Projektbeschreibung
Erkenntnisse zu den Folgen von Algorithmen für maschinelles Lernen für heutige Gesellschaften
Rasante Fortschritte bei den Technologien für maschinelles Lernen verändern das soziale und politische Leben auf eine Art und Weise, die unser Leben im Verhältnis zu anderen auf einzigartige Weise herausfordert. Die Lebenschancen einer Person hängen nun eng mit den Attributen zusammen, die ein Algorithmus aus den Datenmustern unbekannter Personen erlernt hat. Das EU-finanzierte Projekt ALGOSOC entwickelt einen neuen Ansatz, um die Folgen von Algorithmen für maschinelles Lernen für heutige Gesellschaften zu verstehen und darauf zu reagieren. Das Projekt soll untersuchen, wie Algorithmen des maschinellen Lernens im 21. Jahrhundert lernen, die Eigenschaften von Wesen, insbesondere von Menschen, Gruppen und Objekten, zu erkennen, zuzuordnen und daraus zu folgern.
Ziel
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.
Wissenschaftliches Gebiet
Schlüsselbegriffe
Programm/Programme
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Finanzierungsplan
ERC-ADG - Advanced GrantGastgebende Einrichtung
DH1 3LE Durham
Vereinigtes Königreich