When AI hires people: Why ethics matter more than ever in recruitment and selection

Author: Martina Mori, University eCampus, Italy

Artificial intelligence is no longer a futuristic concept in hiring: it is already reshaping how organisations recruit and select talent. According to a survey by the Society for Human Resource Management, nearly 80% of employers now use AI or automation in recruitment and selection. Algorithms screen CVs, rank candidates, analyse video interviews, and even predict future performance.

But as organisations rush to adopt these tools, a crucial question often remains in the background: just because AI can make recruiting and selection faster and cheaper, does that mean it also makes it fairer, more transparent, or more responsible?

This blog draws on the findings of the recent article “A systematic literature review on artificial intelligence in recruiting and selection: a matter of ethics” by Mori, Sassetti, Cavaliere and Bonti (2025), published in Personnel Review. In the study, the authors systematically reviewed more than 120 academic contributions to examine how ethical concerns shape the use of AI in recruitment and selection.

Three Ethical Lenses to Understand AI in Recruiting and Selection 

This publication shows that discussions about AI in recruiting and selection tend to cluster around three main ethical perspectives, each highlighting different risks and opportunities.

1. Efficiency: The Utilitarian View

From a utilitarian perspective, AI is often praised for its ability to optimise recruitment and selection processes. Automated systems can handle large volumes of applications, reduce time-to-hire, and support more data-driven decisions. For organisations facing intense competition for talent, these benefits are compelling.

However, efficiency gains mainly reflect organisational interests. Research shows that some candidates are less willing to apply when AI plays a dominant role (especially in interviews) perceiving these systems as impersonal or opaque. In other words, what is efficient for the organisation may not always be optimal for applicants.
For practitioners, the implication is clear: AI should augment, not replace, human judgment, and its use must be clearly communicated to candidates.

2. Fairness: The Justice View

A second stream of research focuses on justice and fairness. While AI is often presented as a way to reduce human bias, algorithms can reproduce existing inequalities if trained on biased data.

Candidates’ perceptions of fairness depend not only on outcomes, but also on how decisions are made. Transparency about evaluation criteria, the role of human recruiters, and opportunities for explanation all influence whether AI-supported hiring is perceived as legitimate.

Ethical AI, therefore, is not just a technical challenge—it is a relational and organisational one, requiring attention to communication, accountability, and procedural clarity.

3. Rights: The Legal and Human Rights View

The third ethical lens concerns privacy, consent, and data protection. Practices such as cybervetting (screening candidates through online and social media information) often occur without applicants’ awareness, raising concerns about invasiveness and legal compliance.

In a context where regulation is still evolving, scholars increasingly emphasise human rights principles as a baseline for responsible AI use. For policymakers, this points to the need for clearer guidance on acceptable data use, algorithmic accountability, and the protection of candidates’ fundamental rights.

Toward Responsible AI in HRM

One of the key messages emerging from this study review is that no single ethical perspective is sufficient on its own. Responsible AI in recruiting and selection requires integrating efficiency, fairness, and rights into a coherent approach to HR decision-making.

The authors propose an integrative framework that connects AI in HRM with stakeholder theory, sustainable HRM, and transparency management. This perspective recognises that decisions in recruiting and selection affect not only organisational performance, but also candidates’ trust, dignity, and access to opportunities.

A Call to Action

For organisations, ethical AI should be seen as a strategic investment, not a constraint. Transparent communication about how AI is used, collaboration between HR professionals and AI developers, and continuous monitoring of candidate experiences can enhance both legitimacy and employer attractiveness.

For policymakers and researchers, the challenge ahead lies in developing clear, evidence-based standards that ensure AI supports inclusive, lawful, and human-centred recruiting and selection practices.

AI may be transforming these processes—but ethics will determine whether this transformation truly benefits organisations, workers, and society at large.

References

Mori, M., Sassetti, S., Cavaliere, V., & Bonti, M. (2025). A systematic literature review on artificial intelligence in recruiting and selection: a matter of ethics. Personnel Review, 54(3), 854–878. 

Author Bio:

Martina Mori is a tenure-track researcher in Organisational Behaviour at the University eCampus (Italy). Her research focuses on employee voice, participation, leadership, and the impact of AI in human resource management.