A commonly accepted view is that in the near future, Artificial Intelligence will replace a vast amount of jobs.
Automatization is of course nothing new, but what’s different is the nature of the jobs replaced. We already have
technology that drives cars better than us
(most of the time anyway), and the novel AI solutions in medicine,
pharmaceuticals and financing perform things human beings could never do. But as Kai-Fu Lee states in his
excellent Ted Talk, there are some things that humans are going to excel at for a long time.
Things like empathy
and compassion. Things we actually consider to be the cornerstones of humanity.
Because of this, teaching is probably going to be one of the last jobs to be completely replaced by artificial
intelligence. This does not mean that the new technology isn’t useful for teachers. On the contrary. AI-driven
learning analytics can provide many useful insights for the teacher (and the learner as well). For this,
multifaceted and reliable data about students’ learning processes should be collected, processed and made
available to the teacher. Although self assessment and surveys are great tools, they alone can’t be used as a
basis for objective analytics. For reliable analytics data, we need technology that collects the data
automatically, ethically and privately.
But even the best of what technology and AI has to offer can’t reliably run the classroom alone. Traditionally, learning analytics make decisions based on data limited to school work. And this is of course a good thing. With recent examples of companies collecting and utilizing way more data than they were supposed to, keeping students’ personal data safe is paramount. The problem is that the things happening outside the classroom may have a huge effect on in-class performance. We all know that if there are problems at home, this will likely affect schoolwork. However, an adaptive AI system has no idea about these problems. And it shouldn’t have. But it still makes wrong decisions because of this.
So why not get the best of both worlds. We can combine teachers’ human empathy, compassion and their knowledge of
their own students with AI-driven learning analytics, and train the teachers to read, understand and apply the
analytics. This way, the decisions can be made based on the latest, objective information but with a human touch.
Lot of experts think that the real winners in the job market are the experts who can work with artificial
intelligence. Teachers and AI-assisted analytics make a perfect 21st century teaching team. And the greatest thing
is that there are only winners in this game.
