“Living a Life Worth Working”

Like today's future workforce, Dr. Michelle R. Weise is bound to hold numerous roles in her already accomplished career. The former college professor turned ed tech executive worked at the Clayton Christensen Institute for Disruptive Innovation before becoming the chief innovation officer of Strada Education Network's Institute for the Future of Work.

Weise is also the author of Long Life Learning: Preparing for Jobs That Don't Even Exist Yet. In it, she argues for reimagining how we train learners and earners for the prolonged careers that come with longevity, though not necessarily in ways one might think. In this interview for LearningWell, Weise talks about what little structure exists for us to gain the knowledge we will continuously need. She advocates for changes within post-secondary education and the workforce that will help align one's inner and outer lives and lead us to recognize our shared humanity in an increasingly isolated world.

LW: Your book suggests there are numerous jobs we might have in our lives. What has your own work life been like in that regard?

Weise: When I look back, I can see the stepping stones, but I didn't really plan any of this out. It was a lot of pivoting, learning new skills, and then taking that newly acquired knowledge and launching to the next thing. My first job was as a tenure-track English professor. That was supposed to be my job for life, but I realized early on that it didn't feel like the right calling for me. My first job outside of academia was for an ed tech startup that was helping service members transition out of the military into civilian careers. We were creating tools and services to help them translate their skills into the language of the labor market. Even though I didn't know it back then, that focus on learners' translation of their own skill sets has been a resonant theme throughout all of my work.

I ended up building out the higher education practice of Clayton Christensen's think tank on disruptive innovation. That was, as you can imagine, incredibly formative for my thinking, research, and exposure to every burgeoning innovation in ed tech and workforce tech. I've since built out various innovation labs for universities and have also worked with a wide range of stakeholders in the learn-and-work ecosystem and even created the Strada Institute for the Future of Work for Strada Education Network. All of these innovation and thought leadership roles have been focused on connecting post-secondary education more closely to the workforce.

LW: Could you define "long life learning" and what you think the implications of that are for the workforce?

Weise: Our lifespans are extending, and our work lives are getting longer. People are staying in the workforce at historically high rates, well into their sixties and seventies. There's been this conception that folks who are currently retiring only had a couple of jobs or maybe one job throughout their careers—the "gold watch generation"—but the data shows that's not true. Even our early baby boomers are retiring with an average of 12 job changes under their belts. So for the rest of us, we can expect many more job changes and pivots to come. For younger generations, that may mean maybe 20 or 30 job changes over a lifetime. For me, the simple mental model of a longer life and longer work life brings into sharp relief that we have no architecture, no infrastructure, no systems really set up to help us keep up with a rapidly evolving future of work.

So, the book is really my attempt to put the decades-old concept of lifelong learning into action by laying out how we can begin to invest in the on- and off-ramps we'll all need to move more seamlessly in and out of learning and work. How might we get just what we need and then keep moving along on the workforce highway without always having to make a tradeoff and forgo our wages in order to advance our education? What are the ways in which we can do this much more fluidly and in the flow of work?

LW: How can we begin to solve for that from both a preparation lens and a workforce lens?

Weise: I'll start from a curricular perspective. In an ideal world, we'd like to hire talented people whom we could trust in highly ambiguous circumstances. We'd like to trust that they'd take in various kinds of information, signals, and analyses, make sense of all that, and then use good ethical judgment to inform their decision-making process. It's a mix of both human and technical skills. We need people to be able to dance across disciplines, take ideas from another domain and use them in new ways. But it's very hard to train someone to do this unless we teach them how to really deal with ambiguity.

In order to do that, we can't keep teaching in silos. In our industrial learning complex, we silo everything we teach. We don't illuminate the ways in which disciplines interact and overlap. For me, the future of teaching and learning will center on purpose learning—orienting learners around solving a problem they care about like poverty, hunger, or climate change, and in the process of struggling with that larger challenge, they learn why certain principles and disciplinary knowledge are necessary. They also learn how to transfer and apply knowledge from one domain to another.

The refrain in higher ed is that we teach people how to fish, but we don't actually do this well. We teach people very specific content and problems within a discipline. We don't help our learners understand the coherence across a vast array of courses as a body of understanding.

At the same time, in order for our learners to thrive in an increasingly uncertain future, especially now in an age of AI, they're going to need to hone their human skills to complement the work of machines. The term "human skills" might make us think, "Oh, I'm human, I have these innate skills." Yes, but they require deep practice. And for older adults in the workforce, where do they go to practice skills like emotional intelligence, communication, and systems thinking? The lack of these human skills make themselves known in the workplace when there's friction, when there's an inability to build strong and collaborative teams. We also need to be thinking about how we build the right kinds of learning experiences for working learners to actually deepen their human expertise and their character skills.

LW: What role does the workplace play?

Weise: If you think about a T-shaped learner, it's having both those human broad-based skills and some technical or technological expertise. And if we return to the concept of a longer work life, we're not only going to have to deepen our human skills over time. We're also going to have to gain different kinds of expertise over time and get skilled up. Sometimes we're going to need that new knowledge in a very shallow way—just enough to be dangerous. Other times, it will require deeper engagement. We need to do this in an affordable way, within the flow of work.

In my book, I lay out five principles needed for a healthier learning ecosystem, and the fourth is this idea of integrated earning and learning. Right now, when someone's in the workplace and wants to skill up, we say, "Here's some tuition reimbursement money. Go do it on your own time on top of this full-time job or multiple part-time jobs and on top of your caregiving activities. Be self-disciplined." But we need to bring the onus for training back onto employers. It's not just on post-secondary education to solve this problem.

In 1979, we used to offer workers something like two and a half weeks worth of training for new skills. According to Peter Capelli, by 1995, that went down to less than 10 hours per year. But those 10 hours weren't even about building new skills for the future. It was for things like compliance training, risk mitigation, sexual harassment training, or discrimination training. When I was writing the book, Accenture had data that around 44% of employers had zero upskilling opportunities for their existing workforce. We have to begin to reimagine on-the-job training. Skilling people up has to be a shared responsibility about building skills for the future.

LW: You use the phrase "living a life worth working." How would you interpret that?

Weise: My work has been oriented around issues like career navigation, skills gaps, skills building, precision education, and automation and AI's impact on our careers. And at a certain point, I realized that something was missing. I call it "the soul of work," but it's this question of how do we align our inner lives with what it is that we do when we're making some sort of contribution in the world? This incredibly human element has been missing from all the trending discussions about the future of work.

One of the things that has been helpful for me as I've been studying the loneliness epidemic more is this understanding of the ways in which we're clearly searching for something more. I found this interesting data that in the US alone, the consumer wellness market has reached $480 billion a year. Globally, it's close to $1.8 trillion. People are paying for detox cleanses, intermittent fasting, and even bone broths. We're clearly in search of something, and this is happening along with the deterioration of our communities, family structures, and faith-based organizations. In the wake of all that, we're feeling like something is missing. There's some hole or aching need we need to fill.

And so when I talk about a 'life worth working,' it's not that we all have to suddenly drop what we're doing and pursue our passions. It's about how we actually find moments of real authentic encounters, even in what can sometimes feel like mundane work or even in some things that are not necessarily compensated as paid work. How do we find the small moments of encounter that give us that feeling of purpose and meaning in our lives?

And that is really tough because studies are showing that we're becoming more narcissistic and less empathetic. We are becoming so cloistered in ourselves that even small interactions are hard for us. 

I was thinking about how there have been all these return-to-work mandates recently, and I think in the minds of management, they're thinking, "My people aren't being as productive as they should be, so I need to bring them back in-person, so I can watch them and make sure they'll be efficient and productive." Those water-cooler moments and those serendipitous moments of connecting are being hailed as a way to get to greater productivity and deeper collaboration. But what I think we're missing is that we need those moments of serendipity to actually build more of those small and authentic encounters because we have become so consumed with ourselves.

LW: Is this something we can teach or learn?

Weise: How to move towards this kind of service orientation and thinking about others rather than ourselves? I think it's really hard. Our entire system is set up to build super individual high achievers, and then suddenly learners graduate from college, and we expect them to be great team players. I've always been impressed by how [Olin College] grads go through 20 to 30 different team-based projects connected to the real world by the time they leave. Why aren't more schools doing this? It's a way for us to help learners deepen their human skills and practice teaming and collaboration. In addition, by focusing on larger problems, learners must engage in design thinking. And the first step is empathy to understand the challenge they're trying to solve for a company or an organization. They get to immerse themselves in acts of caring that are pointed away from themselves.

LW: You talk about human skills being an important part of mastering machines versus the other way around. What are your thoughts on the use of AI in higher education?

Wiese: People are getting really fearful about the use of AI, but instead of thinking about how it can replace humans, we should be leveraging this technology to fix a super unsexy problem: stitching together incredible amounts of data across our higher ed and workforce systems. We have so much data in various silos and legacy systems, and we don't know how to tap into it all. GenAI gives us a way forward.

Think about how retail companies have built virtuous loops of information about us as consumers. Amazon's doing randomized control trials on us every few seconds. In higher ed, we need to get smarter about our own people, our own prospective learners, to be able to offer them something that really taps into a pain point in their work lives.

This is where I see real potential for AI in higher education.