## 5 Conclusions  
Blockchain and AI integration represent a transformative step toward addressing complex societal and technological challenges, especially when used in addressing sexual exploitation. Practical applications such as using federated learning for sextortion mitigation and blockchain-audited AI decision-making demonstrate the potential for these technologies to align with ethical governance while solving real-world problems. In this paper, we are tackling this literature gap, identified through both related work analyses as well as a systematic literature review, by proposing a privacy-first, societal-resilience-oriented conceptual framework. Specifically, we investigated to what extent decentralized immutable traceability strengthens AI systems by addressing the ethical issues inherent in them. Since new Internet-based technology builds on previous ones to support social and economic activities, and thus positive societal evolution, the future of the Internet must be inextricably tied to the ethical design of its enabling technologies. This article positions the CF-BIAI-SXT framework in the context of established AI ethics guidelines (such as the EU's High-Level Expert Group on AI proposal from 2019 of Ethics Guidelines for Trustworthy Artificial Intelligence or, from the same year, the OECD AI Principles), as presented in Section 3. The ethical gaps and solutions identified in our sextortion case study directly relate to principles of trustworthy AI and, hence, reinforce the idea that the CF-BIAI-SXT framework is designed to uphold the core values deemed essential for socially responsible AI deployment. To conclude, our position paper highlights the potential of integrating AI and blockchain technologies to combat this ever-growing digital threat that is increasing for vulnerable societal categories, such as minors. In a multi-layered approach, we suggest using AI for the early detection of sextortion attempts and providing immediate support to victims, while blockchain ensures secure, anonymous reporting and evidence storage. We also correlate blockchain's transparency with increased trust in AI systems, which is crucial when handling sensitive issues. The study indicates that this technological integration can enhance privacy and data control for users, key factors in sextortion prevention; thus, we propose using smart contracts for secure case management and evidence collection. Overall, our findings suggest that combining AI and blockchain can significantly strengthen societal resilience against sextortion by empowering victims and supporting law enforcement efforts. Ethical and governance risks:Nonetheless, as previously stated, there is a significant literature gap in empirical studies, with the goal of using AI to support societal resilience \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Principle** & **Metric** & **Definition** & **Evaluation Method** & **Target Threshold** \\ \hline Privacy-first & Data Minimization & Proportion of user data retained & Logging AI queries & \textless{}0.10 \\  & Ratio & vs. total data accessed & and ZKP audit trails & \\ \hline Privacy-first & Consent & \% of data operations traceable to & Smart contract-based & \textless{}0.10\% \\  & Auditability & explicit user consent & data wallet logs & 100\% \\ \hline Societal & System & \% of system functions available & Network simulation & \textless{}90\% \\ resilience & Accessibility Index & in low-bandwidth environments & and fallback logs & \\ \hline Societal & Governance & Ratio of system decisions made & Smart contract vote & \textless{}75\% \\ resilience & Inclusiveness Score & \multicolumn{2}{c}{controlled override} & \multicolumn{2}{c}{audit logs} \\ \hline Societal & Abuse Detection & Time from abuse-report trigger & AI + blockchain & \\ resilience & Latency & to flagging response & event log & \textless{}5 min \\  & & comparison & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Operational Metrics for Evaluating “Privacy-First” and “Societal Resilience” Principles.