文章基本信息

标题：Development Practices of Trusted AI Systems among Canadian Data Scientists
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作者：Jinnie Shin ; Okan Bulut ; Mark J. Gierl 等
期刊名称：International Review of Information Ethics
印刷版ISSN：1614-1687
出版年度：2020
卷号：28
页码：1
DOI：10.29173/irie377
出版社：International Center for Information Ethics
摘要：The introduction of Artificial Intelligence (AI) systems has demonstrated impeccable potential and benefits to enhance the decision-making processes in our society. However, despite the successful performance of AI systems to date, skepticism and concern remain regarding whether AI systems could form a trusting relationship with human users. Developing trusted AI systems requires careful consideration and evaluation of its reproducibility, interpretability, and fairness, which in in turn, poses increased expectations and responsibilities for data scientists. Therefore, the current study focused on understanding Canadian data scientists’ self-confidence in creating trusted AI systems, while relying on their current AI system development practices.
关键词：Artificial Intelligence; Data Science; Explainability; Fairness; Machine Learning; Trust