## 5 Conclusions
Therefore, one cannot yet claim the scalability, efficiency, and real-world governance effect of the CF-BIAI-SXT design are given. Second, despite us having abstracted out crucial architectural building blocks such as federated learning, ZKP systems, and smart-contract-based consent governance, we are yet to define these at an implementation level. No performance benchmarks, latency analysis, and throughput comparisons are found in the position paper. In addition, implementation trade-offs have not been quantified, e.g., storage overhead, blockchain energy, and cross-jurisdictional synchronization, which are the scope of further studies. Third, the approach accepts but leaves unresolved legal frictions such as the tension between blockchain immutability and the GDPR's \"right to be forgotten.\" While potential design patterns such as off-chain storage or revocation registries are well-known, these have not been incorporated or tested within the current model. Legal-technical co-design is emphasized as a future line of work. Fourth, the principles of \"privacy-first\" and \"societal resilience\" are taken as axiomatic essentials rather than instruments for the measurability of a system. Better understanding how to translate such dimensions into actual evaluative numbers, such as consent traceability, fairness scores, and resilience metrics, would greatly enhance the practical utility and impact of the framework. Fifth, although the current paper builds on a rich body of scholarly and gray literature, the central intersection of AI, the blockchain, and sextortion is topical and undertherized in empirical research. This is supported by the low number of eligible articles from the systematic literature review, which is further supported by the need for a narrative synthesis. For a position paper, this deficit is acceptable, while on the other hand, such restrictiveness undermines the generalization and reproducibility of the findings. Furthermore, a validation stemming from survivor-centered design and participatory prototyping would also enhance the CF-BIAI-SXT framework. If technologies are to be both socially attuned and grounded in the real world, they will need, and must incorporate, the feedback of affected stakeholders, from civil society, including NGOs, victims' advocates, and legal experts. Validation of this framework will involve proof of concept (PoC) development of a blockchain-integrated AI application that mitigates sexual exploitation. This PoC development will potentially face technical challenges associated with complex systems development and integration, including integration complexity, scalability, and interoperability challenges. Future research imperativesFurther research is required to better understand the long-term effects of BIAI systems on societal behaviors and norms. Furthermore, up-to-date policy development is necessary to keep up with technological advances. For future work, it is important to perform an impact assessment and evaluation of the positions, concepts, and models proposed in this paper. This includes PoC demonstrations for various cases of BIAI applications that address social issues. Additional criteria for the evaluation of these developed PoCs include, as previously mentioned in our framework, ethical and regulatory benefits, technological advances, and AI for social good. The PoC implementation will adopt strategies to limit technical challenges associated with the development and integration of complex systems through modular architecture design and implementation that allows independent development and testing of various components that make up the system. The technology choices for the implementation will focus on blockchain stacks that have already demonstrated stable integration with external entities such as AI components and algorithms. Future research should also explore further improvement options for societal resilience via the integration of blockchain technologies and AI interdisciplinary collaboration between technologists, ethicists, and policymakers.