Michelle R. Weise on education and the future of work, in an interview for the Observatory

We’re going to need other kinds of credentials or clusters of competencies or smaller micro-degrees and alternative credentials that help people come back into a learning experience in order to upskill or retool themselves for the jobs of the future.
— Michelle R. Weise.

Michelle R. Weise, Chief Innovation Officer at Strada Education Network, talks about universities and the future of the workforce, in an interview for the Observatory.

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Observatory: Learning and work are becoming more inseparable than ever. How is this affecting college and universities?

Weise: It's a good question. I think for certain forward-thinking institutions, and it's not happening system-wide, but there are a handful, maybe 10, 20 different institutions who really are thinking very deliberately about how they think about connecting students more directly to the workforce. But for the vast majority of institutions, it's so inordinately difficult to get out of their own way where they may be separate. What they do in college is very distinct from workforce training. But that dichotomy is just a false choice, that there's somehow something special that goes on in college that's different from vocational training or something that is workforce training. The truth is that they are highly integrated, and we have to think about them as more and more connected. So that's where I think that the institutions who are going to survive in terms of all the exponential changes that are happening in the field are the ones who are really thinking about how learning and work are inseparable.

Observatory: We are seeing a shift from the traditional four years college education towards lifelong learning. Does this mean the end of the college degree? And how can universities adapt to the volatile world we are living in?

Weise: I don't think degrees are just going to go away completely, but the idea that somehow, we can do a four-year or a two-year degree when we're young, when we're somewhere between 17 to 22-year-old people, and then somehow make it last a lifetime, that is over, that we're not going to just be able to depend on those four years to help us through all the kinds of volatility that we're going to see in the labor market and this knowledge economy that's evolving. What we're going to see is that we're going to need other kinds of credentials or clusters of competencies or smaller micro-degrees and alternative credentials that help people come back into a learning experience in order to upskill or retool themselves for the jobs of the future. I don't think we're going to just sort of see degrees disappearing. We're still going to need some sort of baseline foundational skills building, liberal arts training that helps us orient toward the future, but we are going to need to sort of see these intermittent kind of learning opportunities in that ecosystem of the future that need to be built, so that any working learner can return to learning seamlessly without having to stop work necessarily where it's flexible, convenient, all those kinds of things for that ecosystem of the future.

Observatory: And in the recent years, choosing the right college or university has more to do with the student employability. How can we improve the college to career pathway?

Weise: That's really interesting because what we have started to do with the college degree is just use it as a proxy, an approximation of someone's potential. But it used to be, at least in the US in the 1970's, that only 30% of our population actually went on to upper secondary education. And so, as a result, those people who actually attained a college degree really did get an automatic ticket into the middle class. Now, we have 4,700 different four-year degree-granting institutions that are relatively indistinguishable from one another in terms of their mission and their ability to land students jobs or what have you. They're all relatively expensive and they're difficult to differentiate from one another. And so as a result, more people have degrees, but they don't mean quite as much, they don't have that heft.

And you're absolutely right that we still use it in terms of thinking about the prestige factor, right? And that somehow if someone came from this kind of school, it must mean that they can learn X, Y, or Z. But we have to have a more granular, a more direct way of understanding what exactly a student knows how to do. So, what they can do from the knowledge in their brain and how it translates into the workforce. We need to understand what really the competencies are that they have to be successful in the workforce, and we don't have that. And part of the reason is we don't have a great assortment of assessment mechanisms to understand really where a person is in their lives and what their work experience means and what their capabilities and aptitudes and capacities are. We don't have a good way of assessing that. And so we rely on these very blunt proxies for a degree. And in the US what has happened is because we rely on that degree, it's just a sorting mechanism for hiring people. We've started asking for degrees for jobs that shouldn't actually require a degree. So, something like being an executive assistant, 15 years ago never required more than a high school degree, and now we're starting to ask for a master's degree because we can't find the right talent, and so we keep increasing and up-credentialing, and so it's a real problem.

Observatory: What do you think about alternative credentials?

Weise: I think it's exciting. They're probably in the early days of gaining traction. But one of my favorite statistics is that if you look at kind of the coding boot camps, they are boasting anywhere from 65 to 98 percent job attainment rates. Those are better odds of getting a job than if I were to go to law school. The American Bar Association tells me that I have a 57% chance of getting a job after spending so much money pursuing a law degree. Whereas if I were to try that $20,000 boot camp, there's a really high likelihood that I'm going to be earning six figures to pay back that investment. And so those are really interesting credentials that I'm seeing. And the ones that are most exciting are the ones that are so tightly knit with employers where the employers are collaborating directly with the learning providers to create a real pipeline for the jobs that are in demand.

Observatory: How will artificial intelligence affect our jobs, and what will the role of education in the automated future?

Weise: This is a hard one because I think there are some really different projections into the future of how much of the workforce will become automated or computerized. I think Oxford Martin Programme projects that 47% of US employment is at risk of obsolescence. McKinsey is talking about a different statistic, in which they could see that maybe approximately 60%, I think is what they project, are at risk globally in terms of jobs. There are these huge forecasts into the future where we're really worried about how artificial intelligence and machine learning and robots are going to take over our lives. But then there's also this other line of thought from people who are making these sort of futures, making these forecasts, who are saying that actually, a lot of this automation and computerization, yes, it will remove some of the repetitive jobs, but it will create a new line of work, and it will create new jobs that have to monitor those robots or that AI.

And one of the interesting pieces of information that I read most recently from a World Economic Forum report was that the skill that will be the most in demand will be high emotional intelligence. So that yes, the robot may be able to read radiology scans way better than any other human, but in order to give the news to a family that you have cancer, you have to have high emotional intelligence. And so, the kinds of empathy and skills-building that we do around emotional intelligence is going to be a really interesting task for learning providers of the future. How do we get people to coordinate better with that artificial intelligence, with robots? How do we think about those skills for the future?

Observatory: What will higher education look like in the 2049?

Weise: I love the 2049. Not 2050, but 2049. I hope it will look vastly different. I hope everything will be competency-based. And my biggest hope for the future of higher education is that somehow, we have a mechanism or a foundation for all of these competencies and skills to mean the same thing across states, across countries, across employers. Because right now, everyone is building in silos. There's so much innovation going on in start-ups, in companies, in large companies, but everyone is working and sometimes reinventing the same thing because nobody's collaborating. But what we need is a way to visualize people's skills, for employers to understand what these competencies mean, so that I know how to skill them up for the job that I need to hire for.

There needs to be a translation and a taxonomy that covers the entire gamut of industries and employers so that this one company doesn't have a particular badging system that doesn't make sense with this company's badging system. We need to have, what I like to call a GitHub for competencies. And GitHub is the way that we understand how proficient a web developer is. And if you actually go, no employer would hire a web developer without looking at their GitHub profile. And when you look at it, it's these green boxes in a grid. And based on the shade of green that you see, you can see how highly skilled or how much they've contributed to this open-source platform, how much code they've built. And we need some kind of mechanism like that, where we understand visually, immediately what kinds of competencies and skill sets that person has. Maybe where they have weaknesses, where they have strengths, so that then we can then build them up in the right ways, and send them to the right alternative learning providers, or maybe the right institutions to get them the training that they need.

But my hope for the future is that we have a singular taxonomy. That makes sense across various organizations, across the Big Five tech companies, that everyone is using that same system, whether it's the learning providers or the employers. That's what I hope for.