A Comprehensive Survey and Classification of Evaluation Criteria for Trustworthy Artificial Intelligence
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910661244616704 |
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| author | McCormack, Louise Bendechache, Malika |
| author_facet | McCormack, Louise Bendechache, Malika |
| contents | This paper presents a systematic review of the literature on evaluation criteria for Trustworthy Artificial Intelligence (TAI), with a focus on the seven EU principles of TAI. This systematic literature review identifies and analyses current evaluation criteria, maps them to the EU TAI principles and proposes a new classification system for each principle. The findings reveal both a need for and significant barriers to standardising criteria for TAI evaluation. The proposed classification contributes to the development, selection and standardization of evaluation criteria for TAI governance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_17281 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Comprehensive Survey and Classification of Evaluation Criteria for Trustworthy Artificial Intelligence McCormack, Louise Bendechache, Malika Computers and Society Artificial Intelligence Human-Computer Interaction Machine Learning This paper presents a systematic review of the literature on evaluation criteria for Trustworthy Artificial Intelligence (TAI), with a focus on the seven EU principles of TAI. This systematic literature review identifies and analyses current evaluation criteria, maps them to the EU TAI principles and proposes a new classification system for each principle. The findings reveal both a need for and significant barriers to standardising criteria for TAI evaluation. The proposed classification contributes to the development, selection and standardization of evaluation criteria for TAI governance. |
| title | A Comprehensive Survey and Classification of Evaluation Criteria for Trustworthy Artificial Intelligence |
| topic | Computers and Society Artificial Intelligence Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2410.17281 |