{"type":"ScholarlyArticle","title":"Putting Accountability of AI Systems into Practice","authors":[{"name":"Beatriz San Miguel","slug":"beatriz-san-miguel","given":"Beatriz San","family":"Miguel","affiliation":"Fujitsu Laboratories of Europe , United Kingdom"},{"name":"Aisha Naseer","slug":"aisha-naseer","given":"Aisha","family":"Naseer","affiliation":"Fujitsu Laboratories of Europe , United Kingdom"},{"name":"Hiroya Inakoshi","slug":"hiroya-inakoshi","given":"Hiroya","family":"Inakoshi","affiliation":"Fujitsu Laboratories of Europe , United Kingdom"}],"abstract":"To improve and ensure trustworthiness and ethics on Artificial Intelligence (AI) systems, several initiatives around the globe are producing principles and recommendations, which are providing to be difficult to translate into technical solutions. A common trait among ethical AI requirements is accountability that aims at ensuring responsibility, auditability, and reduction of negative impact of AI systems. To put accountability into practice, this paper presents the Global-view Accountability Framework (GAF) that considers auditability and redress of conflicting information arising from a context with two or more AI systems which can produce a negative impact. A technical implementation of the framework for automotive and motor insurance is demonstrated, where the focus is on preventing and reporting harm rendered by autonomous vehicles.","doi":"10.24963/ijcai.2020/768","url":"https://ijcai.org/proceedings/2020/768","pdf":"https://ijcai.org/proceedings/2020/0768.pdf","markdown":"https://ijcai.org/proceedings/2020/768.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/768","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Demos","track":"Demos","number":768,"pages":{"first":5276,"last":5278},"keywords":["Uncertainty in AI: general","Multi-agent Systems: general"],"videos":[],"references":[{"position":1,"raw":"[Adadi and Berrada, 2018] Amina Adadi and Mohammed Berrada. 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