This week’s post is inspired by a 2018 movie called Upgrade. Without giving too much of the movie away, an AI chip is implanted into a paralyzed man to enable him to walk again. Sounds good right? It turns out that this chip can do a lot more than just improve motor functions. The chip amplifies the senses, resulting in a heightened sense of awareness and observation along with the advantages that brings.
As the plot develops, so does the question of who is in control, the man or the AI chip? The point of this discussion is all about control. Who or what do you want to be in control of learning? As you can probably guess, I am in favor of a learner-centric design, giving the learner autonomy over the learning experience. However, there is a lot of buzz around how AI can provide a better, more personalized learning experience.
Can AI really know what is best for the learner? Are we so predicable that we can all be put into a finite number of buckets? If that is the case, how much is AI really personalizing learning? For example, after tracking a series of 10 user actions AI algorithms may suggest one of several changes. This can be represented by the diagram below. After a series of actions (circles) AI offers different paths (dotted lines).
Contrast this to an LI adaptive course that offers the learner different learning paths throughout the course. At any time, the learner has control of choosing a different path. As shown in the diagram below there are many more opportunities to take a different path thus multiplying the degree of personalization exponentially.
This may conflict with our instincts. How can artificial intelligence and machine learning not be more powerful than human intelligence and human control? The leading character in Upgrade faced this challenge. Now, you as a learning developer also face this challenge. Will you rely on the power of AI to personalize learning? Or will you design training that gives your learners ultimate control? The choice is yours – for now.