Towards Trusted AI: A Blueprint for Ethics Assessment in Practice (Academic Track)

The development of AI technologies leaves place for unforeseen ethical challenges. Issues such as bias, lack of transparency and data privacy must be addressed during the design, development, and the deployment stages throughout the lifecycle of AI systems to mitigate their impact on users. Consequently, ensuring that such systems are responsibly built has become a priority for researchers and developers from both public and private sector. As a proposed solution, this paper presents a blueprint for AI ethics assessment. The blueprint provides for AI use cases an adaptable approach which is agnostic to ethics guidelines, regulatory environments, business models, and industry sectors. The blueprint offers an outcomes library of key performance indicators (KPIs) which are guided by a mapping of ethics framework measures to processes and phases defined by the blueprint. The main objectives of the blueprint are to provide an operationalizable process for the responsible development of ethical AI systems, and to enhance public trust needed for broad adoption of trusted AI solutions. In an initial pilot the blueprinted for AI ethics assessment is applied to a use case of generative AI in education.

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Publication Details

Journal
DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
Published
2025-01-01
DOI
https://doi.org/10.4230/oasics.saia.2024.7
Citations
2
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
4.73

Funders

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article

Towards Trusted AI: A Blueprint for Ethics Assessment in Practice (Academic Track)

2 citations
DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
Ethics and Social Impacts of AI
4.73
article

Towards Trusted AI: A Blueprint for Ethics Assessment in Practice (Academic Track)

article en
2 citations

Abstract

The development of AI technologies leaves place for unforeseen ethical challenges. Issues such as bias, lack of transparency and data privacy must be addressed during the design, development, and the deployment stages throughout the lifecycle of AI systems to mitigate their impact on users. Consequently, ensuring that such systems are responsibly built has become a priority for researchers and developers from both public and private sector. As a proposed solution, this paper presents a blueprint for AI ethics assessment. The blueprint provides for AI use cases an adaptable approach which is agnostic to ethics guidelines, regulatory environments, business models, and industry sectors. The blueprint offers an outcomes library of key performance indicators (KPIs) which are guided by a mapping of ethics framework measures to processes and phases defined by the blueprint. The main objectives of the blueprint are to provide an operationalizable process for the responsible development of ethical AI systems, and to enhance public trust needed for broad adoption of trusted AI solutions. In an initial pilot the blueprinted for AI ethics assessment is applied to a use case of generative AI in education.

DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
German Research Centre for Artificial Intelligence (DE)
Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 4%
Ethics and Social Impacts of AI
4.73
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