The development of computer science has raised ethical concerns regarding the potential negative impacts of machine learning tools on people and society. Some examples are pornographic deepfakes used as weapons of war against women; pattern recognition designed to uncover sexual orientation; and misuse of data and deep learning by private companies to influence democratic elections. We contend that these three examples are cases of automated evil. In this article, we defend that the concept of forbidden knowledge can help to inform a coherent ethical framework in the context of machine learning research. We conclude that restricting generalised access to extensive data and limiting access to ready-to-use codes would mitigate potential harms caused by machine learning tools. In addition, the notions of intersectionality and interdisciplinarity should be systematically introduced in data and computer science research.
Este estudio examina el comportamiento de los hombres prostituidores en el contexto de la pandemia del Covid-19 a través del discurso de aquellos que han participado en foros de prostitución durante el primer año de la pandemia en España. Aplicando la metodología del Feminist Critical Discourse Analysis (FCDA) este estudio aplica la noción de “masculinidad como factor de riesgo” a los hombres prostituidores, quienes ponen en peligro la salud de las mujeres prostituidas, de otras mujeres y hombres, y la suya propia. Además, este artículo propone una cuarta dimensión con respecto a posibles aspectos negativos de la masculinidad sobre la sociedad y la salud pública en el contexto de la pandemia. La identificación de los hombres prostituidores con una masculinidad misógina debe considerarse un problema tanto desde el punto de vista epidemiológico como desde una perspectiva de derechos humanos.
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