Data protection and privacy in the context of emerging technologies
DOI:
https://doi.org/10.5281/Keywords:
personal data protection, digital privacy, emerging technologies, informed consent, artificial intelligence, neurotechnologyAbstract
This study analyzed the challenges faced by traditional personal data protection mechanisms in the face of the advances of emerging technologies such as artificial intelligence, the Internet of Things, and neurotechnology. The objective was to examine the relationship between regulatory awareness, risk perception, and institutional practices related to data processing. To this end, a quantitative methodology was applied through a structured survey with a stratified sample of digital technology users. The data were analyzed using descriptive and inferential statistical techniques. The results showed a direct correlation between regulatory awareness and perceptions of digital security and a critical outlook among users with greater technological exposure. A gap was also identified between declared institutional policies and their actual implementation. The analysis allowed for the segmentation of user profiles and highlighted the need for more effective consent mechanisms, algorithmic auditing, and digital education. The conclusion was that adopting a comprehensive approach that articulates technological innovation, dynamic regulation, and citizen empowerment is essential to build digital governance based on protecting fundamental rights.
Downloads
References
AEPD. (2024). Innovación y Tecnología. Agencia Española de Protección de Datos. https://www.aepd.es/areas-de-actuacion/innovacion-y-tecnologia
Dhinakaran, D., Udhaya Sankar, S. M., Selvaraj, D., & Edwin Raja, S. (2024). Privacy-preserving data in IoT-based cloud systems: A comprehensive survey with AI integration. arXiv preprint. https://arxiv.org/abs/2401.00794
Ehimuan, B., Chimezie, O., Akagha, O. V., Reis, O., & Oguejiofor, B. B. (2024). Global data privacy laws: A critical review of technology’s impact on user rights. World Journal of Advanced Research and Reviews, 21(2), 1058-1070. https://doi.org/10.30574/wjarr.2024.21.2.0369
García, R. D., Ramachandran, G., Dunnett, K., Jurdak, R., Ranieri, C., Krishnamachari, B., & Ueyama, J. (2024). A survey of blockchain-based privacy applications: An analysis of consent management and self-sovereign identity approaches. ACM. https://arxiv.org/abs/2411.16404
Kablo, E., & Arias-Cabarcos, P. (2023). Privacidad en la era de la neurotecnología. In Proceedings of the 2023 ACM SIGSAC Conference. https://doi.org/10.1145/3576915.3623164
Magee, P., Ienca, M., & Farahany, N. (2024). Beyond neural data: Cognitive biometrics and mental privacy. Neuron, 112. https://doi.org/10.1016/j.neuron.2024.09.004
Mansfield, K. L. (2025). Un estudio señala los peligros que supone la IA para la salud mental de niños y adolescentes. The Lancet. https://elpais.com/ciencia/2025-01-21/un-estudio-senala-los-peligros-quesupone-la-iapara-la-salud-entalde-ninos-y-adolescentes.html
Mendoza, A., & Enríquez, L. (2024). Desafíos del derecho a la protección de datos personales en la era digital. Instituto de Transparencia, Acceso a la Información Pública, Protección de Datos Personales y Rendición de Cuentas de la Ciudad de México. https://www.infocdmx.org.mx/images/biblioteca/2024/DesafiosDerecho-PDP_EraDigital.pdf
Pinto, G. P., Donta, P. K., Dustdar, S., & Prazeres, C. (2024). A systematic review on privacy-aware IoT personal data stores. Sensors, 24(2197). https://doi.org/10.3390/s24072197
Rachut, S., & Maurer, J. W. (2024). Altruismo de datos en el marco del Reglamento Europeo de Gobernanza de Datos, ¿un acierto o mejorable? Revista de Derecho Comunitario Europeo, 78, 183-213. https://recyt.fecyt.es/index.php/RDCE/article/view/107334/79601
Wang, Y., Su, Z., Zhang, N., Xing, R., Liu, D., Luan, T. H., & Shen, X. (2022). A survey on metaverse: Fundamentals, security, and privacy. arXiv preprint. https://arxiv.org/abs/2203.02662
Xia, K., Duch, W., Sun, Y., Xu, K., Fang, W., Luo, H., Zhang, Y., Sang, D., Xu, X., Wang, F-Y., & Wu, D. (2024). Privacy-preserving brain-computer interfaces: A systematic review. arXiv preprint. https://arxiv.org/abs/2412.11394
Yang, L., Tian, M., Xin, D., Cheng, Q., & Zheng, J. (2024). AI-driven anonymization: Protecting personal data privacy while leveraging machine learning. arXiv preprint. https://arxiv.org/abs/2402.17191
Zhu, R., Wang, M., Zhang, X., & Peng, X. (2023). Investigation of personal data protection mechanism based on blockchain technology. Scientific Reports, 13, 21918. https://doi.org/10.1038/s41598-023-48661-w
Published
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Issue
Section
License
Copyright (c) 2025 Angélica M. Hernández (Author)

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.