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Legal aspects of artificial intelligence in the employment process

Author

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  • Helga Špadina

    (Faculty of Law, University J. J. Strossmayer, Osijek (Croatia))

Abstract

The introduction of artificial intelligence in all domains of life is the most transformative process in recent history. It is also a highly dynamic process, and due to the pace of technological development, a very limited legal framework is available to address issues of human rights, ethics, transparency, privacy, safety and accountability. During the last few years, artificial intelligence started to reshape employment processes. Positive aspects of the introduction of AI in the employment process are efficiency and quality in job matching, digitalisation and acceleration of the process, ability to process large data and match job seekers to available vacancy announcements, the alleviation of administrative burdens of employees of employment agencies and giving them strategic and innovative roles. All these are indispensable in present times when demographic challenges in European countries are leading to increased labour migrations and require changes in the recruitment process. The paper explores the current challenges of AI, i.e. how to achieve human-centred values and fairness of AI use during the employment process, preventing algorithmic bias and discriminatory application of AI tools. In order to harness the maximum benefits of AI, we need to develop a regulatory framework that would be enforceable, inclusive and adaptive (OECD), particularly knowing that most AI solutions are privately owned and developed for commercial purposes.

Suggested Citation

  • Helga Špadina, 2023. "Legal aspects of artificial intelligence in the employment process," Stanovnistvo, Institute of Social Sciences, Belgrade, Serbia, vol. 61(2), pages 167-181, December.
    • Handle: RePEc:eto:stanov:v:61:y:2023:i:2:id:546
    DOI: 10.59954/stnv.546
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    References listed on IDEAS

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    1. Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 31-50, Spring.
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