Ethics, 20(3), 453–470. https://doi.org/10.1177/17470161231210542

“))—which is increasingly used to share experiences related to both sexuality (Stang et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR55 “Stang, P., Weiss, M., Winkler, C., & Scholz, S. (2025). Changing conversations: The rise of gender and sexuality discourse on Reddit [Letter to the Editor]. Archives of Sexual Behavior, 54(1), 1–5. https://doi.org/10.1007/s10508-024-03051-9

“)) and generative AI technology (Mentzer et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR39 “Mentzer, K., Price, J., & Singh, J. (2024). Analyzing Reddit discourse surrounding generative AI. Issues in Information Systems, 25(3), 277–292. https://doi.org/10.48009/3_iis_2024_122

“)), including their intersections. Across numerous Reddit forums, we identified several hundred posts detailing AI pornography experiences and opinions of several hundred Reddit users. This article highlights key characteristics of these reported experiences.

Our analysis is guided by a generic communication process model originating in communication research (Lasswell, 1948; Sapienza et al., [2015](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR53 “Sapienza, Z. S., Iyer, N., & Veenstra, A. S. (2015). Reading Lasswell’s model of communication backward: Three scholarly misconceptions. Mass Communication and Society, 18(5), 599–622. https://doi.org/10.1080/15205436.2015.1063666

“)) that traces the flow of media engagement from the media production process (1), to the characteristics of the produced media content (2), to the use of said media content (3), ultimately to the effects of the media content (4) and their ethical–legal implications (5). Our rationale for applying the communication process model (CPM) to AI pornography as a specific media content is twofold. First, the CPM offers a flexible yet systematic framework that is well-suited for the initial exploration of emerging media phenomena, such as AI-generated pornography, particularly in areas where empirical research remains scarce. It allows us to organize Reddit users’ experiences with AI pornography along this communicative trajectory. Second, we deliberately chose a generic model for this exploratory study to remain open to the broad range of topics spontaneously addressed in Redditors’ reports of their personal experiences. We view this as a necessary first step toward developing a more comprehensive research agenda.

In future studies, this generic framework could be productively combined with domain-specific theoretical perspectives—for example, theories of deviance or sexual pleasure to explore motivations and production contexts; feminist and queer theory to interrogate issues of sexism, consent, and heteronormativity in content; audience and reception theories to examine usage patterns and user types; and media effects theories or legal–ethical frameworks to assess potential individual and societal consequences. However, given the exploratory nature of our study and the organically generated Reddit data, it was neither feasible nor methodologically appropriate to preselect and apply a wide range of specific theories. Instead, the CPM served as a pragmatic, theory-informed scaffolding for organizing publicly shared experiences with AI pornography.

AI-Generated Pornography

The rapid advancement of generative AI has opened up new possibilities for digital content creation, including the production of pornographic content (Kardos, [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR22 “Kardos, B. (2025). Beyond the consent paradigm: Problematizing representations of AI-generated pornography in the education discourse of the UN. Policy Futures in Education, 23(5), 1021–1039. https://doi.org/10.1177/14782103251321045

“)). Many publicly accessible AI models for generating text, audio, and images—such as ChatGPT (OpenAI, [2025a](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR46 “OpenAI. (2025a). ChatGPT. https://chat.openai.com

“)), Gemini (Google, [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR14 “Google. (2025). Gemini. https://gemini.google.com

“)), DeepSeek (DeepSeek, [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR7 “DeepSeek. (2025). DeepSeek AI. https://www.deepseek.com

“)), DALL-E (OpenAI, [2025b](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR45 “OpenAI. (2025b). DALL-E. https://openai.com/dall-e

“)), and Midjourney (Midjourney, [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR40 “Midjourney. (2025). Midjourney. https://www.midjourney.com

“))—have implemented strict content moderation systems to prevent the creation of sexually explicit material. These safeguards are motivated by ethical considerations, legal obligations, and corporate interests in creating positive public opinion about AI models and the companies creating them.

However, a separate market for so-called unmoderated or uncensored generative AI tools has emerged, offering user-friendly platforms for producing sexually explicit content through web and app interfaces. So-called unmoderated generative AI tools allow (or do not explicitly prohibit) the creation of AI pornography in various formats, including pornographic stories (e.g., Dreampress.ai**,** MySpicyVanilla.com), chatbots designed for sexually explicit text and audio interactions (e.g., Kindroid.ai), and pornographic images or videos (e.g., PornPen.ai, Pornderful.ai**,** Unstability.ai). AI platforms marketed as uncensored or unmoderated that allow the generation of AI pornography may still be subject to moderation rules (e.g., prohibiting child sexual exploitation material). Additionally, individuals with advanced technical skills and access to robust computational resources can operate local AI models, bypassing public interfaces and their content moderation.

AI pornography refers to pornographic material—i.e., content that depicts or describes nude bodies and sexual activities in detail with the intent to sexually arouse the audience—created or modified (fully or partially) through AI-driven generative processes (Lang & Yermal, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR30 “Lang, J., & Yarmel, A. (2024). The ethics of customizable AI-generated pornography. Midwest Ethics Symposium ’24: Artificial Intelligence, MES 2024 Ethics & Artificial Intelligence. https://scholarship.depauw.edu/midwest_ethics/2024/2024/22/

“)). This technology offers consumers extensive options for personalizing and customizing such content. Historically, consumers have long had two primary avenues for producing pornographic material: (1) creating new material, such as writing erotic fan fiction stories (Döring, [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR8 “Döring, N. (2021). Erotic fan fiction. In A. D. Lykins (Ed.), Encyclopedia of sexuality and gender. Springer International Publishing. https://doi.org/10.1007/978-3-319-59531-3_65-1

“)) or recording personal sex videos (i.e., self-pornography or amateur pornography; e.g., Byron et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR3 “Byron, P., Newton, J. D. A., Hanson, O., Oviedo-Trespalacios, O., Saliba, B., & Demant, D. (2024). Social media, self-pornography, and gay/bisexual/queer men’s psychosexual wellbeing. SCM Studies in Communication and Media, 13(4), 438–464. https://doi.org/10.5771/2192-4007-2024-4-438

“)) and (2) modifying existing material, such as altering pornographic photos through cropping or digital image editing. Generative AI, however, has significantly enhanced the ease, speed, and convenience of both creating and modifying pornographic content. AI pornography platforms now integrate multiple converging technologies—including image and video generation, artificial agent generation, content alteration, and interactive customization tools such as prompting and feature selection—allowing users to craft deeply personalized, multimodal, and immersive sexual experiences (Lapointe et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR31 “Lapointe, V. A., Dubé, S., Rukhlyadyev, S., Kessai, T., & Lafortune, D. (2025). The present and future of adult entertainment: A content analysis of AI-generated pornography websites. Archives of Sexual Behavior. https://doi.org/10.1007/s10508-025-03099-1

“)). This development enables unprecedented levels of customization, fundamentally reshaping the landscape of pornographic content production and personalization (Lang & Yermal, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR30 “Lang, J., & Yarmel, A. (2024). The ethics of customizable AI-generated pornography. Midwest Ethics Symposium ’24: Artificial Intelligence, MES 2024 Ethics & Artificial Intelligence. https://scholarship.depauw.edu/midwest_ethics/2024/2024/22/

“)).

Two types of AI pornography are differentiated based on whether the likeness of a real person is being depicted: (1) fictional content which depicts entirely nonexistent human figures or fantasy creatures and (2) deepfake content which uses the likeness of real individuals, including celebrities or private persons (Jacobsen & Simpson, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR20 “Jacobsen, B. N., & Simpson, J. (2024). The tensions of deepfakes. Information, Communication & Society, 27(6), 1095–1109. https://doi.org/10.1080/1369118X.2023.2234980

“); Karasavva & Noorbhai, [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR21 “Karasavva, V., & Noorbhai, A. (2021). The real threat of deepfake pornography: A review of Canadian policy. Cyberpsychology, Behavior, and Social Networking, 24(3), 203–209. https://doi.org/10.1089/cyber.2020.0272

“); Mania, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR36 “Mania, K. (2024). Legal protection of revenge and deepfake porn victims in the European Union: Findings from a comparative legal study. Trauma, Violence, & Abuse, 25(1), 117–129. https://doi.org/10.1177/15248380221143772

“)). Deepfake pornography, often in the form of still images or video, can be easily created using specialized AI tools (e.g., so-called deepfake, faceswap, or nudify websites and apps). These tools require only a few facial photos or video snippets to superimpose the selected person’s likeness (typically their face and facial expressions, voice and speech style, body movements and gestures) onto pre-existing pornographic material. This is done through a type of machine learning called deep learning (hence deepfake), creating the appearance (hence deepfake) that the targeted individual participated in the depicted sexual act(s). Research on non-pornographic deepfakes indicates that the general public has difficulty distinguishing deepfakes from authentic footage (Köbis et al., [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR24 “Köbis, N. C., Doležalová, B., & Soraperra, I. (2021). Fooled twice: People cannot detect deepfakes but think they can. Iscience, 24(11), Article 103364. https://doi.org/10.1016/j.isci.2021.103364

“); Somoray & Miller, [2023](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR54 “Somoray, K., & Miller, D. J. (2023). Providing detection strategies to improve human detection of deepfakes: An experimental study. Computers in Human Behavior, 149, Article 107917. https://doi.org/10.1016/j.chb.2023.107917

“)).

Most deepfake pornography is created and disseminated without the consent of the affected individuals, falling under the category of non-consensual deepfake pornography (Ajder et al., [2019](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR1 “Ajder, H., Patrini, G., Cavalli, F., & Cullen, L. (2019). The state of deepfakes: Landscape, threats, and impact. Deeptrace. https://regmedia.co.uk/2019/10/08/deepfake_report.pdf

“); Karasavva & Noorbhai, [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR21 “Karasavva, V., & Noorbhai, A. (2021). The real threat of deepfake pornography: A review of Canadian policy. Cyberpsychology, Behavior, and Social Networking, 24(3), 203–209. https://doi.org/10.1089/cyber.2020.0272

“)). However, it is also possible to produce consensual deepfake pornography when two conditions are met: (1) the individuals being deepfaked have given informed consent, and (2) the pornography performers whose likenesses are being replaced have consented and authorized the use of their original material (Döring et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR9 “Döring, N., Le, T. D., Vowels, L. M., Vowels, M. J., & Marcantonio, T. L. (2025). The impact of artificial intelligence on human sexuality: A five-year literature review 2020–2024. Current Sexual Health Reports, 17(1), 4. https://doi.org/10.1007/s11930-024-00397-y

“)).

State of Research

Previous research on AI-generated pornography has predominantly focused on non-consensual deepfake pornography, as indicated by systematic (Döring et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR9 “Döring, N., Le, T. D., Vowels, L. M., Vowels, M. J., & Marcantonio, T. L. (2025). The impact of artificial intelligence on human sexuality: A five-year literature review 2020–2024. Current Sexual Health Reports, 17(1), 4. https://doi.org/10.1007/s11930-024-00397-y

“)) and nonsystematic (Deckker & Sumanasekara, [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR6 “Deckker, D., & Sumanasekara, S. (2025). Artificial intelligence and pornography: A comprehensive research review. World Journal of Advanced Research and Reviews, 26(2), 618–637. https://doi.org/10.30574/wjarr.2025.26.2.1739

“)) literature reviews. Theoretical studies explore ethical issues stemming from non-consensual deepfake pornography (e.g., Öhman, [2020](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR44 “Öhman, C. (2020). Introducing the pervert’s dilemma: A contribution to the critique of deepfake pornography. Ethics and Information Technology, 22(2), 133–140. https://doi.org/10.1007/s10676-019-09522-1

“); Story & Jenkins, [2023](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR57 “Story, D., & Jenkins, R. (2023). Deepfake pornography and the ethics of non-veridical representations. Philosophy & Technology, 36(3), 56. https://doi.org/10.1007/s13347-023-00657-0

“)) and examine existing and prospective legal frameworks to this new form of AI-enabled image-based sexual abuse (AI-IBSA) across various jurisdictions (e.g., Karasavva & Noorbhai, [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR21 “Karasavva, V., & Noorbhai, A. (2021). The real threat of deepfake pornography: A review of Canadian policy. Cyberpsychology, Behavior, and Social Networking, 24(3), 203–209. https://doi.org/10.1089/cyber.2020.0272

“); Mania, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR36 “Mania, K. (2024). Legal protection of revenge and deepfake porn victims in the European Union: Findings from a comparative legal study. Trauma, Violence, & Abuse, 25(1), 117–129. https://doi.org/10.1177/15248380221143772

“); Witt et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR63 “Witt, A., Henry, N., & Beard, G. (2024). Judicial constructions of harm in Australian image-based sexual abuse case law: A feminist discourse analysis. Social & Legal Studies, 33(6), 951–972. https://doi.org/10.1177/09646639241233992

“)). Comparative ethical–legal studies, for example, focus on the different sites of efficient regulation (e.g., individual creators and/or users of non-consensual deepfake pornography; AI platforms that enable its creation; social media platforms that enable its dissemination and publication; Zheng et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR65 “Zheng, G., Shu, J., & Li, K. (2025). Regulating deepfakes between lex lata and lex ferenda—a comparative analysis of regulatory approaches in the U.S., the EU and China. Crime, Law and Social Change, 83. https://doi.org/10.1007/s10611-024-10197-z

“)).

Empirical studies on deepfake pornography have investigated platforms and their users as well as deepfake victims. A content analysis of 36 websites for the generation of AI pornography found that most enable the generation of still images (80.6%), and many enable the generation of videos (41.7%) and AI agents (44.4%) through feature selection and/or prompting (Lapointe et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR31 “Lapointe, V. A., Dubé, S., Rukhlyadyev, S., Kessai, T., & Lafortune, D. (2025). The present and future of adult entertainment: A content analysis of AI-generated pornography websites. Archives of Sexual Behavior. https://doi.org/10.1007/s10508-025-03099-1

“)). Surveys have shown prevalence rates of deepfake pornography victimization (2%) and perpetration (2%) across different countries (Umbach et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR60 “Umbach, R., Henry, N., Beard, G. F., & Berryessa, C. M. (2024). Non-consensual synthetic intimate imagery: Prevalence, attitudes, and knowledge in 10 countries. In CHI ‘24, Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (pp. 1–20). Association for Computing Machinery. https://doi.org/10.1145/3613904.3642382

“)). Other studies have examined the prevalence of the broader phenomenon of digitally altered image-based sexual abuse (which would include, but is not limited to, deepfake pornography) victimization (14%) and perpetration (8%; Flynn et al., [2022](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR12 “Flynn, A., Powell, A., Scott, A. J., & Cama, E. (2022). Deepfakes and digitally altered imagery abuse: A cross-country exploration of an emerging form of image-based sexual abuse. British Journal of Criminology, 62(6), 1341–1358. https://doi.org/10.1093/bjc/azab111

“)). They have also investigated public opinion on deepfake pornography, finding that the majority of people in various countries condemn the practice, with attitudes influenced by factors such as gender and the celebrity status of victims (Fido et al., [2022](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR11 “Fido, D., Rao, J., & Harper, C. A. (2022). Celebrity status, sex, and variation in psychopathy predicts judgements of and proclivity to generate and distribute deepfake pornography. Computers in Human Behavior, 129, Article 107141. https://doi.org/10.1016/j.chb.2021.107141

“); Kugler & Pace, [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR27 “Kugler, M. B., & Pace, C. (2021). Deepfake privacy: Attitudes and regulation. Northwestern Public Law Research Paper, 21(4), 611–680. https://doi.org/10.2139/ssrn.3781968

“); Wang & Kim, [2022](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR61 “Wang, S., & Kim, S. (2022). Users’ emotional and behavioral responses to deepfake videos of K-pop idols. Computers in Human Behavior, 134, Article 107305. https://doi.org/10.1016/j.chb.2022.107305

“)). Some empirical studies and literature reviews have explored the motives, attitudes, and digital practices of deepfake pornography creators—which include entertainment, sexual gratification, technical experimentation, expressions of misogyny, and a desire for online status or community approval (Gamage et al., [2022](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR13 “Gamage, D., Ghasiya, P., Bonagiri, V., Whiting, M. E., & Sasahara, K. (2022). Are deepfakes concerning? Analyzing conversations of deepfakes on Reddit and exploring societal implications. In CHI ‘22, Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1–19). Association for Computing Machinery. https://doi.org/10.1145/3491102.3517446

“); Han et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR16 “Han, C., Li, A., Kumar, D., & Durumeric, Z. (2024). Characterizing the MrDeepFakes sexual deepfake marketplace. https://doi.org/10.48550/ARXIV.2410.11100

“); Popova, [2020](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR47 “Popova, M. (2020). Reading out of context: Pornographic deepfakes, celebrity and intimacy. Porn Studies, 7(4), 367–381. https://doi.org/10.1080/23268743.2019.1675090

“); Timmerman et al., [2023](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR59 “Timmerman, B., Mehta, P., Deb, P., Gallagher, K., Dolan-Gavitt, B., Garg, S., & Greenstadt, R. (2023). Studying the online deepfake community. Journal of Online Trust and Safety, 2. https://doi.org/10.54501/jots.v2i1.126

“); Winter & Salter, [2020](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR62 “Winter, R., & Salter, A. (2020). Deepfakes: Uncovering hardcore open source on GitHub. Porn Studies, 7(4), 382–397. https://doi.org/10.1080/23268743.2019.1642794

“)) as well as the deleterious effects that deepfake pornography can have on victims, such as reputational damage, job loss, and emotional distress (Flynn et al., [2022](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR12 “Flynn, A., Powell, A., Scott, A. J., & Cama, E. (2022). Deepfakes and digitally altered imagery abuse: A cross-country exploration of an emerging form of image-based sexual abuse. British Journal of Criminology, 62(6), 1341–1358. https://doi.org/10.1093/bjc/azab111

“); Laffier & Rehman, [2023](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR28 “Laffier, J., & Rehman, A. (2023). Deepfakes and harm to women. Journal of Digital Life and Learning, 3(1), 1–21. https://doi.org/10.51357/jdll.v3i1.218

“); Maddocks, [2020](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR34 “Maddocks, S. (2020). ‘A deepfake porn plot intended to silence me’: Exploring continuities between pornographic and ‘political’ deep fakes. Porn Studies, 7(4), 415–423. https://doi.org/10.1080/23268743.2020.1757499

“)). Some media commentators (e.g., Saner, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR52 “Saner, E. (2024). Inside the Taylor Swift deepfake scandal: ‘It’s men telling a powerful woman to get back in her box’. The Guardian. https://www.theguardian.com/technology/2024/jan/31/inside-the-taylor-swift-deepfake-scandal-its-men-telling-a-powerful-woman-to-get-back-in-her-box

“)) and researchers (Henry & Beard, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR18 “Henry, N., & Beard, G. (2024). Image-based sexual abuse perpetration: A scoping review. Trauma, Violence, & Abuse, 25(5), 3981–3998. https://doi.org/10.1177/15248380241266137

“); Jacobsen & Simpson, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR20 “Jacobsen, B. N., & Simpson, J. (2024). The tensions of deepfakes. Information, Communication & Society, 27(6), 1095–1109. https://doi.org/10.1080/1369118X.2023.2234980

“)) have emphasized the importance of contextualizing the harms of deepfake pornography on women under the broader framework of image-based sexual abuse (IBSA; e.g., so-called revenge pornography) which is now evolving into AI-IBSA. These voices argue for understanding non-consensual deepfake pornography through the lens of misogyny and sexual violence, instead of treating it as a purely technological problem.

A distinct sub-field of AI research focuses on the implications of AI tools in the context of child sexual exploitation material (CSEM), often referred to as “child pornography.” AI tools are employed both for the creation of such material—including fictional and deepfake CSEM—and for its detection and elimination as well as for the prosecution of those responsible (Steel, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR56 “Steel, C. M. (2024). Artificial intelligence and CSEM - A research agenda. Child Protection and Practice, 2, Article 100043. https://doi.org/10.1016/j.chipro.2024.100043

“); Wolbers et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR64 “Wolbers, H., Cubitt, T., & Cahill, M. J. (2025). Artificial intelligence and child sexual abuse: A rapid evidence assessment. Trends and Issues in Crime and Criminal Justice, 711. https://doi.org/10.52922/ti77802

“)). In 2023, the National Center for Missing and Exploited Children (NCMEC) in the USA received over 4,700 reports involving AI-generated CSEM (NCMEC, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR42 “National Center for Missing & Exploited Children. (2024). Addressing real harm done by deepfakes. https://www.missingkids.org/blog/2024/generative-ai-csam-is-csam#:~:text=In_2023%2C_NCMEC’s_CyberTipline_received,user_of_certain_GAI_platforms

“)). Their report highlights the types of prompts entered into generative AI models to create AI-CSEM. Additionally, a recent analysis found that LAION-5B—the largest publicly available dataset used to train major AI image generators like Stable Diffusion—contains a substantial number of images suspected to be CSEM (Thiel, [2023](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR58 “Thiel, D. (2023). Identifying and eliminating CSAM in generative ML training data and models. Stanford Internet Observatory. https://stacks.stanford.edu/file/druid:kh752sm9123/ml_training_data_csam_report-2023-12-23.pdf

“)).

Beyond non-consensual deepfakery and other unethical uses of AI pornography, some empirical studies have explored consumer preferences and perceptions of erotic AI images versus authentic erotic photographs—finding an anti-AI bias reflected in a preference for authentic erotic imagery (Marini et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR37 “Marini, M., Ansani, A., Demichelis, A., Mancini, G., Paglieri, F., & Viola, M. (2024). Real is the new sexy: The influence of perceived realness on self-reported arousal to sexual visual stimuli. Cognition and Emotion, 38(3), 348–360. https://doi.org/10.1080/02699931.2023.2296581

“)). A survey on attitudes toward fictional synthetic pornography among people with diverse sexual orientations showed more optimistic views among queer individuals who believe that AI pornography could provide more visual diversity in pornography (Kim & Banks, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR23 “Kim, S., & Banks, J. (2024) Expanding experiences and anxieties: gender-identity and sexual-orientation differences in attitudes toward synthetic pornography. Porn Studies. https://doi.org/10.1080/23268743.2024.2400945

“)). However, research on fictional synthetic pornography and on ethical uses of AI pornography remains limited (Döring et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR9 “Döring, N., Le, T. D., Vowels, L. M., Vowels, M. J., & Marcantonio, T. L. (2025). The impact of artificial intelligence on human sexuality: A five-year literature review 2020–2024. Current Sexual Health Reports, 17(1), 4. https://doi.org/10.1007/s11930-024-00397-y

“)).

Current Study

Against this backdrop, the current study aims to explore a broad spectrum of experiences with and opinions about AI pornography. Rather than employing reactive research methods such as interviews or surveys, in which researchers actively elicit participants’ answers, this study uses a non-reactive approach by analyzing experiences with AI pornography as shared organically in public Reddit posts.

Reddit, launched in 2005, was selected for this study due to its status as the largest English language forum platform, hosting 3.5 million forums (called subreddits) and 430 million active users (called Redditors), its diverse user base and tradition of open dialog on sensitive topics, including sexuality and pornography (Rocha-Silva et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR51 “Rocha-Silva, T., Nogueira, C., & Rodrigues, L. (2024). Passive data collection on Reddit: A practical approach. Research Ethics, 20(3), 453–470. https://doi.org/10.1177/17470161231210542

“)). Consequently, researchers have frequently used Reddit to investigate a wide range of sexuality-related experiences, including low libido (Belcher et al., [2023](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR2 “Belcher, R. E., Sim, D., Meykler, M., Owens-Walton, J., Hassan, N., Rubin, R. S., & Malik, R. D. (2023). A qualitative analysis of female Reddit users’ experiences with low libido: How do women perceive their changes in sexual desire? Journal of Sexual Medicine, 20(3), 287–297. https://doi.org/10.1093/jsxmed/qdac045

“)), sex work (Makbul, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR35 “Makbul, N. E., Zannat, R., & Hale, B. J. (2024). Communicating sex work online: A content analysis of client and provider discourse in r/sexworkers. Journal of Sex Research, 61(7), 1050–1061. https://doi.org/10.1080/00224499.2023.2255180

“)), erotic role-play with AI chatbots (Hanson & Bolthouse, [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR17 “Hanson, K. R., & Bolthouse, H. (2024). “Replika removing erotic role-play is like grand theft auto removing guns or cars”: Reddit discourse on artificial intelligence chatbots and sexual technologies. Socius: Sociological Research for a Dynamic World, 10, Article 23780231241259627. https://doi.org/10.1177/23780231241259627

“)), problematic pornography use (Chasioti & Binnie, [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR5 “Chasioti, D., & Binnie, J. (2021). Exploring the etiological pathways of problematic pornography use in NoFap/PornFree rebooting communities: A critical narrative analysis of internet forum data. Archives of Sexual Behavior, 50(5), 2227–2243. https://doi.org/10.1007/s10508-021-01930-z

“)), and deepfakes including pornographic ones (Gamage et al., [2022](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR13 “Gamage, D., Ghasiya, P., Bonagiri, V., Whiting, M. E., & Sasahara, K. (2022). Are deepfakes concerning? Analyzing conversations of deepfakes on Reddit and exploring societal implications. In CHI ‘22, Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1–19). Association for Computing Machinery. https://doi.org/10.1145/3491102.3517446

“)).

Reddit has a significant historical connection to the topic of AI pornography (for an overview see Miller et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR41 “Miller, D. J., Somoray, K., & Stevens, H. (2025). A shallow history of deepfakes. SSRN. https://doi.org/10.2139/ssrn.5130379

“)): In 2017 and 2018, notorious yet unknown Redditors named “deepfakes” and “deepfaceapp” published the first deepfake pornography content and the first deepfake tool on the platform, respectively. During this time, the subreddit r/deepfakes also emerged, but was later banned by Reddit in 2018 for ethical and legal reasons (Reddit, n.d.). This ban prompted the deepfake community to migrate to other forum platforms (e.g., GitHub) and establish dedicated websites such as MrDeepfakes.com (Han et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR16 “Han, C., Li, A., Kumar, D., & Durumeric, Z. (2024). Characterizing the MrDeepFakes sexual deepfake marketplace. https://doi.org/10.48550/ARXIV.2410.11100

“); Timmerman et al., [2023](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR59 “Timmerman, B., Mehta, P., Deb, P., Gallagher, K., Dolan-Gavitt, B., Garg, S., & Greenstadt, R. (2023). Studying the online deepfake community. Journal of Online Trust and Safety, 2. https://doi.org/10.54501/jots.v2i1.126

“)). Despite the ban of r/deepfakes, both unethical and ethical activities related to AI pornography have continued to be prominent topics of discussion on Reddit.

Experiences with AI pornography are complex and multifaceted, encompassing technological, economic, criminological, psychological, sociological, educational, and sexological aspects (Döring et al., [2025](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR9 “Döring, N., Le, T. D., Vowels, L. M., Vowels, M. J., & Marcantonio, T. L. (2025). The impact of artificial intelligence on human sexuality: A five-year literature review 2020–2024. Current Sexual Health Reports, 17(1), 4. https://doi.org/10.1007/s11930-024-00397-y

“)). In this study, we adopted a communication process model that traces the flow of media engagement—from the production process (1), to the characteristics of the produced content (2), to its use (3), ultimately to its effects (4), and ethical–legal implications (5) (Lasswell, 1948; Sapienza et al., [2015](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR53 “Sapienza, Z. S., Iyer, N., & Veenstra, A. S. (2015). Reading Lasswell’s model of communication backward: Three scholarly misconceptions. Mass Communication and Society, 18(5), 599–622. https://doi.org/10.1080/15205436.2015.1063666

“)). This model provides a framework for structuring experiences and engagement with AI pornography as a specific type of media content across the five model dimensions, leading to five research questions (RQ): How do Redditors describe their experiences related to the production (RQ1), content (RQ2), use (RQ3), effects (RQ4), and ethical–legal implications (RQ5) of AI pornography?

Method

The current study utilized a manual quantitative content analysis (Krippendorff, 2018; Neudendorf, 2016) to examine Reddit posts describing experiences with AI pornography.

Research Ethics

Within the expanding field of Reddit research, which primarily relies on manual or automated analyses of Reddit content, two distinct approaches to research ethics have emerged. These can be understood as the public domain approach versus the user-centered approach (Hintz & Betts, [2022](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR19 “Hintz, E. A., & Betts, T. (2022). Reddit in communication research: Current status, future directions and best practices. Annals of the International Communication Association, 46(2), 116–133. https://doi.org/10.1080/23808985.2022.2064325

“); Proferes et al., [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR49 “Proferes, N., Jones, N., Gilbert, S., Fiesler, C., & Zimmer, M. (2021). Studying Reddit: A systematic overview of disciplines, approaches, methods, and ethics. Social Media + Society, 7(2), Article 20563051211019004. https://doi.org/10.1177/20563051211019004

“); Rocha-Silva et al., [2024](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR51 “Rocha-Silva, T., Nogueira, C., & Rodrigues, L. (2024). Passive data collection on Reddit: A practical approach. Research Ethics, 20(3), 453–470. https://doi.org/10.1177/17470161231210542

“)).

The public domain approach explicitly or implicitly argues that Reddit content can be treated as public domain material, freely useable by researchers without the need for review or approval by ethics bodies. The rationale behind this approach is twofold: (1) Redditors have actively published their content on the platform, which is interpreted as implicit consent for public assessment, including scientific analysis and (2) Redditors commonly employ pseudonymous usernames which is seen as a safeguard against personal accountability and potential harm from scientific analysis. A research review found that, among the k = 727 Reddit studies published between 2010 and 2020, the vast majority (86.1%) did not report any ethics body approval; furthermore, over a quarter (28.5%) included direct quotes from Reddit material, and 9.4% even mentioned actual Reddit usernames without having obtained user consent (Proferes et al., [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR49 “Proferes, N., Jones, N., Gilbert, S., Fiesler, C., & Zimmer, M. (2021). Studying Reddit: A systematic overview of disciplines, approaches, methods, and ethics. Social Media + Society, 7(2), Article 20563051211019004. https://doi.org/10.1177/20563051211019004

“), p. 8).

The user-centered approach critiques the public domain position, cautioning that Reddit research can draw unwanted attention to certain Reddit content and its creators, potentially leading to negative consequences such as harassment, public shaming, de-anonymization, and even legal prosecution. To mitigate these risks, the user-centered approach advocates for additional protective measures, particularly when analyzing sensitive Reddit content. According to this approach, researchers should avoid mentioning Reddit usernames or including verbatim quotes (that could be easily searched). Instead, only paraphrased or modified quotes should be used, ensuring that the original Reddit content and related users cannot be traced (at least not as easily). The approach argues that explicit, informed consent from Redditors in question should be obtained before using Reddit usernames or verbatim quotes in research. The review of the k = 727 previous Reddit studies showed that this user-centered approach is primarily implemented by avoiding direct quotes from Reddit material (69.1%); rarely did researchers use paraphrased/modified quotes (2.5%; Proferes et al., [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR49 “Proferes, N., Jones, N., Gilbert, S., Fiesler, C., & Zimmer, M. (2021). Studying Reddit: A systematic overview of disciplines, approaches, methods, and ethics. Social Media + Society, 7(2), Article 20563051211019004. https://doi.org/10.1177/20563051211019004

“), p. 9).

In the current study, we adhere to a user-centered ethical approach: We obtained approval from the Ethical Committee of Technische Universität Ilmenau. To protect Redditors’ privacy, we do not mention Reddit usernames or provide verbatim quotes from Reddit posts. Instead, we report only modified quotes that preserve the original meaning and sentiment while preventing traceability. Quotes were adjusted solely for reporting purposes; data analysis was conducted using the original text material. The original quotes were modified with the help of ChatGPT-4 (prompt “rephrase: [quote]”) and subsequently edited by the first author, who also verified non-traceability. To further protect Redditors’ privacy, we sampled Reddit posts from a wide range of subreddits, mitigating the ethical concerns about exposing specific subreddits or their members (Proferes et al., [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR49 “Proferes, N., Jones, N., Gilbert, S., Fiesler, C., & Zimmer, M. (2021). Studying Reddit: A systematic overview of disciplines, approaches, methods, and ethics. Social Media + Society, 7(2), Article 20563051211019004. https://doi.org/10.1177/20563051211019004

“), p. 11).

To further protect user privacy, we have not publicly shared our data file containing links to the analyzed Reddit posts. Access to the data is granted only upon reasonable request from fellow researchers and under strict conditions of confidentiality. While the need to protect Redditors prevents us from adopting an open data and open analysis approach for this study, we adhere to an open materials approach and have publicly shared our codebook below.

In the evolving field of Reddit research and ethics, the importance of giving back to the community is emphasized (Proferes et al., [2021](https://link.springer.com/article/10.1007/s10508-025-03227-x#ref-CR49 “Proferes, N., Jones, N., Gilbert, S., Fiesler, C., & Zimmer, M. (2021). Studying Reddit: A systematic overview of disciplines, approaches, methods, and ethics. Social Media + Society, 7(2), Article 20563051211019004. https://doi.org/10.1177/20563051211019004

“), p. 11). Researchers extracting data from Reddit forums are encouraged to share their findings with the respective communities, where feasible. However, as we extracted posts from over 150 different subreddits, sharing results with all these forums would constitute spamming. Instead, we have published this article open-access, explicitly mentioning Reddit in the paper title to ensure that Redditors interested in Reddit-related research can easily access our findings.

Sample

Our aim was to sample all publicly accessible Reddit posts describing experiences with AI-generated pornography as of August 2024. Typically, a Reddit post (also initial post) introduces a topic and invites other Redditors to comment. The initial post, along with its comments, forms a Reddit thread that examines the topic from various perspectives. We focused exclusively on initial Reddit posts to prioritize users’ primary, self-initiated perspectives without the influence of ongoing dialog or group dynamics. Initial posts often reflect a user’s core message or concern and offer a consistent unit of analysis across threads. However, we acknowledge that Reddit’s interactive nature means comments within threads may offer important dialogic dynamics—especially in understanding community responses and evolving discourse. These aspects were beyond the scope of the current study, though.

We manually extracted relevant posts from Reddit using the platform’s search function. To identify these posts, we applied 13 different pretested search terms and three filters, along with three inclusion and five exclusion criteria. Details on the sampling process are provided in Table 1.

The final sample consisted of N = 390 public Reddit posts describing experiences with and opinions about AI-generated pornography (see Table 2). These posts were published between 2016 and 2024 across 169 different subreddits, dedicated to various topics such as technology, pornography, sexuality, dating, fandom, life advice, legal advice, and gender relations. Subreddit names are not specified here to