AI FOR HR NEWS


AI in HR: Navigating Opportunities and Challenges as a Strategic Partner

Human resources is being reshaped by artificial intelligence, a technology that is moving far beyond simple automation and is now viewed as a potential strategic partner. The capabilities of AI are arising from intense development, but they are also emerging from the elusiveness of the technology itself. AI isn't easy; it's complex and, by nature, imparts an intelligence that isn't always easy to see or understand when we set it next to tools of the past. The promise of AI is huge, and for as many potential pitfalls as we can discuss, we can also point to just as many potential rewards.

AI as an Enabler, Not Just an Automator:

One of the main themes is that the most significant potential of AI lies in augmenting human ability, not merely substituting for it. Josh Carty, a researcher at Foundry, drives this point home. "AI is a wonderful tool for taking care of mindless tasks, particularly research," he says, "which allows even more experienced HR professionals to spend the bulk of their time making strategic decisions and managing the workforce in a way that plays right to the unique skill set of HR. " The predications run along two main lines: that autonomous HR professionals will have more freedom to focus on higher-value activities and that, more or less at the same time, HR will be repositioned within organizations to have a greater focus on generally higher-value activities.

Tackling Bias with AI (and Caution):

One of the most compelling uses of AI in HR is its potential to eliminate unfair bias in processes like hiring. Old methods, such as keyword searches based on often-biased job descriptions, can perpetuate inequality. AI, on the other hand, can be taught to ignore bias and focus on the right aspects, such as skills and attributes. It can analyze language for bias and challenge hiring managers when they make potentially unfair decisions. But here's the catch: AI can only do this if it is set up correctly. AI learns from the data it is given; if the data reflect historical biases, AI can amplify them.

Compliance, Governance, and Data Concerns:

Similarly, the responsibilities of AI are significant. HR leaders are growing increasingly concerned because AI involves many unknowns. While part of the unknown is what exactly it can do, and another part is how well it performs its intended tasks (or not), the HCM community seems excited mainly by its potential. And, you know, we just might be on the verge of something big!

The Evolving HR Professional:

The emergence of AI and sophisticated technologies in HR tech is driving an evolution in the profession. HR leaders observe that, for the most part, HR has not been a major player in technology decisions, largely due to a lack of understanding necessary to make informed decisions.

Understanding technology and collaborating seamlessly with the IT function is essential for future HR professionals. Evolving technologies (like AI and machine learning) are creating opportunities for enhanced data-driven decision-making. To fully capitalize on these opportunities, HR needs to improve its data literacy.

Looking Ahead:

Experts view HR integration of AI as being in its infancy. They foresee much deeper integration, some market consolidation, and a strong focus on applying skills analysis and development as the big payoff. They hope for this much more useful AI to help employees and leaders make better decisions 'in the flow' of work, rather than in hindsight. With AI, the world of work can become much richer and more effective.

AI can change HR for the better:

It can increase efficiency, provide deeper strategic insight, and make processes fairer. But these outcomes aren't automatic. Is it happening? To ensure it happens, we have to take a human-centered, thoughtful approach to the tech. We also need to ensure that the HR people are trained, skilled, and ready to work with this powerful tech partner.

The importance of training the AI Model:

The quality of data for training AI models in HR is crucial, especially since the models learn directly from the data provided. Training a model on incomplete and/or inaccurate data suggests that the model may be incorrect, didactic, and/or biased in making predictions; the very opposite of what one seeks in an AI tool.

The notion of a "reliable" AI tool seems to hinge on whether one has a firm grasp of the concept of validity and/or uses proxies for it, such as accuracy, fairness, reliability, and high performance in the real world. A good place to start in generating a reliable HR AI tool is by using good training data.

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