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Justificatory explanations in machine learning: for increased transparency through documenting how key concepts drive and underpin design and engineering decisions
Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technica...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer London
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8965536/ https://www.ncbi.nlm.nih.gov/pubmed/35370366 http://dx.doi.org/10.1007/s00146-022-01389-z |