AI Certification: Advancing Ethical Practice by Reducing Information
Asymmetries
- URL: http://arxiv.org/abs/2105.10356v1
- Date: Thu, 20 May 2021 08:27:29 GMT
- Title: AI Certification: Advancing Ethical Practice by Reducing Information
Asymmetries
- Authors: Peter Cihon, Moritz J. Kleinaltenkamp, Jonas Schuett, Seth D. Baum
- Abstract summary: This paper draws from management literature on certification and reviews current AI certification programs and proposals.
The review indicates that the field currently focuses on self-certification and third-party certification of systems, individuals, and organizations.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: As artificial intelligence (AI) systems are increasingly deployed, principles
for ethical AI are also proliferating. Certification offers a method to both
incentivize adoption of these principles and substantiate that they have been
implemented in practice. This paper draws from management literature on
certification and reviews current AI certification programs and proposals.
Successful programs rely on both emerging technical methods and specific design
considerations. In order to avoid two common failures of certification, program
designs should ensure that the symbol of the certification is substantially
implemented in practice and that the program achieves its stated goals. The
review indicates that the field currently focuses on self-certification and
third-party certification of systems, individuals, and organizations - to the
exclusion of process management certifications. Additionally, the paper
considers prospects for future AI certification programs. Ongoing changes in AI
technology suggest that AI certification regimes should be designed to
emphasize governance criteria of enduring value, such as ethics training for AI
developers, and to adjust technical criteria as the technology changes.
Overall, certification can play a valuable mix in the portfolio of AI
governance tools.
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