As generative AI and machine learning technology continue to gain mainstream popularity, learning and development (L&D) professionals and educators alike need to understand better how best to manage the impact that AI will continue to have on L&D programs and education.
Incorporating AI into L&D and education has the potential to lead to improved learner outcomes, enhanced accessibility, better data-driven decision-making, and increased efficiency. While there are significant opportunities, it is essential to address ethical considerations, ensure data privacy and maintain human oversight to safeguard the responsible use of AI tools.
As we look to the future, we will need to consider how best to incorporate this technology into assessment strategies to take advantage of the opportunities it presents while also understanding the challenges of generative AI and machine learning technology.
A Unique Opportunity to Revamp Assessment Strategies
The release and commoditization of AI programs have produced a unique opportunity for positive disruption within the assessments and learning space. For education leaders and L&D experts, improving assessment and teaching quality is no longer tied to limits on time, money, or resources.
With large language models (LLM) like ChatGPT, AI can be applied effectively across huge swathes of the learning and assessment processes, from content creation to scoring and marking and creating tailored learning experiences for students. Traditionally, these assessment areas were impacted by time and budget, often resulting in a learning experience that was compromised and one-size-fits-all. With AI as a support, all areas of education – be they in academia or corporations – can now benefit from a higher quality of individual formative learning, assessment, and teaching than was previously feasible.
This expected shift has further fueled the discussion on what makes a good assessment and whether traditional exams and assessment formats are truly successful in demonstrating the actual skills or knowledge required. With AI-assisted assessment and learning capabilities, we might see a complete reversal of the standardized testing system often used in schools and organizations around the world, instead favoring a student-centric approach that better surfaces skill and knowledge.
Understanding the Challenges of AI
When considering how to incorporate AI into assessments and learning, it’s important to acknowledge the challenges that can come with it.
For both L&D professionals and educators, it’s unsurprising that one of the biggest concerns that the technology has brought up is its ability to assist with test fraud and cheating. Ironically, it might also be one of the more manageable challenges associated with the tech.
Yes, the use of tools like ChatGPT are a potential new way for test takers to cheat, but as with other technologies, this simply forces us to adapt, and like those technologies, it will change the kinds of skills we value in people and the kinds of things we test. To manage this new avenue for cheating will mean organizations will need to implement good test fraud prevention strategies, which include creating strong anti-cheating policies, randomized testing, and proctoring solutions—to name a few.
For other valid challenges, such as the legal ramifications and the concerns around data privacy, the solution is trickier. With the tech moving faster than governments and legal agencies can keep up, managing the risks means keeping AI as an assist-to-humans tool, rather than something left unchecked to make decisions.
From a learning perspective, there are also questions around a lack of transparency within AI tools which can act as ‘black boxes’, making it nearly impossible to understand how the technology comes to its conclusions. This can lead to inherited biases from the data sets used to produce content, potentially resulting in biases toward race, gender, or socioeconomic status.
Interestingly, some of these challenges, like bias or test cheating, may well end up being solved by the very AI tools that are now raising concerns. It’s simply too soon to say.
What we do know is that in the short-term, organizations in both the L&D and education space need to approach AI as an assistant to experts, allowing them to leverage the opportunities and manage challenges.
The Future of AI in L&D and Education
AI is in its infancy and will only continue to improve. For organizations to remain competitive, this means they will eventually need to incorporate its use into the mainstream.
As we’ve seen with the introduction of the internet, as the labor market adopts AI into everyday operations, organizations everywhere will need to follow suit. AI will facilitate valuable enhancements in the assessment space, allowing for a more personalized learning approach by leveraging data and adaptive algorithms to tailor assessments to individuals, allowing for intelligent tutoring systems that can provide personal guidance, feedback, support, and data-informed content creation.
This saved time and ability to deliver more valuable learning processes without stretching budgets will eventually make AI management a key skill for L&D and education professionals the world over.
