From AI ethics principles to data science practice: a reflection and a gap analysis based on recent frameworks and practical experience
article
In the field of AI ethics, after the introduction of ethical frameworks and the evaluation thereof, we seem to have arrived at
a third wave in which the operationalisation of ethics is central. Operationalisation is required, since ethics frameworks are
often not suited to be used by data scientists in the development of AI-based services or products. Therefore, in this paper,
we aim to contribute to this third wave by mapping AI ethical principles onto the lifecycle of an AI-based digital service or
product and combining it with an explicit governance model to clarify responsibilities in operationalisation. We then discuss
practical, conceptual, and political implications of this analysis to end with key challenges around operationalising AI ethics.
a third wave in which the operationalisation of ethics is central. Operationalisation is required, since ethics frameworks are
often not suited to be used by data scientists in the development of AI-based services or products. Therefore, in this paper,
we aim to contribute to this third wave by mapping AI ethical principles onto the lifecycle of an AI-based digital service or
product and combining it with an explicit governance model to clarify responsibilities in operationalisation. We then discuss
practical, conceptual, and political implications of this analysis to end with key challenges around operationalising AI ethics.
Topics
TNO Identifier
981622
Source
AI and Ethics, 2(4), pp. 697-711.
Pages
697-711
Files
To receive the publication files, please send an e-mail request to TNO Repository.