Garantías procesales para la protección de datos personales frente a tecnologías automatizadas.

Abstract

The proliferation of artificial intelligence systems for mass personal data processing poses a severe dilemma for effective judicial protection in Ecuador. Machine learning algorithms operate as "black boxes," creating opaque environments where reconstructing causation or establishing direct human fault under traditional civil law rules becomes virtually impossible. This technical asymmetry creates an insurmountable evidentiary barrier for individuals against corporations under the standard procedural regime of the General Organic Code of Processes (COGEP). Through dogmatic and statutory analysis, this study examines informational self-determination and the right not to be subjected to solely automated decisions under the Organic Law on Personal Data Protection (LOPDP), Resolution SPDP-SPD-2026-0009-R, and comparative legal standards. The findings indicate that ordinary procedural rules fail to address harmful algorithmic outcomes, allowing technological complexity to shield corporate liability. Consequently, this paper proposes the mandatory application of the dynamic burden of proof in judicial proceedings, a strict civil liability framework based on created risk, the mandatory inclusion of the human-in-the-loop safeguard, and risk-based regulatory classifications enforced by the supervisory authority.