There is a lot of talk these days about robots replacing humans in the workforce, but those conversations remain largely abstract. For students in school today, however, the issue is urgent, research shows. What if the job they aspire to today is no longer an option when it comes time to graduate? How can they train for jobs that don’t even exist yet?
On the other side of that equation are educators, who often draw from their own learning experiences in K-12 and higher education to inform their instruction. What responsibility do they have in preparing today’s students for a future none of them can really envision?
EdSurge recently sat down with Karen Cator, the CEO of Digital Promise, to get her take. Cator is a former director of the U.S. Department of Education’s Office of Educational Technology who has been championing digital learning since long before the term “digital learning” was being thrown around—back when she was still a classroom teacher in Alaska. Of all the issues and trends in edtech these days, she says automation is one of the most pressing—and one that all educators should be thinking about.
Listen to highlights of the discussion on this week’s EdSurge On Air podcast. You can follow the podcast on Apple Podcasts, Stitcher or wherever you listen. The transcript below has been lightly edited and condensed for clarity.
EdSurge: We're here at the EdSurge Fusion conference, learning about a range of ideas. One thing that's come up a few times—and something you presented about—is the rise of automation and artificial intelligence, and how both will affect our current students’ job prospects in the not-too-distant future. What is your take on this?
Karen Cator: This is not just a straight line on into the future, where everything becomes automated and artificial intelligence takes over our lives. There are a lot of tests and starts and stops, and people are adjusting as they try things.
But advanced manufacturing is definitely one area that automation is kind of taking over. Another interesting area is healthcare. If we think about the role of artificial intelligence being able to better diagnose what's happening—and help doctors really understand what's happening and connect the dots that they may not have just connected on their own—that's incredibly helpful. We hear about machines being able to read x-rays. But the machine reader is not going to be able to present those results with empathy. We think a lot in this whole world of automation and artificial intelligence about the differences between what the machines will be able to do and what is uniquely human.
A lot of people say that by 2030, when our current kindergartners are high school graduates, automation will have phased out many career paths that are available today. But then there's another camp of people who say, "Don't listen to that, they're just fear mongering." What do you say to people who doubt the research about automation and what risks do we run by not taking that seriously?
A lot of people are worried that automation and artificial intelligence will take away jobs. Some of the research by the McKinsey Global Institute says that by 2030 the transitions will be challenging, the transitions to different kinds of jobs. It will be much like the transition out of agriculture.
The kinds of skills that people need are changing, and we've been thinking about this for a long time. Way back in the '90s when we were thinking about 21st century skills, or the skills that kids need to be productive in the workforce: critical thinking, problem solving, communication, collaboration, creativity, innovation, financial literacy. There are a lot of things that we know that people need, but now it's really an imperative. The world is changing. The actual jobs that will be available are ones that you do need a different kind of education for, and that's what we need to pay attention to.
A lot of this talk about how jobs will change is framed from the student perspective, but obviously, part of the equation here is the educators. Do educators have a responsibility to teach students skills that aren't going to go out of style, and that no machine can replicate?
The biggest challenge here is that we're asking educators to do something that isn't like their own learning experience. We sometimes say, "Teachers have 15,000 hours of muscle memory about what it feels like to be a student, to be in a classroom." They just went through K-12 education, they went through college and now they're in a classroom, they're a teacher and so they have this feeling about what it is to be a teacher. Some of the transitions in what it means to be a teacher cause them to do something that may not be comfortable, that may not be something they have experience with.
I think some of the opportunities are developing a whole cadre of coaches that can work with teachers in their classroom. That's some of the most helpful professional development that we know of—classroom coaching. Someone who can roll up their sleeves along with the teacher, figure out, you know, if they want to try something new, they have sort of a partner to try this with, a co-teacher to try this with. It's a lot of professional development.
I think we also can leverage the power of communication technologies. We can create videos. We can create open education resources and publish them online for people to access and use. We can connect people online with communities of practice, with experts, with people who can also coach teachers through these kinds of transitions as they're trying to engage students in new kinds of learning experiences.
There are a lot of ways that existing technology further marginalizes students who were already at a disadvantage. How can schools make sure that doesn't happen with automation and the changing landscape of the workforce?
Equity is a huge topic. How we are able to ensure that all students—and especially focusing on underrepresented, marginalized students—have the best possible opportunities is something that it takes everyone to consider every single day. Sometimes it feels a little bit easier to create these more innovative and interesting and deeper learning environments with students who may have lots of support at home, or they already have a lot of social capital. They have experts they can reach out to. Their parents can help them. There are some advantages of all of those things.
But what we absolutely have to do is make sure that we figure out how to create these learning opportunities for students who are in schools that may not have all of those advantages. Making sure that schools are fully connected to broadband, making sure that students have devices that they can use inside of school and outside of school so that they have the opportunities to do their homework, do their research, find ways of solving challenges. That their assignments can be as big and compelling as other students who already have those kinds of advantages. It is imperative that all students have access to these kinds of rich learning opportunities, so that they, too, have great prospects for a productive future.
So, how do we make that happen?
One of the things that we've been thinking a lot about is this notion of inclusive innovation. I spent 12 years at Apple, I've been working with technologies as long as I've been in my teaching career, and have spent lots of time talking about innovation. I know that many times innovations have benefited certain populations more than others. Now we're trying to think about, how do we think about inclusive innovation? Inclusive innovation means that we are solving challenges with the people that the solution is for.
Perhaps we have homeless children that are coming to school, we include them, we ask them, "What kinds of things would be helpful for you? What are those solutions?" Because the population of people in the school that are not homeless may not think of the fact, "You know what we really need is a laundromat. We wish we had a place to wash our clothes." That is in fact an innovation, really when you think about it. It's something that solves a challenge, and it can be scaled up. That is something that's very possible to work with.
