Descripción del proyecto
Comprender las consecuencias de los algoritmos de aprendizaje automático para las sociedades contemporáneas
Los rápidos avances en las tecnologías de aprendizaje automático están transformando la vida social y política de maneras que desafían como nunca antes la forma en que vivimos en relación con los demás. Ahora, las oportunidades vitales de una persona están íntimamente vinculadas con los atributos que un algoritmo ha aprendido de los patrones de datos de otros desconocidos. El proyecto ALGOSOC, financiado con fondos europeos, está desarrollando un nuevo enfoque para entender y responder a las consecuencias de los algoritmos de aprendizaje automático para las sociedades contemporáneas. En el proyecto analizará cómo los algoritmos de aprendizaje automático del siglo XXI están aprendiendo a reconocer, atribuir e inferir las características de las entidades, más específicamente de las personas, los grupos y los objetos.
Objetivo
ALGOSOC develops a new approach to understanding and responding to the consequences of machine learning algorithms for contemporary societies. Rapid advancements in machine learning technologies are transforming social and political life in ways that uniquely challenge how we live in relation to others. The life chances of a person are now intimately connected to the attributes that an algorithm has learned from the data patterns of unknown others. From judgements in the criminal justice system to decisions on treatment pathways in health, the outputs of algorithms have become pivotal to the decisions and adjudications on the probable futures of individuals. While there is substantial academic and public emphasis on defining ethical codes of conduct for algorithmic decisions, there is a lack of attention to how machine learning algorithms remake the ethical relations that define a society. In short, existing research is focused on limiting the harms of the actions of algorithms, whereas ALGOSOC focuses on how algorithms are redefining the thresholds of what harmful, good, bad, or risky behaviour means in a society. The ALGOSOC project will examine how 21st century machine learning algorithms are learning to recognize, to attribute, and to infer the characteristics of entities (people, groups, and objects). In order to do this, the project will conduct a series of path-defining studies of societal domains of machine learning that, though they share algorithms in common, have not previously been researched in combination: behavioural biometrics and biomedical object recognition; consumer recommendation and criminal justice scoring; oncology treatment pathways and anomaly detection for security. The ALGOSOC project will provide new social science knowledge of what is taking place as machine learning algorithms travel across different domains and sites, and how precisely they learn by their exposure to different worlds of data.
Ámbito científico
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Régimen de financiación
ERC-ADG - Advanced GrantInstitución de acogida
DH1 3LE Durham
Reino Unido