Key Takeaways:
- By integrating ethical considerations into the design and implementation of AI systems, organizations can create a more supportive and empowering employee experience while avoiding potential biases and discrimination.
- Successful utilization of AI in HR requires collaboration among data engineers, HR professionals, and ethics experts.
- HR departments must evolve to become proficient in AI technologies, emphasizing the importance of choosing the right data and understanding algorithm behavior.
In the ever-evolving world of HR technology, where the boundaries of possibility are constantly being pushed, one principle remains steadfast: ethical AI. It's not just about innovation — it's about harnessing the power of artificial intelligence with integrity and empathy. At the intersection of human resources and cutting-edge AI lies a pivotal juncture that can redefine the employee experience. One where ethical AI becomes the catalyst for creating a workplace that truly understands, supports and empowers its people.
Artificial intelligence can also be used for process automation, allowing us to optimize our work and become more efficient. On the other hand, it will enable us to make correlations that are not immediately obvious — if they were, of course, human intelligence would suffice!
Combining these two factors can significantly improve our HR processes, but the algorithm cannot think for itself. That’s why it’s essential to talk about ethics and consider how to incorporate algorithm behavior into the design stage.
We cannot ignore the fact that AI creates uncertainty and risk, and the field of HR is no exception.
One commonly discussed example is using unfiltered people data for a recruitment algorithm that results in gender-based discrimination. This kind of situation has occurred because, often, programming AI is based on having a lot of data and searching for repetitive patterns within that historical data. The data can reflect outdated realities — for example, that most people holding certain positions are men.
For this reason, companies that work with automation have a responsibility to bring together data engineers, HR professionals and ethics professionals in order to use this technology effectively.
There are many reasons to innovate in this area as these elements have become more evident in recent times:
- Speed
- Volume
- Rapid changes
- The limitations of traditional manual processes
For example, let’s consider a company that wants to adapt to change and adopts a learning strategy based on reskilling. A manual process is limited in both capacity and quality; thus, automating AI processes will help us manage these processes faster, ensuring they are helpful.
But in order to achieve this, HR departments will have to be updated and become “experts” on AI — or, more accurately, expert users of AI. Here are two key considerations:
- Choosing the right data — What data are we using to create these algorithms? If we use historical data, this can have consequences we need to consider during design.
- Using the algorithm — Once the algorithm has been implemented, its users — i.e., HR teams — will have to learn how the AI works to assess the accuracy of its results, correct errors, reduce risk and contribute to improving AI.
This phenomenon will open up new jobs within HR departments while offering an excellent opportunity for this department to expand its skills — upskilling and reskilling.
We focus our innovation on ethics at Cornerstone, remembering these seven requirements for ethical AI — human agency and oversight, technical robustness and safety, privacy and data governance, transparency, diversity, non-discrimination and fairness, societal and environmental well-being and accountability.
AI is a very powerful tool. How it’s used depends on us, the HR professionals.
Dive into our eBook to uncover the principles and methodologies that define Cornerstone's commitment to responsible AI.
