## 3 Initial Results
#### 3.1.1 A Systematic Literature Review (SLR) of the Analyzed Concepts  
To fully deploy the SLR part of the exploratory investigation, we searched Scopus, Web of Science, IEEE Explore, and ACM Digital Library using keywords spanning AI, blockchain, and sextortion (2017-2025) and identified 45 candidate publications. We then applied PRISMA 2020 guidelines to our screening process, as illustrated in Figure 19 in Appendix A, which shows the flow of information through identification, screening, and inclusion. As described in the methodology, to enhance the transparency and reproducibility of our literature review and ensure unbiased selection, we used a rigorous, multi-reviewer screening approach. Each author of this paper independently screened the records using the Rayyan platform, a web tool for systematic review management. We included only studies that met all criteria (addressing AI and blockchain in the context of digital sexual exploitation with an ethics focus) and excluded others (see Appendix A for detailed criteria). To ensure that we keep the SLR as intended, at the intersection of AI, blockchain, ethics, and sextortion, we used Boolean logic in the search terms and presented them in Appendix A. Thus, in our systematic review, we included only sources that: (1) integrate AI and blockchain (technologies relevant to our research question); (2) focus on digital sexual exploitation (e.g., sextortion contexts); and (3) address ethical considerations (such as fairness, transparency, or privacy in AI use). Studies that failed to meet any of these criteria were excluded. For instance, we omitted works with no AI or no blockchain component (16 articles), those unrelated to sextortion or digital abuse (12 articles), and those lacking any AI ethics dimension (11 articles). By using the defined search for the period 2017-2025, we find the following literature results:  
* Scopus identified 6 papers from 2019 onwards, with 1 being a false report--5 articles;
* Web of Science returned 0 results (even without a period range);
* IEEE Explore returned 0 results (even without a period range);
* ACM Digital Library returned 55 results for the period 2017-2025 without defining the search by timeframe; therefore, we can identify two brief conclusions: those are all articles on the defined topic from the database and the chosen timeframe is valid. * Although we initially excluded Arvix from the search, we nonetheless tried the query on this database as well and received 0 results. Similarly, Semantic Scholar returned 0 results for the same Boolean logic. The limited number of relevant results may reflect a disciplinary/research dissemination skew caused by the fact that these databases tend to emphasize either highly technical implementations or formal computer science publications, with less coverage of interdisciplinary studies addressing ethics, governance, or social impact. It highlights a lack of holistic handling of macro issues with societal impacts by incentivizing researchers to focus on narrow issues, more suitable for publication. Moreover, the tight Boolean logic using AND operators may have narrowed retrieval too far for broader-indexing platforms. This limitation is to be mitigated by the supplementary SLR, as will be described further in this section. We screened the 60 articles for duplicates and identified that ACM proposes both the Proceedings and the article in case there is a match, so we retained in the analysis just the article. This leads to retaining in the analysis only 40 references from the ACM Library. We applied the PRISMA methodology of literature review for the found articles (45 in total--5 from Scopus and 40 from ACM, all in English and peer-reviewed. See full list in Appendix B) and proceeded with a screening based on the inclusion/exclusion criteria detailed in Appendix A.