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Society-Aware Machine Learning: The paradigm shift demanded by society to trust machine learning.

CORDIS · observation · Publication date unknown

Society-Aware Machine Learning: The paradigm shift demanded by society to trust machine learning. To date, the design of ethical machine learning (ML) algorithms has been dominated by technology owners and remains broadly criticized for strategically seeking to avoid legally enforceable restrictions. In order to foster trust in ML technologies, society demands technology designers to deeply engage all relevant stakeholders in the ML development. This ERC project aims at responding to this call with a society-aware approach to ML (SAML). My goal is to enable the collaborative design of ML algorithms, so that they are not only driven by economic interests of the technology owners but are agreed upon by all stakeholders, and ultimately, trusted by society. To this end, I aim to develop multi-party ML algorithms that explicitly account for the goals of different stakeholders---i.e., owners, those expert

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recordType

award

status

SIGNED

region

EU

value

1499845

unit

EUR