Abstract
Artificial Intelligence (AI) domain-specific applications may have different ethical and legal implications depending on the domain. One of the current questions of the AI is the challenges behind the analysis of job video-interviews. There are pros and cons to using AI in recruitment processes, and potential ethical and legal consequences for candidates, companies and states. There is a deficit of regulation of these systems, and a need for external and neutral auditing of the types of analysis made in interviews. I propose a multi-agent system architecture for neutral auditing to guarantee a fair, inclusive and accurate AI and to reduce potential discrimination, for example on the basis of race or gender, in the job market.
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Work partially supported by the Spanish Ministry of Science, Innovation and Universities, co-funded by EU FEDER Funds, through grants TIN2015-65515-C4-4-R and RTI2018-095390-B-C33.
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Fernández, C., Fernández, A. (2019). Inclusive AI in Recruiting. Multi-agent Systems Architecture for Ethical and Legal Auditing. In: De La Prieta, F., et al. Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection. PAAMS 2019. Communications in Computer and Information Science, vol 1047. Springer, Cham. https://doi.org/10.1007/978-3-030-24299-2_30
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DOI: https://doi.org/10.1007/978-3-030-24299-2_30
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