Should Human Resources use Artificial Intelligence?

In recent years, there has been an increasing interest in big data, machine learning, algorithms and work automation [1]. As these concepts cease to be ‘alien’ and come to belong to the common lexicon of our organizations, Human Resources Management should focus on the discussions that circle around the modern workplace: longevity of careers, the complexity of the work environment derived from the exponential adoption of new technologies, emerging new skills, cross-functional expertise, diversity and inclusion.

These points of reflection are extremely important but what happens when this revolution directly impacts the HR function? The question is not only what to do, or how to do it. The question must always be: why do it? Why should HR adopt machine learning or artificial intelligence?

The HR function, in the last decades, quickly evolved from being an administrative-based set of tasks, focused on compliance and operational support, to a highly complex and strategic business partner. But this evolution did not happen by itself, it was a long process of environmental and organizational change that was influenced by globalization and rapid technological disruptions.

Data gathering and management is the ‘Oil of the 21stcentury’. New organizations, that are decentralized and globalized, created a new form of economy, platform economy, where data is the trading stock between the client and the investor. Companies such as Google, Amazon, Facebook and Apple (intelligently named GAFAnomics) generate, daily, large quantities of data that are vital to their sustainability and enhance their productivity, commercial reach and financial performance.

Human Resources, no matter the industry in which it operates, should use artificial intelligence to help manage the data that is produced in the modern workplace. Nonetheless, this process must never replace the human intervention in what is central to people management.

The application of AI in HRM must be sought as a new tool that enhances our capabilities to adopt a new approach to the world of work: an evidence-based practice [2]. This new approach allows a problem-focused approach based on evidence-oriented critical thinking, releasing our practice from the common mistakes from our past, such as relying on intuition or solutions that worked well in the past (availability heuristic) [3].

Common applications of AI in human resources include candidate sourcing (for talent acquisition), resume screening (in order to avoid gender or ethnic bias), automation of administrative tasks and employee behaviour prediction. It is now a common realization that HR must leverage its intervention on predictive analytics, by using sophisticated algorithms, to forecast new trends in organizational behaviour, such as employee intention to quit or identification of traits that are positively associated with high performance.

Whilst there seems to exist clear reasons for adoption of these methodologies, a recent Report published by Linkedin, in 2018, reveals that only 22% of the firms surveyed have adopted advanced analytics in their Human Resources practices [1, 4].

Debates on ethical decision making and data privacy remain heated, and it seems that some cases of data usage are still morally questionable. A strategy for the collection, storage, usage, and distribution of data should be available and clear to all stakeholders, highlighting the tangible value of AI in the workplace.

Fields such as Marketing or Business Development already rely on AI and data analytics on a daily basis. For Human Resources, that horizon seems to be, still, somewhat far away but approaching at a high velocity. It is our duty, as academics and/or HR professionals, to welcome change and lead the effort to start this discussion in our organizations and work teams.

The future is undoubtedly going to be digital, bits and bytes will progressively replace nuts and bolts. In comics there is a wise saying, “…with great power there must also come – great responsibility”.Let’s make sure that, no matter how amazing and powerful these new technologies can be, we never forget to start the debate by asking “why”.

References

[1] Cappelli, P., Tambe, P., & Yakubovich, V. (2018). Artificial Intelligence in Human Resources Management: Challenges and a Path Forward. Available at SSRN 3263878.

[2] King, K. G. (2016). Data analytics in human resources: A case study and critical review. Human Resource Development Review, 15(4), 487-495.

[3] Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive psychology, 5(2), 207-232.

[4] LinkedIn (2018). The rise of HR analytics.

José Sintra, Organizational Psychologist, Content Editor & Advisor @Bound.Health