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Algorithmic Societies: Ethical Life in the Machine Learning Age

Project information

Grant agreement ID: 883107

Status

Grant agreement signed

  • Start date

    1 October 2020

  • End date

    30 September 2025

Funded under:

H2020-EU.1.1.

  • Overall budget:

    € 2 150 686

  • EU contribution

    € 2 150 686

Hosted by:

UNIVERSITY OF DURHAM

United Kingdom

Objective

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.
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Host institution

UNIVERSITY OF DURHAM

Address

Stockton Road The Palatine Centre
Dh1 3le Durham

United Kingdom

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 2 150 686

Beneficiaries (1)

UNIVERSITY OF DURHAM

United Kingdom

EU Contribution

€ 2 150 686

Project information

Grant agreement ID: 883107

Status

Grant agreement signed

  • Start date

    1 October 2020

  • End date

    30 September 2025

Funded under:

H2020-EU.1.1.

  • Overall budget:

    € 2 150 686

  • EU contribution

    € 2 150 686

Hosted by:

UNIVERSITY OF DURHAM

United Kingdom