Rethinking AI in learning beyond automation
Artificial intelligence (AI) has quickly become one of the most effective ways to create and deliver training content to individuals. You can create courses in minutes, respond quickly to questions, identify and recommend training resources before learners even know they need them, and deliver “personalized learning at scale.” The potential of AI in learning and development is extraordinary.
However, many companies are now realizing that faster doesn’t necessarily mean better when it comes to learning. The question is not whether AI can (and can) accomplish its many functions, but whether it will enable individuals to engage in higher levels of critical thinking and creativity, or whether it will simply assist individuals in completing necessary tasks.
How AI can solve our problems (and why we love it)
The truth is, when it comes to training and the learner journey, AI offers solutions to all the problems and challenges that exist today. Most learners do not struggle with the complexity of the subject matter. Rather, they face challenges because they can’t find answers quickly or don’t feel the training material is relevant to their job.
AI therefore provides solutions that will best benefit the learner. With AI-based learning, learners can receive real-time information based on their performance, so they can troubleshoot issues immediately and receive feedback from both the tool and administrators without waiting. For many corporate professionals, this feature is a huge benefit as it transforms learning from once a month to anytime learning.
You can provide support to your learners, making it easier for them to progress. However, just because a tool is easy to operate doesn’t necessarily mean it provides the best training for learners.
The speed of learning can obscure shallow understanding.
A common concern for learning and development teams is that learners are completing courses in record time. However, their ability to retain and apply learned information and make rational decisions based on it has not improved significantly. If you give an answer right away, you miss the opportunity to think. AI offers solutions with great capabilities that provide “what’s next?” But forcing learners to live with uncertainty, explore options, and grapple with complexity—all necessary ingredients for deep understanding—doesn’t work.
For example, if a learner receives an answer immediately, is the learning complete (or did the learner simply find the answer)? AI doesn’t take away from the learning experience, but unless it’s purposefully designed, it can prioritize efficiency over comprehension.
Data collected from learner feedback
Learners actively seek guidance from AI systems, but prefer to use human input to support context, judgment, and decision-making. The differences between AI systems and humans can be attributed to a number of distinguishing characteristics. Examples include, but are not limited to:
Humans can challenge and encourage learners to think in new ways. Humans can share personal experiences about how and why things are valuable. Humans explain the importance of different things. Humans can read emotional signals sent by others. Humans can decide when it is appropriate to “bend the rules.”
The contrast between the roles played by chatbots and humans also makes important differences in the areas of leadership development, ethics, customer service, and problem solving. When learners learn how to think clearly and apply what they have learned to problems, they become better able to think independently and critically than if they only knew how to do something.
final thoughts
AI will impact the future of learning in ways that are impossible to define today simply as either AI or human-based. In the future, artificial intelligence technology will provide users with the means to create engaging educational experiences for both students as well as educators. When using artificial intelligence to measure success, don’t base it on how quickly learners complete a course. Rather, the success of a learning experience should be measured by how the learner uses the knowledge, skills, and experience gained from the course after completing it.
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