De la amenaza al algoritmo: la dataficación de la protesta social
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Centro de Estudios en Relaciones Internacionales de Rosario (CERIR)
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La protesta social ha constituido históricamente una forma central de demanda política no estatal mediante la cual actores colectivos interpelan decisiones públicas y visibilizan conflictos estructurales. En las últimas décadas, sin embargo, los Estados han transformado sus estrategias de gestión del disenso, desplazándose desde enfoques predominantemente reactivos hacia racionalidades preventivas sustentadas en narrativas de seguridad. Este artículo analiza cómo la securitización de la protesta social, combinada con procesos de dataficación y el uso de tecnologías de inteligencia artificial, reconfigura la relación entre Estado, ciudadanía y accióncolectiva. Desde una perspectiva crítica de la seguridad y las relaciones internacionales, se sostiene que la traducción de la protesta en datos cuantificables posibilita su gobierno bajo una lógica de riesgo, en la cual la anticipación y el cálculo algorítmico sustituyen progresivamente a la deliberación política. El artículo examina los efectos de esta transformación sobre la democracia y los derechos fundamentales, particularmente el derecho a la protesta y la libertad de expresión, destacando los riesgos asociados a la opacidad, los sesgos algorítmicos y la expansión de prácticas de vigilancia preventiva. Finalmente, se argumenta que la gestión algorítmica de la protesta plantea desafíos sustantivos para los marcos normativos democráticos, al despolitizar el conflicto social y reforzar formas de control estatal bajo una apariencia de neutralidad técnica.
Social protest has historically constituted a central form of non-state political demand through which collective actors challenge public decisions and make structural conflicts visible. In recent decades, however, states have transformed their approaches to managing dissent, shifting from predominantly reactive strategies toward preventive rationalities grounded in security narratives. This article examines how the securitization of social protest, combined with processes of datafication and the deploymentof artificial intelligence technologies, reshapes the relationship between the state, citizenship, and collective action. Drawing on critical security studies and international relations, the article argues that the translation of protest into quantifiable data enables its governance through a logic of risk, in which anticipation and algorithmic calculation increasingly replace political deliberation. It analyzes the democratic and human rights implications of this transformation, particularly regarding the right to protest and freedom of expression, emphasizing the risks posed by algorithmic opacity, embedded biases, and the expansion of preventive surveillance practices. The article concludes that the algorithmic management of protest poses significant challenges to democratic normative frameworks by depoliticizing social conflict and reinforcing forms of state control under a veneer of technical neutrality.
Social protest has historically constituted a central form of non-state political demand through which collective actors challenge public decisions and make structural conflicts visible. In recent decades, however, states have transformed their approaches to managing dissent, shifting from predominantly reactive strategies toward preventive rationalities grounded in security narratives. This article examines how the securitization of social protest, combined with processes of datafication and the deploymentof artificial intelligence technologies, reshapes the relationship between the state, citizenship, and collective action. Drawing on critical security studies and international relations, the article argues that the translation of protest into quantifiable data enables its governance through a logic of risk, in which anticipation and algorithmic calculation increasingly replace political deliberation. It analyzes the democratic and human rights implications of this transformation, particularly regarding the right to protest and freedom of expression, emphasizing the risks posed by algorithmic opacity, embedded biases, and the expansion of preventive surveillance practices. The article concludes that the algorithmic management of protest poses significant challenges to democratic normative frameworks by depoliticizing social conflict and reinforcing forms of state control under a veneer of technical neutrality.