Parasitismo libertario en entornos digitales: Análisis del problema y propuestas de actuación
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Publication date
2021
Defense date
15/08/2021
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Abstract
El presente trabajo trata de mostrar el hilo conductor que une algunos importantes problemas de la actualidad a través de su relación con la arquitectura de las redes sociales. Estos problemas se presentan en dos categorías principales: sociales (posverdad, polarización) e individuales (adicciones, ansiedad, depresión). Las redes sociales generarían o, como poco, potenciarían estos problemas de forma coherente con lo que se denominará parasitismo libertario, es decir, dirigiendo a los individuos hacia comportamientos que van en su propio perjuicio, por medio de un sistema de incentivos propiciado por el modelo económico de la economía de la atención, pero siempre bajo la premisa de que el individuo es formalmente libre para dejar de usarlas. En este modelo, las empresas obtienen más beneficios cuanto más tiempo consigan mantener a más usuarios dentro de sus redes y produzcan mejores modelos predictivos con los que vender espacios a anunciantes. Se apuntarán algunos de los mecanismos mediante los que el diseño de estas redes sociales y sus algoritmos se convierten en algo potencialmente perjudicial y cómo su defensa proviene de una antropología deficiente. También se discutirá la posibilidad de una solución desde dentro del propio entorno empresarial a través del concepto de responsabilidad social de las empresas y, por último, se bosquejarán algunas propuestas de solución.
The present work intends to show the common thread that links some important current problems through their relationship with social network's arquitecture. These problems fall into two main categories: social (post-truth, polarization) and individual (addictions, anxiety, depression). Social networks would generate or, at the very least, augment these problems in a way consistent with what will be called libertarian parasitism, that is, directing individuals towards behaviors that are to their own detriment, due to a system of incentives set by the economic model of the attention economy, but always under the premise that the individual is formally free to stop using them. In this model, companies profit more the longer they manage to keep more users within their networks and produce more accurate predictions of their behaviour in order to get ad revenue. It will also outline some of the mechanisms by which the design of these social networks and their algorithms become potentially harmful and how its advocates uphold an inaccurate anthropology. It will also explore the possibility of a solution from within the business environment itself through the concept of corporate social responsibility and, finally, it will sketch some proposals to fix the problems generated.
The present work intends to show the common thread that links some important current problems through their relationship with social network's arquitecture. These problems fall into two main categories: social (post-truth, polarization) and individual (addictions, anxiety, depression). Social networks would generate or, at the very least, augment these problems in a way consistent with what will be called libertarian parasitism, that is, directing individuals towards behaviors that are to their own detriment, due to a system of incentives set by the economic model of the attention economy, but always under the premise that the individual is formally free to stop using them. In this model, companies profit more the longer they manage to keep more users within their networks and produce more accurate predictions of their behaviour in order to get ad revenue. It will also outline some of the mechanisms by which the design of these social networks and their algorithms become potentially harmful and how its advocates uphold an inaccurate anthropology. It will also explore the possibility of a solution from within the business environment itself through the concept of corporate social responsibility and, finally, it will sketch some proposals to fix the problems generated.