## 3 Initial Results
### The Pathways--A Layered Implementation Strategy for the CF-BIAI-SXT Framework  
For the framework to be usable, apart from regulatory elements, technical and organizational preconditions must be met, alongside proper risk mitigation, adequate governance, and interoperability. Thus, we have three layers to consider for proper implementations: Technical Enablement, Governance and Stakeholder Alignment, and Trust and Oversight. The intersections of these dimensions, often creating design trade-offs -such as between transparency and computational efficiency, or between decentralization and scalability--must be properly tackled by governance issues and risk mitigation to ensure implementation success. 3.1 The Technical Enablement Layer (What Infrastructure Is Needed for the System to Work in Practice?) This foundational layer ensures that privacy, scalability, and interoperability are embedded by design. It allows the BIAI system to operate effectively across jurisdictions and sensitive use cases. Key elements to be considered are trust-by-design and local data retention are crucial for mitigating sextortion. Blockchain systems must record all AI-critical activities (such as model training, inference decisions, and data access) on immutable ledgers, guaranteeing verifiability, supporting post hoc auditing, and ensuring accountability, thus mitigating the risk of norm violations. Smart contracts can encode procedures for rule enforcement, compensation, and conflict resolution, reducing reliance on intermediaries and strengthening procedural fairness. Continuous system monitoring, through log review, performance audits, and advanced diagnostic tools using techniques like noise-aware sparse Gaussian processes and edge-AI analytics, may further enhance predictive accuracy and system responsiveness in real-time [142; 143]. For example, the findings of [144] show that blockchain and AI in combination improve surveillance and tracking capabilities by ensuring detailed, secure, and immutable records of all transactions. A series of key technical considerations for deploying BIAI systems in real-world, cross-jurisdictional contexts are summarized in Table A4 in Appendix C. These include the use of federated learning, privacy-preserving computation (such as ZKPs and homomorphic encryption), and secure digital identities. In addition, also to be considered is the case of lower-resource jurisdictions (from which a significant number of victims emerge), where edge-based implementation may offer an alternative to cloud reliance, but may also require mobile-first or hybrid deployments. 3.2 The Governance and Stakeholder Alignment Layer (Who Runs It, Who Participates, and How Governance Legitimacy Is Ensured?) This governance layer is central in translating the BIAI framework's technical elements into ethical context-aware systems capable of earning public trust. The key element to be considered is the importance of adaptive governance, essential when ethical risks evolve faster than regulation. Additionally, effective governance frameworks are essential for the management of blockchain-integrated AI systems that tackle sexual exploitation issues. Such governance systems also need to be aligned with societal values and regulatory standards to deliver on their desiderate to strengthen societal resilience. Moreover, to properly ensure effective implementation of BIAI, they must fulfill several core functions:  
* Support decentralized decision-making \(\bigcirc\) & Distributed authority prevents centralized abuse and improves transparency in high-risk contexts like sextortion. \(\bigcirc\) & DAO logic enables rule-setting via encoded, consensus-based processes [145]. \(\bullet\) & Integrate diverse stakeholders \(\bigcirc\) & Policymakers, ethicists, technologists, regulators, and victim advocacy groups must collaborate on design and oversight [146]. \(\bigcirc\) & Such inclusion allows for democratic control and societal legitimacy.