Systematizing Audit in Algorithmic Recruitment

Business psychologists study and assess relevant individual differences, such as intelligence and personality, in the context of work. Such studies have informed the development of artificial intelligence systems (AI) designed to measure individual differences. This has been capitalized on by companies who have developed AI-driven recruitment solutions that include aggregation of appropriate candidates (Hiretual), interviewing through a chatbot (Paradox), video interview assessment (MyInterview), and CV-analysis (Textio), as well as estimation of psychometric characteristics through image-(Traitify) and game-based assessments (HireVue) and video interviews (Cammio). However, driven by concern that such high-impact technology must be used responsibly due to the potential for unfair hiring to result from the algorithms used by these tools, there is an active effort towards proving mechanisms of governance for such automation. In this article, we apply a systematic algorithm audit framework in the context of the ethically critical industry of algorithmic recruitment systems, exploring how audit assessments on AI-driven systems can be used to assure that such systems are being responsibly deployed in a fair and well-governed manner. We outline sources of risk for the use of algorithmic hiring tools, suggest the most appropriate opportunities for audits to take place, recommend ways to measure bias in algorithms, and discuss the transparency of algorithms.

An exploration of preferred teacher characteristics and hiring tools in Belize

PurposeThe purpose of this paper is to answer the following research questions: what characteristics do key Belizean educational leaders value in teacher applicants and why? What hiring tools do they use to ascertain whether teacher applicants have the characteristics they prefer?Design/methodology/approachThe authors utilized a mixed-methods approach drawing upon three data sources – face-to-face interviews with Belizean educational leaders, field notes, and government documents. A card sorting activity of applicant characteristics and tools was embedded into the interview.FindingsInformants preferred motivation, caring, subject matter knowledge, and teaching skills. Intelligence was perceived as a potentially negative characteristic unless coupled with other characteristics, such as strong teaching skills, motivation, and caring or the umbrella of other characteristics, such as content knowledge or university training/credentialing. Professional characteristics, such as where one went for teacher training and academic performance, were perceived as having less relative importance than personal characteristics. Least important were applicant demographics. Consistent with the extant literature, Belizean informants perceived the interview, evidence of prior experience, and certification as the most important tools in vetting and hiring applicants.Research limitations/implicationsThe exploratory study is limited by the small sample of informants, but provides insights into preferences for applicant characteristics and hiring tools in an understudied international context. This study informs future research that may seek to survey representative samples of various stakeholder groups (i.e. general managers and principals) for their preferences in applicant characteristics and hiring tools from across Belizean schools and educational providers.Originality/valueThe study adds to limited research on preferred teacher characteristics among educational leaders responsible for hiring and/or working with teachers and to the limited international educational leadership research.