Our children’s education is vital. And we are on the cusp of a pedagogical revolution, an upending of traditional instruction. We must invest now to keep education lock-step with technological progress.
Automation, machine learning, and artificial intelligence may be serving up the greatest challenge we have ever faced when it comes to education. As these technologies displace jobs at faster and faster rates, we’ll increasingly need a workforce that’s adaptable. We need people who are not just ready for some of tomorrow’s jobs. We need people who are ready for any of tomorrow’s jobs. We need a population that can learn new skills incredibly quickly and can perform complex problem solving across multiple domains.
Fortunately, the same forces disrupting the labor market can be harnessed to disrupt our educational system. Machine learning and artificial intelligence can assist in creating a generalized and flexible curriculum that trains a population of thinkers who can seamlessly transition between careers.
The technology is here, but in its infancy. MATHia is a machine-learning tool that aims to personalize tutoring. It collects data on students’ math progress, provides tailored instruction, and helps students understand the fundamental aspects of mathematical problem solving. Intelligent Tutoring Systems can assist in human-machine dialogue helpful in learning new languages.
These are admirable approaches, but they lack the much-needed problem-solving punch to train truly adaptable individuals across many domains. They fail to tap into what truly makes for effective teaching. A consensus report from the National Academy of Sciences (NAS) states that mentorship in the form of continuous and personalized feedback is key to effective learning. This is a far cry from the current state of education, wherein students are taught in large classrooms and assessed for rote knowledge on standardized exams.
According to the NAS, “accomplished teachers…reflect on what goes on in the classroom and modify their teaching plans accordingly. By reflecting on and evaluating one’s own practices…teachers develop ways to change and improve their practices.”
Thankfully, continuous reflection and improvement are the bread and butter of machine learning algorithms. AI will therefore be adept at delivering personalized feedback to every single student. This feedback, in turn, will provide students with the cognitive toolbox to transfer knowledge between a litany of different subjects.
The current lack of knowledge transfer is at the crux of today’s workforce debates: arguments are abundant on how to “reskill” workers displaced by automation. This is important. But the reskilling debate is nothing new, and it’s only one piece of the puzzle. We must also focus resources on creating a workforce that needs less reskilling. It’s a workforce that can adjust to new labor demands in the blink of an eye. We must begin early, in primary and secondary education.
In December 2017, the House introduced the “FUTURE of Artificial Intelligence Act.” Dead on arrival, it had only one small provision addressing education. This act must be resurfaced, and it must give AI in education its due. As the technology landscape changes, so too will the labor landscape. Education must evolve to meet this need.