On the present-future impact of AI technologies on personnel selection and the exponential increase in meta-algorithmic judgments

Abstract

The ongoing implementation of new AI technologies in both public and private organizations has already had a great impact on professional judgment and decision-making processes. For many experts working with people’s applications tied to, e.g., welfare services, employment, school admission, parole, and insurance, algorithm-based decision assistance has already changed the way they perform their assessments. Yet we are still in what seems to be the early stages of this socio-technological transformation. Based on interviews with twenty-four expert recruiters, the purpose of the study is to explore their professional views and expectations concerning the present-future impact of AI on personnel selection. The study seeks to shed new light on the exponential increase in meta-algorithmic judgments, a concept that pinpoints the fact that many experts today must handle algorithmic assessments before moving forward in the decision-making process. What do the respondents think has motivated this socio-technological change, and what do they expect will happen to the role of human judgment in the future? The analysis suggests that the seemingly inevitable existence of human biases and the lack of efficiency in traditional recruitment are, according to all respondents, the main reasons why AI should be used, given its promise to improve both fairness and time management. While AI recruitment systems will most likely become increasingly sophisticated, most respondents thought that these systems would nevertheless never be able to fully replace human judgment. However, a handful of respondents deviated from this majority view by instead expecting that AI would take over the whole process in the not-too-distant future. • New AI technologies are already transforming the selection and decision-making practices in hiring. • An exponential increase in meta-algorithmic judgments, i.e., professionals having to handle algorithmic assessments before taking the next step in the decision-making process. • Qualitative interviews with expert recruiters, focusing on their imagined futures and expectations (hopes and fears) about how the next-coming AI may come to change their profession. • A typology of meta-algorithmic judgment is introduced and analyzed in relation to the empirical study.

Ähnliche Arbeiten