Once the AI understands the question, it can then dive back into the course material to find an answer. But course materials must be structured by a subject-matter expert, who approves answers before the AI responds. This human participation is absolutely necessary, not only because highly regulated industries such as healthcare won’t allow an algorithm alone to provide life-or-death answers to a healthcare provider, but also because, without an expert, you risk the “Dr. Google” problem. Any physician can tell you how frustrating it is when patients come to their offices with wrong information they’ve gathered from a search engine, which simply shows them the most popular answers. After approval, however, the expert need not review answers to that question until the material changes, and AI can help there too, notifying the expert when content appears to have changed.

What if a student asks a question to which there isn’t an answer in the course materials? In this case, the AI becomes part of a virtuous feedback loop, alerting instructors about gaps in the course content, which can help the class better address the needs of future students.

I’ll be talking a lot about this at Open edX 2019 in March, when I will be a keynote speaker. The open-source platform is now working toward establishing waypoints in content to help learners and, potentially, AIs, understand what the content is for, how it’s used and applied. Most of the work is done after a course, when you want to apply on the job what you’ve learned.

Related: AI can humanize teaching—if we let it

AI and lifelong learning

Applying AI to constant education is not about replacing teachers. It’s a wonderful way to expand the reach of education to more employees. The trick is to balance that reach with the same rich learning experience as if the instructor were right there. Doing that requires making the platform sufficiently flexible to meet learners’ needs.

Constant learning is increasingly the norm for more and more jobs. To scale education beyond the classroom and into daily life, we need to move the learning process into work itself. That only works and scales with AI navigating, knowing when we need to know and where we need to go and scaling up mentoring.

About the Author:

Walter Bender is the former executive director of the MIT Media Lab and was co-founder and president of One Laptop Per Child. He is a keynote speaker at Open edX 2019.


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