AI and Telecommunication Privacy
Rethinking Legal Protections against Algorithmic Surveillance
DOI:
https://doi.org/10.26512/lstr.v17i2.57121Keywords:
Artificial Intelligence, Surveillance, Ethics, Privacy, Technology, Society, Data.Abstract
[Purpose] This paper explores how artificial intelligence (AI) can aid in the integration of telecommunication networks, and how it will affect privacy. It talks about the threats that AI brings to consumer privacy, such as algorithmic monitors that are challenging and explain what does and doesn’t seem to be working to protect consumer privacy in present legislation. The purpose is to study the integration of AI and telecommunication data privacy to find that there is a need to have new set of laws and weighty privacy protection in this age of digital transformation.
[Methodology/approach/design] The paper critically analyses historical interactions of AI with telecommunication privacy, discusses how existing policies work and what gaps exist in current legislation. Examining the validity of such risks in telecommunication networks when it comes to privacy violation, data exploitation, and the need for clear regulations of the system. Moreover, the methodology proposes an interdisciplinary approach comprised of legal, technological, and ethical stakeholders to handle the problems in question.
[Findings] And finally, the paper concludes that the existing legal frameworks cannot secure privacy of consumer in the framework of AI-based telecommunication systems. That is why it emphasizes the need for international privacy standards, independent audits and robust national regulatory bodies. It calls for new legal guidelines that would guarantee transparency, responsibility and consumer consent as well as foster collaboration among the different stakeholders to improve privacy protection and data control in AI systems.
[Practical implications] The paper parallels strong privacy protections and ethical practices of AI in telecommunication systems. It calls for new legal and international standards of privacy. The intention behind these recommendations is to maintain the privacy and control of the consumer’s data within AI powered systems.
[Originality/value] Finally, this research uniquely combines legal, technological, and ethical aspects of litigation involving AI and privacy in telecommunications all into one. It draws the gaps in the existing laws and provides innovative solutions for privacy protection. The modern concern addressed by the paper is privacy, and the value of the paper is in the interdisciplinary approach it uses to address that specific concern.
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Agubor, C. K., Chukwudebe, G. A., & Nosiri, O. C. (2015). Security challenges to telecommunication networks: An overview of threats and preventive strategies. Proceedings of the 2015 International Conference on Cyberspace (CYBER-Abuja), Abuja, Nigeria, 124–129. https://doi.org/10.1109/CYBER-Abuja.2015.7360500
Akram, N., Dagdeviren, Z. A., Akram, V., Dagdeviren, O., & Challenger, M. (2021). Design and implementation of asset tracking system based on Internet of Things. 2021 7th International Conference on Electrical, Electronics and Information Engineering (ICEEIE), 366–371. https://doi.org/10.1109/ICEEIE52663.2021.9616667
Alhammadi, A., Shayea, I., El-Saleh, A. A., Azmi, M. H., Ismail, Z. H., Kouhalvandi, L., & Saad, S. A. (2024). Artificial intelligence in 6G wireless networks: Opportunities, applications, and challenges. International Journal of Intelligent Systems, 2024, 8845070. https://doi.org/10.1155/2024/8845070
Ali, S., Wang, J., & Leung, V. C. M. (2025). AI-driven fusion with cybersecurity: Exploring current trends, advanced techniques, future directions, and policy implications for evolving paradigms– A comprehensive review. Information Fusion, 118, 102922. https://doi.org/10.1016/j.inffus.2024.102922
Balmer, R. E., Levin, S. L., & Schmidt, S. (2020). Artificial intelligence applications in telecommunications and other network industries. Telecommunications Policy, 44(6), 101977. https://doi.org/10.1016/j.telpol.2020.101977
Bélanger, F., & Crossler, R. E. (2011). Privacy in the digital age: A review of information privacy research in information systems. MIS Quarterly, 35(4), 1017–1041. https://doi.org/10.2307/41409971
Brunner, L. (2018). Digital communications and the evolving right to privacy. In M. K. Land & J. D. Aronson (Eds.), New technologies for human rights law and practice (pp. 217–242). Cambridge University Press.
Bygrave, L. A. (1998). Data protection pursuant to the right to privacy in human rights treaties. International Journal of Law and Information Technology, 6(3), 247–284. https://doi.org/10.1093/ijlit/6.3.247
Carvalho, H. E. R. H. de, Freitag, A. E. B., & Santos, D. R. dos. (2022). Impactos da implantação da Lei Geral de Proteção de Dados Pessoais no Brasil: Uma análise bibliométrica [Impacts of the implementation of the General Law for the Protection of Personal Data in Brazil: A bibliometric analysis]. Revista de Gestão e Secretariado, 13(3), 1398–1411. https://doi.org/10.7769/gesec.v13i3.1412
Cuzzocrea, A., & Soufargi, S. (2025). Privacy-preserving multidimensional big data analytics models, methods and techniques: A comprehensive survey. Expert Systems with Applications, 270, 126387. https://doi.org/10.1016/j.eswa.2025.126387
de Almeida, P. G. R., dos Santos, C. D., & Farias, J. S. (2021). Artificial intelligence regulation: A framework for governance. Ethics and Information Technology, 23, 505–525. https://doi.org/10.1007/s10676-021-09593-z
de Carvalho, R. M., Del Prete, C., Martin, Y. S., et al. (2020). Protecting citizens’ personal data and privacy: Joint effort from GDPR EU cluster research projects. SN Computer Science, 1, 217. https://doi.org/10.1007/s42979-020-00218-8
Dev, K., Xiao, Y., Challita, U., de Alwis, C., & Magarini, M. (2023). Guest editorial: Autonomous networks: Opportunities, challenges, and applications. IEEE Communications Standards Magazine, 7(2), 6-7. https://doi.org/10.1109/MCOMSTD.2023.10148968
Dilmaghani, S., Brust, M. R., Danoy, G., Cassagnes, N., Pecero, J., & Bouvry, P. (2019). Privacy and security of big data in AI systems: A research and standards perspective. In Proceedings of the 2019 IEEE International Conference on Big Data (Big Data) (pp. 5737–5743). IEEE. https://doi.org/10.1109/BigData47090.2019.9006283
Edozie, E., Shuaibu, A. N., Sadiq, B. O., et al. (2025). Artificial intelligence advances in anomaly detection for telecom networks. Artificial Intelligence Review, 58, 100. https://doi.org/10.1007/s10462-025-11108-x
El-Hajj, M. (2025). Enhancing communication networks in the new era with artificial intelligence: Techniques, applications, and future directions. Network, 5(1), 1. https://doi.org/10.3390/network5010001
Fanca, A., Puscasiu, A., Gota, D.-I., & Valean, H. (2020). Recommendation systems with machine learning. 2020 21st International Carpathian Control Conference (ICCC), High Tatras, Slovakia, 1–6. https://doi.org/10.1109/ICCC49264.2020.9257290
Fast, N. J., & Jago, A. S. (2020). Privacy matters… or does it? Algorithms, rationalization, and the erosion of concern for privacy. Current Opinion in Psychology, 31, 44–48. https://doi.org/10.1016/j.copsyc.2019.07.011
Filho, A., Santos, A., Rodrigues, I., Vale, L., Vieira, M., Santos, S., & Simas, D. (2024). A proteção de dados pessoais e a Lei Geral de Proteção de Dados (LGPD): limites e desafios na sociedade digital brasileira. Contribuciones a las Ciencias Sociales, 17, e11915. https://doi.org/10.55905/revconv.17n.10-343
Fontes, C., Hohma, E., Corrigan, C. C., & Lütge, C. (2022). AI-powered public surveillance systems: Why we (might) need them and how we want them. Technology in Society, 71, 102137. https://doi.org/10.1016/j.techsoc.2022.102137
Fu, M., Wang, P., Wang, Z., & Li, Z. (2023). Deep learning for network traffic prediction: An overview. In 2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, International Conference on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) (pp. 665–671). IEEE. https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361459
Gorrepati, U., Zavarsky, P., & Ruhl, R. (2021). Privacy protection in LTE and 5G networks. Proceedings of the 2021 2nd International Conference on Secure Cyber Computing and Communications (ICSCCC), Jalandhar, India, 382–387. https://doi.org/10.1109/ICSCCC51823.2021.9478109
Greenleaf, G. (2009). Five years of the APEC privacy framework: Failure or promise? Computer Law & Security Review, 25(1), 28–43. https://doi.org/10.1016/j.clsr.2008.12.002
Guhl, S. D., & Pendse, R. (2008). The Communications Assistance for Law Enforcement Act (CALEA). Journal of Information Technology & Politics, 17(3), 1. https://doi.org/10.1080/19393550802297399
Hill, R. (2014). The 1988 International Telecommunication Regulations. In The new international telecommunication regulations and the Internet. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45416-5_2
Hoofnagle, C. J., van der Sloot, B., & Borgesius, F. Z. (2019). The European Union General Data Protection Regulation: What it is and what it means. Information & Communications Technology Law, 28(1), 65–98. https://doi.org/10.1080/13600834.2019.1573501
Jones, M. L., Kaufman, E., & Edenberg, E. (2018). AI and the ethics of automating consent. IEEE Security & Privacy, 16(3), 64–72. https://doi.org/10.1109/MSP.2018.2701155
Jungherr, A. (2023). Artificial intelligence and democracy: A conceptual framework. Social Media + Society, 9(3). https://doi.org/10.1177/20563051231186353
Kabay, M. E. (2003). Crime, use of computers in. In H. Bidgoli (Ed.), Encyclopedia of Information Systems (pp. 345–363). Elsevier. https://doi.org/10.1016/B0-12-227240-4/00023-X
Kastouni, M. Z., & Ait Lahcen, A. (2022). Big data analytics in telecommunications: Governance, architecture and use cases. Journal of King Saud University - Computer and Information Sciences, 34(6, Part A), 2758-2770. https://doi.org/10.1016/j.jksuci.2020.11.024
Khan, M. (2023). AI-enabled transformations in the telecommunications industry. Telecommunication Systems, 82(1–2), 1–2. https://doi.org/10.1007/s11235-022-00989-w
Lakhani, S. (2024). Bridging law and technology: Navigating policy challenges. International Review of Law, Computers & Technology, 1(3). https://doi.org/10.1080/13600869.2024.2364987
Li, M., Huo, M., Cheng, X., & Xu, L. (2020). Research and application of AI in 5G network operation and maintenance. Proceedings of the 2020 IEEE International Conference on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), Exeter, United Kingdom, 1420–1425. https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom51426.2020.00212
Lyon, D. (2014). Surveillance, Snowden, and Big Data: Capacities, consequences, critique. Big Data & Society, 1(2). https://doi.org/10.1177/2053951714541861
Machado, H., Silva, S., & Neiva, L. (2023). Publics’ views on ethical challenges of artificial intelligence: A scoping review. AI Ethics. https://doi.org/10.1007/s43681-023-00387-1
Mao, Y., Pranolo, A., Hernandez, L., Wibawa, A. P., & Nuryana, Z. (2022). Artificial intelligence in mobile communication: A survey. IOP Conference Series: Materials Science and Engineering, 1212(1), 012046. https://doi.org/10.1088/1757-899X/1212/1/012046
Mattoo, A., & Meltzer, J. P. (2018). International data flows and privacy: The conflict and its resolution. Journal of International Economic Law, 21(4), 769–789. https://doi.org/10.1093/jiel/jgy044
Moussawi, S., Deng, X. (N.), & Joshi, K. D. (2024). AI and discrimination: Sources of algorithmic biases. Communications of the ACM, 55(4). https://doi.org/10.1145/3701613.3701615
Mumuni, A., & Mumuni, F. (2025). Automated data processing and feature engineering for deep learning and big data applications: A survey. Journal of Information and Intelligence, 3(2), 113–153. https://doi.org/10.1016/j.jiixd.2024.01.002
Murphy, M. H. (2017). Algorithmic surveillance: The collection conundrum. International Review of Law, Computers & Technology, 31(2), 225–242. https://doi.org/10.1080/13600869.2017.1298497
Park, Y. J., & Jones-Jang, S. M. (2023). Surveillance, security, and AI as technological acceptance. AI & Society, 38, 2667–2678. https://doi.org/10.1007/s00146-021-01331-9
Penttinen, J. T. J. (2013). Standardization and regulation. In The Telecommunications Handbook: Engineering Guidelines for Fixed, Mobile and Satellite Systems (pp. 23–48). Wiley. https://doi.org/10.1002/9781118678916.ch2
Power, D. J., Heavin, C., & O’Connor, Y. (2021). Balancing privacy rights and surveillance analytics: A decision process guide. Journal of Business Analytics, 4(2), 155–170. https://doi.org/10.1080/2573234X.2021.1920856
Priyadarshi, H., Singh, K., & Shrivastava, A. (2023). Wireless communications using machine learning and deep learning. In Machine Learning Algorithms for Signal and Image Processing (pp. 361–370). IEEE. https://doi.org/10.1002/9781119861850.ch20
Qi, J., Wu, F., Li, L., & Shu, H. (2007). Artificial intelligence applications in the telecommunications industry. Expert Systems, 24.
Quach, S., Thaichon, P., Martin, K. D., & et al. (2022). Digital technologies: Tensions in privacy and data. Journal of the Academy of Marketing Science, 50, 1299–1323. https://doi.org/10.1007/s11747-022-00845-y
R. H. J. & Mohana. (2022). Fraud detection and management for telecommunication systems using artificial intelligence (AI). 2022 3rd International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India, pp. 1016-1022. https://doi.org/10.1109/ICOSEC54921.2022.9951889
Ranjan, R., & Kumar, S. S. (2022). User behaviour analysis using data analytics and machine learning to predict malicious user versus legitimate user. High-Confidence Computing, 2(1), 100034. https://doi.org/10.1016/j.hcc.2021.100034
Rocha, N. A. de S., de Almeida, A. N., Nunes, A., & Angelo, H. (2024). Critical points for the processing of personal data by the government: An empirical study in Brazil. Computer Law & Security Review, 54, 106023. https://doi.org/10.1016/j.clsr.2024.106023
Rodrigues, R. (2020). Legal and human rights issues of AI: Gaps, challenges, and vulnerabilities. Journal of Responsible Technology, 4, 100005. https://doi.org/10.1016/j.jrt.2020.100005
Sachoulidou, A. (2024). Harnessing AI for law enforcement: Solutions and boundaries from the forthcoming AI Act. New Journal of European Criminal Law, 15(2), 117-125. https://doi.org/10.1177/20322844241260114
Saheb, T. (2023). Ethically contentious aspects of artificial intelligence surveillance: A social science perspective. AI Ethics, 3, 369–379. https://doi.org/10.1007/s43681-022-00196-y
Sampson, F. (2021). Data privacy and security: Some legal and ethical challenges. In: Jahankhani, H., Kendzierskyj, S., & Akhgar, B. (Eds.), Information security technologies for controlling pandemics. Advanced Sciences and Technologies for Security Applications. Springer, Cham, pp. 109–134. https://doi.org/10.1007/978-3-030-72120-6_4
Sargiotis, D. (2024). Data security and privacy: Protecting sensitive information. In Data Governance (pp. 217–245). Springer. https://doi.org/10.1007/978-3-031-67268-2_6
Saura, J. R., Ribeiro-Soriano, D., & Palacios-Marqués, D. (2021). From user-generated data to data-driven innovation: A research agenda to understand user privacy in digital markets. International Journal of Information Management, 60, 102331. https://doi.org/10.1016/j.ijinfomgt.2021.102331
Secundo, G., Spilotro, C., Gast, J., & others. (2024). The transformative power of artificial intelligence within innovation ecosystems: A review and a conceptual framework. Review of Managerial Science. https://doi.org/10.1007/s11846-024-00828-z
Seetharamu, S., Manasa, L. C. N., Bhattacharya, A., & Chitra, B. T. (2024). Digital data protection laws: A review. International Journal of Scientific Research in Science, Engineering and Technology, 11(5), 64–75. https://doi.org/10.32628/IJSRSET2411416
Sergiou, C., Lestas, M., Antoniou, P., Liaskos, C., & Pitsillides, A. (2020). Complex systems: A communication networks perspective towards 6G. IEEE Access, 8, 89007-89030. https://doi.org/10.1109/ACCESS.2020.2993527
Shin, D., Kee, K. F., & Shin, E. Y. (2022). Algorithm awareness: Why user awareness is critical for personal privacy in the adoption of algorithmic platforms? International Journal of Information Management, 65, 102494. https://doi.org/10.1016/j.ijinfomgt.2022.102494
Singh, T. (2024). AI-driven surveillance technologies and human rights: Balancing security and privacy. In A. K. Somani, A. Mundra, R. K. Gupta, S. Bhattacharya, & A. P. Mazumdar (Eds.), Smart systems: Innovations in computing. SSIC 2023 (Vol. 392, pp. 611-620). Springer. https://doi.org/10.1007/978-981-97-3690-4_53
Singhal, A., Neveditsin, N., Tanveer, H., & Mago, V. (2024). Toward fairness, accountability, transparency, and ethics in AI for social media and health care: Scoping review. JMIR Medical Informatics, 12, e50048. https://doi.org/10.2196/50048
Sumartono, E., Harliyanto, R., Situmeang, S. M. T., Siagian, D. S., & Septaria, E. (2024). The legal implications of data privacy laws, cybersecurity regulations, and AI ethics in a digital society. The Journal of Academic Science, 1(2). https://doi.org/10.59613/29qypw51
Timan, T., & Mann, Z. (2021). Data protection in the era of artificial intelligence: Trends, existing solutions, and recommendations for privacy-preserving technologies. In E. Curry, A. Metzger, S. Zillner, J. C. Pazzaglia, & A. García Robles (Eds.), The elements of big data value. Springer, Cham. https://doi.org/10.1007/978-3-030-68176-0_7
van Daalen, O. L. (2023). The right to encryption: Privacy as preventing unlawful access. Computer Law & Security Review, 49, 105804. https://doi.org/10.1016/j.clsr.2023.105804
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Wang, Z., Wei, G. F., Zhan, Y. L., et al. (2017). Big data in telecommunication operators: Data, platform, and practices. Journal of Communications and Information Networks, 2(3), 78–91. https://doi.org/10.1007/s41650-017-0010-1
Whang, S. E., Roh, Y., Song, H., & others. (2023). Data collection and quality challenges in deep learning: A data-centric AI perspective. The VLDB Journal, 32, 791–813. https://doi.org/10.1007/s00778-022-00775-9
Zachary, G. P. (2020). Digital manipulation and the future of electoral democracy in the U.S. IEEE Transactions on Technology and Society, 1(2), 104–112. https://doi.org/10.1109/TTS.2020.2992666
Zhang, Y., Wu, M., Tian, G. Y., Zhang, G., & Lu, J. (2021). Ethics and privacy of artificial intelligence: Understandings from bibliometrics. Knowledge-Based Systems, 222, 106994. https://doi.org/10.1016/j.knosys.2021.106994
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