The benefits and risks of artificial intelligence in personal data protection in Ecuador

  • Vanessa Carolina Gallegos-Unda Universidad Regional Autónoma de los Andes, Ambato, Tungurahua, Ecuador
  • Gladis Margo Proaño-Reyes Universidad Regional Autónoma de los Andes, Ambato, Tungurahua, Ecuador
  • Fernando de Jesús Castro-Sánchez Universidad Regional Autónoma de los Andes, Ambato, Tungurahua, Ecuador
Keywords: Artificial intelligence, personal data protection, data governance, algorithms, privacy, (UNESCO Thesaurus).

Abstract

ABSTRACT

This research analyzes the complex convergence between artificial intelligence (AI) and personal data protection in Ecuador. Its objective is to identify the benefits and risks of this application, examining the current legal framework and challenges in data governance. Through a qualitative methodology and documentary analysis, the study reveals that AI can significantly enhance efficiency and security in information processing. However, inherent risks also arise, such as possible algorithmic biases and privacy violations. The findings emphasize that responsible, transparent, and ethical implementation, backed by robust data governance, is essential to mitigate these dangers. In conclusion, AI has transformative potential for Ecuador, but its success depends on the creation of a robust regulatory framework that ensures a balance between technological innovation and the protection of fundamental rights.

 

Downloads

Download data is not yet available.

Author Biographies

Vanessa Carolina Gallegos-Unda, Universidad Regional Autónoma de los Andes, Ambato, Tungurahua, Ecuador
Gladis Margo Proaño-Reyes, Universidad Regional Autónoma de los Andes, Ambato, Tungurahua, Ecuador
Fernando de Jesús Castro-Sánchez, Universidad Regional Autónoma de los Andes, Ambato, Tungurahua, Ecuador

References

Abraham, R., Schneider, J., & vom Brocke, J. (2019). Data governance: A conceptual framework, structured review, and research agenda. International Journal of Information Management, 49, 424-438. https://doi.org/10.1016/j.ijinfomgt.2019.07.008

Barragán-Martínez, X. (2023). Situación de la Inteligencia Artificial en el Ecuador en relación con los países líderes de la región del Cono Sur. FIGEMPA: Investigación y Desarrollo, 16(2), 23-38. https://doi.org/10.29166/revfig.v16i2.4498

Benalcázar, M. (2024). Proyecto de Ley Orgánica de Regulación y Promoción de la Inteligencia Artificial en el Ecuador. Asamblea Nacional del Ecuador. http://www.asambleanacional.gob.ec/leyes/proyecto-ley-ia

Benfeldt, O., Persson, J. S., & Madsen, S. (2020). Data governance as a collective action problem. Information Systems Frontiers, 22(2), 299-313. https://doi.org/10.1007/s10796-019-09923-z

Brous, P., Janssen, M., & Krans, R. (2020). The success of data governance initiatives: A measurement framework. Journal of Theoretical and Applied Electronic Commerce Research, 15(2), 1-15. https://doi.org/10.4067/S0718-18762020000200101

Comisión Europea. (2020). Libro Blanco sobre la Inteligencia Artificial: un enfoque europeo orientado a la excelencia y la confianza. https://n9.cl/9jq3j

Comisión Europea. (2021). Propuesta de Reglamento del Parlamento Europeo y del Consejo por el que se establecen normas armonizadas en materia de inteligencia artificial. Ley de Inteligencia Artificial. https://n9.cl/0kcju

DAMA International. (2017). The DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK2). Technics Publications. https://n9.cl/t4tgv

Floridi, L. (2018). La Cuarta Revolución: Cómo la infosfera está transformando la realidad. Oxford University Press. https://n9.cl/pflt1l

Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review. https://n9.cl/jm6sk

Fouirner, J. (2021). Measuring AI: Investment, Innovation, Implementation. Tortoise Media. https://n9.cl/ag6g8u

Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., & Janowski, T. (2020). Data governance: Organizing data for trustworthy Artificial Intelligence. Government Information Quarterly, 37(3), 101493. https://doi.org/10.1016/j.giq.2020.101493

Mendoza, P. (2022). Protección de datos personales en la era de la inteligencia artificial. Editorial Tirant Lo Blanch. https://n9.cl/jmh9q

OCDE. (2019). Artificial Intelligence in Society. OECD Publishing. https://doi.org/10.1787/eedfee77-en

OCDE. (2024). AI and the Future of Data Governance. OECD Digital Economy Papers, No. 352. https://doi.org/10.1787/5d8a0c3c-en

Osoba, O. A., & Welser IV, W. (2017). An Intelligence in Our Image: The Risks of Bias and Errors in Artificial Intelligence. RAND Corporation. https://n9.cl/mmt9b

Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Pearson. https://n9.cl/w7iol

Sullivan, B. (2024). The Cost of Data Breach: The Value of AI and Automation. IBM Security. https://n9.cl/rqvag

Zarsky, T. (2016). The trouble with algorithmic decisions: An analytic road map to examine efficiency and fairness in automated and opaque decision making. Science, Technology, & Human Values, 41(1), 118-132. https://doi.org/10.1177/0162243915605575

Zhang, C., Zhao, K., & Kumar, R. L. (2016). The impact of data governance on organizational performance. Proceedings of the 20th Pacific Asia Conference on Information Systems (PACIS). https://n9.cl/axc0a9
Published
2025-08-01

Most read articles by the same author(s)

1 2 3 4 5 6 7 8 > >>