{"type":"ScholarlyArticle","title":"AI in Recruiting. Multi-agent Systems Architecture for Ethical and Legal Auditing","authors":[{"name":"María del Carmen Fernández Martínez","slug":"maria-del-carmen-fernandez-martinez","given":"María del Carmen","family":"Fernández Martínez","affiliation":""},{"name":"Alberto Fernández","slug":"alberto-fernandez","given":"Alberto","family":"Fernández","affiliation":""}],"abstract":"Artificial Intelligence (AI) domain-specific applications may have different ethical and legal implications. One of the current questions of AI is the challenges behind the analysis of job video-interviews. There are pros and cons to using AI in recruitment processes, and potential consequences for candidates, companies and states. Furthermore, the deficit of regulation of these systems reinforces the need for external and neutral auditing of the types of analysis made in interviews. We, therefore, propose a Multi-agent system architecture for neutral auditing to guarantee an inclusive and accurate AI and to reduce the potential discrimination in the job market.","doi":"10.24963/ijcai.2019/903","url":"https://ijcai.org/proceedings/2019/903","pdf":"https://ijcai.org/proceedings/2019/0903.pdf","markdown":"https://ijcai.org/proceedings/2019/903.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/903","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":903,"pages":{"first":6428,"last":6429},"keywords":["Agent-based and Multi-agent Systems: Agent Communication","Agent-based and Multi-agent Systems: Human-Agent Interaction","Multidisciplinary Topics and Applications: Philosophical and Ethical Issues","Humans and AI: Ethical Issues in AI"],"videos":[],"references":[{"position":1,"raw":"[Siyao et al., 2014] Siyao Fu, Haibo He, Zeng-Guang Hou. Learning from Face: A Survey. IEEE Trans. Pattern Anal. Mach. Intel 36(12): 2483-2509, 2014.","title":"Learning from Face: A Survey","authors":"Siyao Fu, Haibo He, Zeng-Guang Hou","year":"2014","venue":"IEEE Trans. Pattern Anal. Mach. Intel","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Kosinski and Wang, 2018] Michal Kosinksi and Yilum. Wang. Deep neural networks are more accurate than humans at detecting sexual orientation from images. Journal of Personality and Social Psychology, 114(2):246-257, 2018.","title":"Deep neural networks are more accurate than humans at detecting sexual orientation from images","authors":"Wang ; Kosinski, Michal Kosinksi, Yilum Wang","year":"2018","venue":"Journal of Personality and Social Psychology","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Dileo et al., 2006] Jonathan DiLeo, Timothy Jacobs and Scott DeLoach. Integrating ontologies into multiagent systems engineering. Air Univ Maxwell AFB Al Center For Aerospace Doctrine Research and Education, 2006.","title":"Integrating ontologies into multiagent systems engineering","authors":"Jonathan Dileo, Timothy Jacobs, Scott Deloach","year":"2006","venue":null,"doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}