Did you also see the video of the robot opening a door? Did you freak out and think: if they can open doors…what will they learn next? People see a robot do something that looks intelligent and the natural instinct is to extrapolate and assume that there is a general intelligence behind the action. In reality, the set of tasks that robots and Artificial Intelligence (AI) more generally are good at right now is constrained by very narrow parameters.

Think about the game of chess (or more recently, the Chinese game of Go). Every state of the world on a chess board can be ranked from great to terrible based on how likely you are to win from that position. So it becomes easy (relatively speaking) with enough data or games played to evaluate moves based on valuing the possible states of the board against each other. You don’t have to give a computer much more than the basic rules and a mountain of data to get a best-in-the-world opponent these days, thanks to Moore’s Law and the power of cloud computing. 

Even with the current limitations of AI, there are still some serious economic changes coming as a result of self-driving cars and other innovations. Whether it’s appropriate to conclude that “47 percent of all jobs are going to go away!” as some have, is another question entirely.

A key question for educators is to think about is what it means to live in a world where rule-based decision making, and even more complex pattern-matching tasks, will be done by computers. While some jobs will be wholly automated away, other roles will require a higher-level synthesis of the data produced by sophisticated decision-support algorithms.

It is important to keep in mind that so much of what drives behavior and decisions today is not easily captured into a data point to be fed into an algorithm. It will always be the case that experience and context. plus data-driven AI will produce the best outcomes. Whether that will happen via direct brain integration or not, I don’t know.

So what does this mean for educators? We already live in a world where we have to design assignments knowing that students can Wikipedia and Google their way to a competent paper summarizing a particular historical event. Part of the transition to Common Core State Standards has involved a focus on interpreting primary sources of information.

Even back when I was in high school we understood that computing should play a role in the STEM subjects, for example using graphing calculators to help students better understand calculus. And yet even within STEM, we’re still shamefully under-focused on computer science education in K-12. If we’re going to bring along a new generation to help shape both the algorithms themselves as well as the desired role of AI in our lives, we have to start with providing a baseline understanding of what exactly computers can and can’t do, how they work, and how to design them.

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See also: 

• How Artificial Intelligence Is Likely to Shape the School Market
• ‘LearnLaunch’ Speakers See Artificial Intelligence, Learning Sciences Shaping the Future of K-12
• Student-Centered Learning in Spotlight at World’s Largest Ed-Tech Show