AI & Skills– Your Questions Answered

August 18, 2021 Cyril Le Mat

 

Getting your head around the role of AI in HR and skills development can be daunting at times, especially if you’re not as familiar with the technology. At Cornerstone, we’ve been attending and hosting many virtual events on the topic of AI in HR during the past year. Often at these events, there are questions and concerns about the technology that are regularly asked so we’ve decided to pick the best ones and answer them publicly in this blog.

Whether it’s identifying employee’s skills gap, finding out how algorithms work or the ethics behind AI, here are some of the common questions and our answers around AI and skills.

  1. How do you detect a gap in an employee’s current skillset?

There are several ways to detect gaps within an individual employee’s profile, and not all of them require technology or AI. In fact, the first step is understanding and having open and honest conversations with your employees about what their skills are, their career aspirations and the importance of training and learning. Hammering home this message can naturally surface gaps, provided the environment and relationship is open enough. AI can also help identify skills gaps, by matching employees to various skills from a skills repository (such as the Cornerstone Skills Graph) and then seeing where there might be disparities. AI can then suggest training and learning content to help them increase their skills and ultimately close the gap. It’s important to note though that AI and learning programmes alone, cannot completely solve the skills gap. A continuous learning culture must be developed so that employees see the value in learning and training.

  1. What data sources are used to generate the list of 52,000 skills and subsequent clusters in the Cornerstone Skills Graph?

The Cornerstone Skills Graph uses technology from Clustree (acquired by Cornerstone in 2020), the world’s largest skills engine that pulls skills data from public, institutional and customer-contributed databases across every industry globally. The skills engine can also be integrated with other skills libraries to create an unlimited catalogue of relevant skills for any position.

  1. Are there potential ethical issues around the use of AI in this context?

The notion of algorithms will, of course, create uncertainty and risk. In the context of HR, where it’s very much about dealing with people data that is sensitive and personal, the ethical risks are higher. One  possible ethical issue with AI in HR could be gender-based discrimination. If your organisation is traditionally male dominated, for example, the AI may notice that particular pattern and naturally suggest male candidates for new roles. This kind of issue goes deeper than the technology itself, but it can cause damage to the company’s reputation and trust, if it comes to the surface. Regulation and guidelines are constantly being developed and evolving to mitigate potential ethical issues, such as the “EU’s Ethics guidelines for trustworthy AI”, but it’s also important that data engineers, HR and ethics professionals regularly assess the AI they’re using to ensure it’ is serving its purpose within the organisation.

  1. After a skill has been detected using AI, how do I know if the employee is really competent on that skill?

Skills development is ever changing. As technology and digitalisation continues to progress around us, current skills evolve, and new skills emerge. This means that using AI isn’t necessarily about measuring how well an individual employee can perform a certain skill, because it could very quickly change. Instead, it is about understanding the skills that your employees have and expanding on them through suggested trainings. For example, the Cornerstone Skills Graph can help to detect certain skills within an organisation by matching existing skills that are linked to that term. It can then offer training content to employees that want to bolster or develop these skills. It’s also worth bearing in mind that using AI to identify and analyse employee skills is only the first step in the employee skill development journey and ultimately, any final decision should still be made by a human. Having approval processes with managers regarding employee’s skills can be a way to ensure the employee has full competency.   

  1. Do we risk missing out the 'unconscious' strengths of human beings? e.g., Project Managers who are excellent creatives because they've never done the 'job'?

Organisations shouldn’t solely rely on AI to identify skills in organisations, rather it should be used as a supporting technology. With any type of technology that offers suggestions and predictions, ultimately the final decision is made by a human, which is important to remember when using AI. It’s about balancing the technical capabilities of AI, the judgement of line managers and the trust of employees. Organisations that use AI strategically will be the ones that see the most benefit with skills development.

Want to hear about how DPDHL used AI to boost its skills strategy? Read their story, here. You can also find out more about our Cornerstone Innovation Lab for AI, here.

 

About the Author

Cyril Le Mat

Cyril Le Mat is a Data Science executive with over 10 years of experience building data teams and machine learning products for startups and tech companies. After graduating from the Ecole Centrale de Nantes with a master’s degree in mathematics and computer science, he worked as a Management Consultant and Data Analyst for various companies. He then joined several French startups as Head of Data Science : Cheerz (acquired by cewe) and HostnFly. In 2018, he joined Clustree, a HR Artificial Intelligence platform focused on skills framework and careers,where he built a technology that surpassed the state of the art of the market and was acquired by Cornerstone OnDemand. He is now an international expert in Artificial Intelligence applied to HR, developing machine learning products at Cornerstone OnDemand.

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