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  • 标题:Lessons learn on responsible AI implementation: the ASSISTANT use case
  • 本地全文:下载
  • 作者:Eduardo Vyhmeister ; Gabriel G. Castane ; Johan Buchholz
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:10
  • 页码:377-382
  • DOI:10.1016/j.ifacol.2022.09.422
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Currently, pioneer companies are working hard to construct applied ethical frameworks in different sectors for using AI components that generate trust in their clients and workforce. However, independent of these few companies, there is still a considerable gap between understanding the impact of using responsible AI components, the implications of the lack of use, and what is currently applied in the industrial sector.Given that industry has shown an increased commitment to incorporating AI components, works focus on broadening the understanding of manufacturing sector stakeholders of what approaches could be considered within AI life-cycle, reducing the gap between principles and actionable requirements, and defining fundamental considerations based on risk management for incorporating, and managing, AI-based on responsible AI are required.In this work, we present a summary of the most suitable approaches that can be used for implementation and the lessons learned from a European Funded project (ASSISTANT).
  • 关键词:AI;standardisation;responsible AI;AI ethics;Human centered automation;design methodology for HMS;AI en manufacturing
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