Automation and artificial intelligence are already upending society and the labor market. There’s every reason to believe that trend will continue.
But what will the changes look like long-term? What will they mean for schools? How can educators and policymakers prepare today’s students for a world that can’t easily be predicted?
Education Week recently examined these questions in a special report, “Schools & the Future of Work.” Now, our Commentary team is bringing in added perspectives, with a new collection of opinion pieces under the umbrella of “Artificial Intelligence, Schooling, and Tomorrow’s Jobs.”
For a K-12 sector just beginning to truly wrestle with the implications of the broader technological changes happening in society, the entire package is a must-read. Here are some of the highlights:
Arizona State professor Michael Bennett spins out a vision of what an artificial-intelligence-enabled future could look like in education: a young student with a commercially available virtual mentor that “curates her comprehensive educational environment,” a busy administrator with a “retina-draping augmented reality device” that presents wardrobe recommendations and teacher-absenteeism data, and more.
“We must get used to...the notion that widely distributed technological systems and devices often govern our lives more effectively than local, state, or federal laws,” Bennett writes in his piece, “Artificial Intelligence Is Around the Corner. Educators Should Take Note.”
Misplaced faith in neutrality of these technologies is a problem, he says. Educators should resist simplistic views and talking points about AI, he suggests, instead focusing on understanding how the technologies actually work and teaching students to think through the social and political implications of the technologies that will play an ever-increasing role in their lives.
To make that happen, though, Charles Fadel thinks the K-12 sector needs “a profound redesign of curricula, where modernizing what students learn is an imperative.”
In his piece, “We Need to Modernize Education. The Clock is Ticking,” the founder of the Center for Curriculum Redesign makes the case that entrepreneurship, social sciences, and wellness should become just as important as technology and engineering, or math and science.
Fadel also argues for an increased focus on cultivating students’ “nonacademic qualities,” including creativity, critical thinking, collaboration, and curiosity.
And the most important, and most difficult, switch he wants to see is a new K-12 emphasis on “transfer,” which he describes as “the ability to use one’s competencies outside an original classroom setting, in the real world, perhaps many years hence.”
In “Students Must Be Prepared to Reinvent Themselves,” Harvard University professor Christopher Dede agrees with that notion, writing that “educators today are faced with the challenge of preparing young people for unceasing reinvention.”
Not only will today’s young people likely have a longer span of working-age years than their parents, Dede argues, they’ll be more likely to go through multiple careers (not just jobs.)
Dede sees barriers to the needed changes in our existing curriculum standards, outdated teaching practices, and “drive-by summative assessments.” Schools’ focus on individual accomplishment and rote content acquisition also does not jibe well with the future, he writes.
But there are promising tools at hand, Dede believes, including blended (physical and digital) makerspaces for hands-on creation; a growing array of child-friendly, creative computer programming languages such as Scratch, and the development of “immersive media” and classroom simulations—all of which, he says, can be used to promote learning that is based around solving big problems, not just mastering facts.
Milton Chen of the Panasonic Foundation and The George Lucas Educational Foundation writes that examples are out there. He looks at the “5 Habits of Extreme Learners"—students who love to learn, are passionate and fearless about pursuing their interests, and create “their own personal ecosystems” full of formal and informal learning spaces that offer rich opportunities for experiential, project-based learning.
Chen outlines five habits that are common among such learners, including self-motivation, curiosity across disciplines, elite technical skills, and strong social-emotional skills.
For a great example of what this looks like in real life, check out our profile of 13-year old Emma Yang, an elite coder who is building an artificial-intelligence-powered app to help Alzheimer’s patients manage their contacts and communications.
Yang’s story is also a great segue into “Preventing an Artificial-Intelligence Fueled Dystopia, One Student at a Time,” by Tess Posner, the executive director of AI4All.
The nonprofit group works to connect high-school-aged girls to opportunities to learn about artificial intelligence at elite universities such as Carnegie Mellon, Princeton, and Stanford. The idea is that education, mentorship, and outreach—combined with opportunities to learn about and apply AI to humanitarian causes—is a great way to engage traditionally under-represented populations in cutting-edge technology fields.
Why is that important?
Right now, Posner writes, “a relatively homogenous group of people are the current creators, researchers, and builders of AI.” An immediate consequence of that dynamic, she says, is technologies that are reflecting or amplifying existing biases.
And bigger-picture, Posner suggests, there’s a vision of an AI-enabled future that we could miss out on.
Imagine a world where AI supports and improves human capabilities, rather than just taking jobs and generating more clicks on online ads; where algorithms and datasets are open and transparent; and where proactive policies exist to ensure against discriminatory impacts of technology.
We’re not on that path right now, Posner says. Getting on it will require that all students have an opportunity to shape the future.
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A version of this news article first appeared in the Digital Education blog.