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Documents authored by Wirth, Christoph Tobias

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Academic Track
DOI: 10.4230/OASIcs.SAIA.2024.7
Towards Trusted AI: A Blueprint for Ethics Assessment in Practice (Academic Track)

Authors: Christoph Tobias Wirth, Mihai Maftei, Rosa Esther Martín-Peña, and Iris Merget

Published in: OASIcs, Volume 126, Symposium on Scaling AI Assessments (SAIA 2024)

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.
Cite as

Christoph Tobias Wirth, Mihai Maftei, Rosa Esther Martín-Peña, and Iris Merget. Towards Trusted AI: A Blueprint for Ethics Assessment in Practice (Academic Track). In Symposium on Scaling AI Assessments (SAIA 2024). Open Access Series in Informatics (OASIcs), Volume 126, pp. 7:1-7:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{wirth_et_al:OASIcs.SAIA.2024.7,
  author =	{Wirth, Christoph Tobias and Maftei, Mihai and Mart{\'\i}n-Pe\~{n}a, Rosa Esther and Merget, Iris},
  title =	{{Towards Trusted AI: A Blueprint for Ethics Assessment in Practice}},
  booktitle =	{Symposium on Scaling AI Assessments (SAIA 2024)},
  pages =	{7:1--7:19},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-357-7},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{126},
  editor =	{G\"{o}rge, Rebekka and Haedecke, Elena and Poretschkin, Maximilian and Schmitz, Anna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SAIA.2024.7},
  URN =		{urn:nbn:de:0030-drops-227478},
  doi =		{10.4230/OASIcs.SAIA.2024.7},
  annote =	{Keywords: Trusted AI, Trustworthy AI, AI Ethics Assessment Framework, AI Quality, AI Ethics, AI Ethics Assessment, AI Lifecycle, Responsible AI, Ethics-By-Design, AI Risk Management, Ethics Impact Assessment, AI Ethics KPIs, Human-Centric AI, Applied Ethics}
}
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