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As of this month, I’m a college graduate, albeit one whose degree has yet to be mailed. Many graduates will likely approach this time immediately after commencement with lots of enthusiasm, excited about a world filled with possibility—and the promises of PTO! And yet, while this pivotal time is certainly intoxicating, the Class of 2018 is entering a precarious workforce, one in which .

More specifically, from my experience, many students aren’t considering how automation and artificial intelligence may affect their job prospects once they’ve crossed the stage. But here’s why they should be.

“,” “,” “,” “.” These are just a few headlines that speak to the potentially seismic impact of automation, and how some people might soon find themselves in a radically different work environment. In a sense, this story isn’t new: Technology has essentially always changed jobs—creating some, eliminating others—in the process leaving people in a state of professional flux and economic vulnerability.

Manufacturing shines a light on this disruption. Today, many rust belt communities are coping with the . Workers once had to switch from the agrarian to the industrial. Now, the mechanical seems to be going the way of the digital.

But it may be too easy for recent college graduates to dismiss the upheaval of blue-collar work. After all, that’s exactly why they pursued their four-year degrees in the first place: Almost every bar chart affirms that those with a bachelor’s degree have higher earning potential and better employment prospects. Sure, on-the-job training will be necessary, but I’m now fundamentally skilled, the thinking goes. Sure, supply and demand may waver, but society will always value my bachelor’s in finance.

While it’s true that higher levels of education correlate with and , it’s unlikely that this level of education will be enough to weather the next likely half-century of graduates’ professional careers. Indeed, while experts disagree on the magnitude and speed of automation, an increasing number of tasks—in fields like finance, medicine, and law—performed by those with a higher level of education are entirely within the crosshairs of constantly-improving software.

For instance, a estimates that 47 percent of “total U.S. employment is in the high-risk category,” according to characteristic tasks of each occupation. (Last year, PricewaterhouseCoopers that 38 percent of all existing U.S. jobs are at “high risk” of complete automation by 2030.) In a similar vein, and perhaps more relevant to students, the OECD in 2016 that, for some 25 percent of jobs, “50 percent of the tasks will change significantly because of automation.” This means that either outright automation or the fundamental transformation of many jobs may happen so rapidly and so broadly that most American workers, especially the youngest ones, might have to repeatedly re-skill and reinvent themselves throughout their careers.

In this light, it’s important that recent graduates ask: How might these new machines force me to re-conceptualize my work, instead of outright replace it?

Indeed, more under-discussed than outright obsoletion is the possibility that a decent job might soon require regular re-adaptation. In other words, lifelong learning to avoid obsoletion will become your main job. This could take the form of rapidly bouncing between unstable industries or holding as many as a dozen “micro-time” positions at any moment—or creating an entirely new, holistic profession.

What could this mean for students? For one thing, jobs that require strong analytical thinking and creativity could be difficult to replace with artificial intelligence. People with these sorts of skills could be more likely to survive professionally and excel as the future of work changes. In turn, a general liberal arts education, with a focus on critical thinking, could offer keys for preparing students for a lifetime of reinvention.

At least, that’s been my observation, both from working with ������Ƶ’s ShiftLabs and as a recent college graduate. My studies in science, technology, and society afforded me opportunities to grapple with possible future scenarios. But it wasn’t just me. Almost everyone in my classes had heard of artificial intelligence, and were aware of the dramatic changes gradually playing out in the workforce. Automated assembly lines and empty rust belts towns often, and quickly, came to people’s minds.

As I got further from my future studies and technology classes, though, the further technological automation (especially digital) receded from students’ minds. Very few entertained the likelihood that what they were learning about in the classroom would be substantively different by the time they get out. Most considered change on a scale of decades, rather than by fiscal quarters. Many professors also didn’t teach the long game: that the existence of bots capable of producing perfectly legible news articles might disrupt the future plans of journalism students, or that accounting majors might need to be tested more on their socials skills than on their proficiency with pivot tables.

The largest warehouses built by Amazon are staffed ; I hope that supply chain students are ready to factor that into their management decisions. Watson, IBM’s AI supercomputer, has been I hope that my biomedical peers are considering how it may supplement their work.

And I hope that all of us consider the ways in which we, too, might be on the brink of having to reinvent ourselves.