Rethinking AI In Learning Beyond Automation
Artificial Intelligence (AI) has quickly become one of the most effective ways to produce and deliver training content to individuals. It is capable of producing a course in minutes, responding quickly to questions, identifying and recommending training resources for the learner before they are even aware of the need, and providing "personalized learning at scale." The potential capabilities of AI in Learning and Development are exceptional.
However, many companies are now realizing that faster does not always mean better when it comes to learning. The question is not about whether or not AI is capable of achieving its many functions (it can), but whether AI allows individuals to use higher levels of critical thinking and creativity or simply assists individuals in completing the tasks required.
How AI Fixes Our Problems (And Why We Love It)
Let's be real: when it comes to training and the learner's journey, AI provides solutions for all the problems and challenges that exist today. Most learners do not struggle with the subject matter's complexity; instead, they face difficulties because they can't find answers quickly enough and/or don't feel that the training material is relevant to their job.
That is where AI provides solutions that can benefit learners the most. With AI-based learning, learners receive information in real-time based on their performance, allowing them to troubleshoot issues immediately and receive feedback from both the tool and an administrator without waiting. For many corporate professionals, this capability provides them with significant advantages, as it has transformed learning from something that occurs once a month to something available at any hour.
The ability to provide support for learners makes learning easier to navigate. However, just because a tool is easy to navigate doesn't mean it is necessarily providing the best training for learners.
The Speed Of Learning Can Obscure Shallow Understandings
A common concern among Learning and Development teams is that learners are completing courses at record speeds; however, their ability to retain, apply, and make reasonable decisions based on the information they learned has not improved nearly as much. When we provide answers instantly, we eliminate the opportunity for reflection. AI provides solutions with a remarkable capability to provide "what's next"; however, it doesn't do a good job of forcing learners to live with uncertainty, explore their choices, and wrestle with complexity: all necessary components of deep understanding.
For instance, if the learner receives an answer immediately, was learning accomplished (or did the learner simply locate the answer)? Although AI does not detract from the learning experience, it can prioritize efficiency over understanding unless it is designed with intent.
The Data Gleaned From The Learner Feedback
Learners are willing to seek guidance from an AI system but prefer to utilize human input for assistance with context, judgement, 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 the following:
- Humans can challenge and encourage learners to think in new ways.
- Humans can share their personal experiences of how and why things have value.
- Humans explain the importance of different things.
- Humans can read the emotional signals that others send.
- Humans can determine when it is appropriate to "bend the rules."
Also, the contrast between the roles a chatbot and a human play makes an important distinction in the areas of leadership development, ethics, customer service, and problem-solving. When a learner learns how to think clearly and apply whatthey have learned to a problem, the learner is better equipped to think independently and critically than they would be if they only knew how to do something.
Final Thoughts
AI will affect the future of learning in ways that are impossible to define today simply as either AI or human-based. In the future, Artificial Intelligence technologies will provide users with the means to create educational experiences that are engaging to both students as well as educators. Using Artificial Intelligence to measure success should not be based upon the speed at which learners complete courses. Rather, learning experience success should be gauged by how learners will use the knowledge, skills, and experiences gained from the course once they complete that course.
