## 3 Initial Results
#### 3.1.2 A Narrative Conceptual Exploration
We examined the literature articles [38; 39; 40; 43; 44] in Table 2 to identify social media platforms, chatting platforms, dating websites, and virtual reality platforms where sexual exploitation activities are prevalent. The findings [38] show that mobile apps emphasize psychological impacts, but fail to differentiate between platform-specific risks, highlighting a critical gap when designing technological countermeasures. The broader categorization of platforms from [43] offers more nuanced insights into how different technological environments create unique exploitation opportunities, suggesting that a one-size-fits-all mitigation approach is insufficient. These platforms enable criminals to stalk, coerce, threaten, and harass victims into sharing sexually explicit images and videos. Social media platforms also provide grooming channels to lure victims into various romance scams. These explicit images are then stored on cloud services, web hosting platforms, and other file hosting services to extort the victims, thereby resulting in sextortion cases. Extortion of victims has several health implications, such as psychological, emotional, and financial, which can lead to depression, self-harm, and, in the worst cases, result in suicide. In this context, a case study on sextortion as a form of cyber abuse and growing societal concern, particularly in the case of young people and/or minors, can be a niche illustration of the ethical challenges of AI. Efforts to combat this cybercrime may benefit from the use of AI [3; 45], while some countries (Indonesia, for example) are setting regulatory frameworks in place to deal with sexual violence crimes, including sextortion (the TPKS law of 2022 [46]). On the opposite side of the spectrum, AI can be shown to leverage the sextortion efforts of perpetrators through dating apps [47] or deepfakes [4]. Despite timid advances in the topic, both in the literature and in regulatory and legal frameworks, the significant gap in empirical studies demonstrating the effectiveness of technological solutions (AI or other) in preventing and mitigating sextortion has yet to be addressed. This empirical gap stems from both methodological challenges in studying sensitive populations and the rapid evolution of digital technologies that outpace traditional research timelines. Furthermore, existing studies often focus on technical detection without adequately addressing the ethical dimensions of AI deployment in these contexts. The manner in which these identified technological enablers of sextortion highlight how centralized data storage and insufficient user control over intimate content create exploitation vulnerabilities directly informs our framework's focus on decentralized control and enhanced privacy mechanisms. Secondly, we identify the dual-use roles of AI in preventing and countering sexual exploitation on digital platforms and the potential ethical issues in automated AI systems. AI plays a role both in enabling and mitigating sexual exploitations that lead to sextortion cases. Even when AI is applied to help prevent sexual exploitation through various automated algorithms, there are also ethical concerns about the use and misuse of personal data. In Table 3, we analyzed the following related articles [3; 4; 17; 18; 19; 49; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 70] to identify the roles of AI in enabling and mitigating sexual exploitation and collect the list of ethical concerns that are raised when AI is applied to address sexual exploitation problems. The role of AI in enabling sexual exploitation mostly involves the alteration of images and video