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AI and Human Resources: Can HR be a key strategic driver for inclusive and diverse AI?



As a professor of human resources and business governance, Anne-Katrin Neyer

conducts research at the intersection of IT and organizational design on topics

related to collaboration, organizational transformation, and innovative human

resources work. Her current research focus is on the interplay of artificial

intelligence and HR in organizations. She holds the Chair of Human Resources

and Business Governance at Martin Luther University Halle-Wittenberg (MLU) in

Germany. Anne-Katrin is involved with Women in AI as Chief People Officer.


1. What is the significance of the use of artificial intelligence in human resources management?

Artificial Intelligence (AI) has the potential to change HR processes, standardize them, and make them more objective. Algorithms form the basis. These have an influence, for example, on applicant selection and personnel development. One of the crucial questions is therefore how these algorithms are trained and developed in the respective company or organization. To ensure diversity in career trajectories, the systems need to be designed in a non- discriminatory manner.

2. In your view, why does HR need to play a strategic role to foster diversity and inclusion in AI?

Inclusive and responsible AI is not happening by chance. In its Global Gender Gap report (2021) the World Economic Forum emphasizes that newly emerging jobs (such as Artificial Intelligence Specialists or Big Data developers) are deeply unequal. These findings are worrying given that experts representing the various stakeholders in an organization's ecosystem need to be involved in the generation, acquisition, transfer, analysis, and implementation of AI and data- driven knowledge. This is not just about fairness and ethics, this is a question of how to create value for organizations and the common good. Strategic HRM is thus required to systematically develop a people strategy to foster diversity in AI.

3. What needs to be the focus?

To gain a better understanding, I suggest focusing on three levels for inclusive and diverse AI in Strategic HRM. The first level looks at the task dimension, i.e. job description and job branding. The second level looks at the functional dimension, i.e. is HR itself ready to meaningfully work with data? The third level looks at the cultural dimension and thus, the question, of whether diversity and inclusion are not only defined but actually lived as a core strategic value in the company.

4. Can organizational development help create an inclusive and diverse AI workforce strategy?

According to our research, organizational development can contribute to diversity in AI, if it develops an appropriate strategy, shapes culture, and changes structures to create an inclusive work environment. One of the proposed solutions to balance human and artificial intelligence in decision-making is to work with so-called human-in-the-loop systems. This means that humans interact with AI and try to maintain control by overriding AI decisions (Enarsson et al., 2022). Therefore, diverse teams are needed to do this in an open and unbiased way. New approaches to human resources such as learning analytics have the potential to foster the development of competencies and skills required in teams to enable an inclusive AI approach. These include, for example, interdisciplinarity, creativity, and self-reflection.

5. What is your advice to companies that want to act sustainably here?

It is important to improve data literacy in HR to raise awareness of potential bias. For companies, this pays off on multiple levels. The 2022 WAI report "WAI@WORK - Shaping the future of work for women in AI" concludes, that companies with greater diversity is not only proven to perform better financially but building a representative workforce also attracts new talent and fosters a culture of diverse idea sharing.

Experiment with AI and data-driven HR tools to evaluate their benefits and weaknesses. Be a role model by bridging the gap between human-centric focus and data support. And most importantly, go hands-on. This is not a tick box exercise. Thank you very much, Anne-Katrin, for your commitment and your research.

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Prof. Dr. Anne-Katrin Neyer, Martin-Luther-Universität Halle-Wittenberg https://personal.wiwi.uni-halle.de/team/neyer/ Wirges, F., Neyer, AK. Towards a process-oriented understanding of HR analytics: implementation and application. Rev Manag Sci (2022). https://doi.org/10.1007/s11846-022-00574-0 KI-HR-LAB https://ki-hr-lab.de/


References: Therese Enarsson, Lena Enqvist & Markus Naarttijärvi (2022) Approaching the human in the loop – legal perspectives on hybrid human/algorithmic decision-making in three contexts, Information & Communications Technology Law, 31:1, 123-153, DOI: 10.1080/13600834.2021.1958860 https://www.weforum.org/reports/global-gender-gap-report-2021/infographics- ad8db6203f The WAI Report (2022) “WAI@WORK - Shaping the future of work for woman in AI“ https://www.womeninai.co/wai-at-work

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