## 5 Conclusions
thus hindered by a series of challenges researchers encounter when addressing this topic (sextortion), such as:  
* _Limited Empirical Research at Risk of Obsolescence_: As both the AI-sextortion and blockchain-sextortion areas are in their infancy, empirical research remains very limited. Only a few studies deal with the use of AI (or blockchain) to detect, prevent, or mitigate the phenomenon, and even fewer focus on the nexus of the three concepts. This lack of transdisciplinary research holds back technology from having direct applicability in solving social problems and may have major implications in the long run. Studies might become obsolete or irrelevant as the time needed for academic research can be excessively long compared to the speedy pace of technological changes. * _Interdisciplinary Complexity_: Apart from the two technologies considered, aspects related to psychology, sociology, anthropology, ethics, law, and economics must be integrated to gain a clear perspective and propose potential solutions. For this, we used two versions of reviews (a systematic and a narrative) and included a flow diagram and code protocols in Appendix A to facilitate independent verification of both. * _Data Use and Sensitivity_: Extensive exploitation of data for educating AI or carrying out research is hindered by its sensitive nature, posing potential harm to victims, its distribution across multiple jurisdictions and platforms, in addition to the numerous ethical clearances needed from different local and global organizations. This international perspective is also affected by distinct legal and regulatory frameworks, leading to the inability to propose shared policies or resolutions. However, this is also the stage in which, as [PERSON] [156] mentions in his famous dilemma, society must intervene to ensure that a specific technology is safely deployed and is a solution, not a threat. Sextortion serves as a relevant example of this intersection. Both users and stakeholders need to understand well the ethical implications of BIAI systems by integrating extensive educational measures that are part of an integrated, comprehensive governance framework. These measures must always contain very clear information about the detailed use of data, the important AI decision-making processes, and the vital role of blockchain technologies that ensure transparency and security. Always encouraging a highly responsible use of BIAI systems with better informed consent requires the promotion of sophisticated ethical knowledge among users. Thus, a better and well-matched alignment of such complex systems with their related societal expectations and additional ethical standards can be achieved when a properly informed user base exists. However, we emphasize the need for careful ethical considerations in the implementation of these technologies to ensure they do not inadvertently cause harm or infringe on individual privacy rights. The essential imperative is to ensure that human rights are upheld and individual justice is promoted whenever blockchain technologies and AI are deployed together. _Limitations and research gaps_: This position paper introduces the CF-BIAI-SXT architecture as a conceptual combination of blockchain and artificial intelligence toward ethical governance on high-risk AI applications, and more specifically for the prevention of sextortion. Even though the interdisciplinary approach and methodological framework are based on a systematic and narrative review, a number of limitations need to be considered, and avenues for further research and validation need to be stressed. There are two reasons for this: First, empirical validation of the proposed framework is missing. The BPMN models do not provide active workflow instances, rather are conceptual abstractions, and the lack of simulation, prototype implementation, or evaluation is a shortcoming to the applicability and performance of the framework under operational conditions.