Artificial intelligence for optimizing protective measures in domestic violence cases

Authors

  • Evelyn Diana Cayllahua Cépida Universidad Nacional de Huancavelica, Huancavelica, Perú
  • Marjorie Jhanira Arana Colquepisco Universidad Nacional de Huancavelica, Huancavelica, Perú

DOI:

https://doi.org/10.54943/rceo.v5i2.816

Keywords:

Artificial Intelligence, Protective Measures, Law No. 30364, Domestic Violence Proceedings, Family Law

Abstract

In response to accelerated technological advancement, legal science is facing a new era marked by the influence of artificial intelligence (AI). This influence is largely realized through the standardization and implementation of legal expert systems (LES), tools designed to enhance the effectiveness and efficiency of the administration of justice in various fields of law. In this context, Peruvian society, and particularly in our Huancavelica region, faces an urgent and persistent challenge: domestic violence. The victims of this complex social problem deserve expeditious and effective protection of their fundamental rights, a task where traditional judicial systems often encounter limitations due to procedural overload and the complexity of each case. AI, therefore, emerges as a promising alternative to streamline the state's response and guarantee effective judicial protection. This article proposes a critical analysis of the impact of the application of artificial intelligence on the design and implementation of protection measures within domestic violence cases. To this end, the classic theories and doctrines of jurists who have laid the foundation for the study of family law and the protection of fundamental rights will be addressed, serving as precedents for a critical discussion on the relevance and risks of technology in this sensitive area.

Published

2025-10-31

How to Cite

Cayllahua Cépida, E. D., & Arana Colquepisco, M. J. (2025). Artificial intelligence for optimizing protective measures in domestic violence cases . Revista De Investigación Científica Erga Omnes, 5(2), 09–25. https://doi.org/10.54943/rceo.v5i2.816