Written by Dan Hughes, Director of International R&D
Generative AI, including tools like ChatGPT, offers a potentially transformative approach to talent assessment and development with endless possibilities. There are multiple options for leveraging AI as an HR professional to enhance hiring and employee development strategies, but always in conjunction with human oversight. We’ll explore the key considerations to think about, and some examples of how to use generative AI for talent management.
Is ChatGPT generative AI?
Chances are you’ve heard variations of types of artificial intelligence thrown around recently, some you may have been using for years and some that are newer to the technology scene. ChatGPT is one component of generative AI and while both of those terms may sound new, generative AI has been around for decades.
In our recent blogs, we discussed the impact of ChatGPT from two different perspectives. First, we shared some key skills that employees will need to take full advantage of generative AI, such as ChatGPT, moving forward. This echoed themes from our previous research into changing success criteria in the future of work, where we predicted competencies like critical thinking, digital dexterity, learning agility, and change orientation would come to the forefront. We have also explored some of the negative implications of generative AI in talent assessments, like candidates using ChatGPT or other AI-driven chatbots to potentially cheat on talent assessments. This is a great example of how important it is for organizations to maintain good test security and incorporate a range of measures to mitigate the risks that come in this age of artificial intelligence.
The natural language interface of tools like ChatGPT certainly makes generative AI more accessible than ever before, allowing more and more people in talent management to easily and effectively utilize generative AI for business in their day-to-day work.
How to use generative AI for talent assessment and development
It is important to remember that, like other major technological advancements over the years, the focus should be on where this technology can supply a clear benefit over existing approaches, rather than just using it for the sake of doing so. To better understand how to use generative AI, here are six key considerations of applying these tools in talent selection and development:
- Productivity – Will this increase the speed of performing certain talent assessment or development tasks and save valuable time?
- Scale – Will this enable certain approaches or tasks to be delivered at a much larger scale than would be possible with existing approaches?
- Consistency – Will this help to improve the reliability of talent assessment?
- Accuracy – Will this improve precision of measurement in talent assessment?
- Fairness – Will this improve fairness of outcomes for minority groups, reduce bias, or increase access for diverse groups?
- Engagement – Will this increase engagement for candidates in a hiring process or for employees undergoing a development activity?
Always keep these questions in mind when exploring new applications for generative AI in assessments and talent development. At the same time, consider any negative consequences that introducing generative AI might have and how this will be evaluated or audited. For example, it is essential to check that the use of generative AI will not create biased outcomes.
3 examples of how to use generative AI in talent assessment and development
There are huge possibilities for taking advantage of generative AI to enhance hiring and employee development. Here are some interesting examples we have been exploring:
1. Assessment content generation
From our own research and application, ChatGPT can do a reasonable job of suggesting some initial content ideas for talent assessments, such as interviews, personality assessments, and situational judgement tests (SJTs). With other visual and audio-generative AI tools, there is also the opportunity to create multimedia assessment content at a faster pace than has been possible before, which can increase candidate engagement.
While it provides a useful starting point and can save some time, the content generated by these tools tends to have flaws, therefore it is important for human experts, such as I/O psychologists, to review and refine it. Generative AI content can also be repetitive at times, lacking the creativity of human content developers. And, of course, the same principles apply in developing talent assessments. They should be trialed and tested thoroughly to demonstrate evidence of reliability, validity, and fairness.
2. Chatbot-based assessment
The natural language interface of ChatGPT means it can be deployed as a chatbot interview assistant to help assess the personality or competencies of candidates in the hiring process. This type of use of generative AI offers significant benefits for scaling interviews to larger volumes of candidates or assessing candidate personality in a more engaging format than questionnaires.
This type of application needs to be balanced with ensuring that the hiring process keeps some human-to-human interaction or touchpoints within it to foster more candidate engagement. Also, it is important to evaluate whether this approach can achieve the same or better levels of consistency and accuracy in comparison to existing assessment methods. There has already been some promising scientific research in this area, but there is still more research required.
3. Digital work coach
From a talent development side, an interesting application of generative AI is in providing personalized coaching solutions, which can support someone in achieving their individual goals. A chatbot coach can ask questions to explore a specific work challenge the person is facing and help them identify options, solutions, and an action plan for addressing their challenges.
Generative AI has significant potential to democratize coaching by providing 24/7 on-demand services at a much wider scale than is possible with human coaching. At the same time, AI-based coaching is limited in its capabilities and can’t replicate the qualities of human coaches, such as empathy and emotional intelligence. Coaching provided using generative AI may be useful for supporting individuals with narrow, targeted work challenges, but human coaches will still remain essential for deeper levels of coaching which require a stronger connection between the coach and their mentee, an understanding of the nuanced context of work challenges, and an appreciation of the emotional impact.
The future of talent with generative AI
These are just a few examples of how to use generative AI in talent assessment and development. This is an exciting time, and it will be interesting to see how the talent management space evolves as this technology continues to become more widely accessible and develops its capability.
