Economists across the political spectrum agree that the single biggest threat to future job growth is neither immigration nor trade — it’s the artificial intelligence revolution already underway.Studies by Oxford University, McKinsey and Pricewaterhouse Coopers forecast that up to 50% of current jobs could be replaced by smart machines within the next 20 years. Already, more than 5 million U.S. factory jobs have been lost to automation since 2000. It’s become clear: If a job can be automated in the future, it will be.
What’s less clear is how educational institutions — the incubators of human talent — will respond to this sea change in the future of work. Despite being the envy of the world, American universities have been slow to modernize — too often educating students for 20th century career fields that will be obsolete by the time they graduate. Beyond simply conferring degrees, the foundational purpose of colleges and universities must be to educate — and that means equipping people of all ages, at all stages of their careers, to build successful and fulfilling lives. This means we need to take several important steps to make our students robot-proof.
First, we must design and implement a curriculum that empowers humans to do those jobs only humans can do. Call it humanics. This curriculum provides students with three literacies: technical literacy, data literacy and human literacy (such as teamwork, entrepreneurship, creativity, ethics and cultural agility). Then it integrates them, allowing learners to develop a creative mindset and the mental elasticity to invent, discover and produce original ideas in the A.I. age. Even as smart machines become smarter, we will still need humans to launch new companies, engage in global diplomacy, and supervise diverse teams of other people.
But a modernized curriculum will not be enough. Students must also gain workplace experience before fully entering the workforce — to deepen their understanding beyond “what” into “why” and “how.” For example, an engineering student might leverage her classroom studies in circuitry design during an internship at Waymo, Google’s autonomous vehicle project. By integrating firsthand experience with intelligent machines with her academic work, she learns agility and adaptability, and, most important, she learns how to continue learning.
We must also recognize that technological progress doesn’t come with a brake pedal. As machines get…