A Pedagogy of the Edges (or, the Wrong Robots)

The theme for #FutureEd this week was expressed in a Toffler quote (which turns out to not quite be a Toffler quote):

The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.

I find this quote a bit frustrating. For one, I agree with Tom that “unlearning” is just learning. For another, I’m troubled by the notion that previous generations didn’t engage in lifelong learning. Surely a cobbler, physicist, or reporter continued to learn throughout their career? I prefer Harold Jarche’s formulation of this phenomenon:

In the near future, the edges will be where almost all high-value work will be done in organizations. Change and complexity will be the norm in this work. Most people will work the edges, or not at all. Core activities will be increasingly automated or outsourced. This core will be managed by very few internal staff.

This is a sea change in organizational design. Some companies are already playing with new designs, tweaking their existing models. A few, mostly start-ups, are trying completely new models. Any work where complexity is not the norm will be of diminishing value. Freelancers and contractors, already increasing in number, will be needed to address continuously evolving markets. The future of work will be in understanding complexity and dealing with chaos.

It’s not just that we continue learning, it’s that automation of known processes and replication of digital content keeps pushing us to the edges. A decent newspaper reporter of ages past continued to learn her core craft throughout her career. But there’s something decidedly different about a reporter who moves from reporting to blogging to blogging plus photography and basic number crunching along with online research and analysis. As history proceeds, it’s the knowledge and process integrator that is becoming more valued, and the nature of what needs to be integrated is a moving target. We can certainly teach our students that intersection of geology, engineering, and statistics that is petroleum engineering today (a great example of demand for integrated skills) — but there is simply no way that much of what we teach today won’t be automated in five to ten years. And what then? The predictable does not have much of a future.

A lot of the educational debate breaks down into debates between the robo-believers and the robo-doubters. The robo-believers believe the emergence of technological solutions, AI, and networked knowledge can obviate the need for traditional teacher-powered education. The robo-doubters believe no app will ever capture the feel of an afternoon on the quad reading Keats with your class. Robo-believers accuse robo-doubters of living in Brideshead Revisted. Robo-doubters accuse the robo-believers of constructing Minority-Report-As-a-Service.

Left out of the public conversation quite often is a third point of view — that the robo-believers are right, but they are focussing on the wrong robots.

Because, if you believe, like I do, that technology will be doing amazing things in fifteen years, that AI *will* finally start living up to its promise, that vast advances in the machine processing of distributed knowledge will radically change what is possible, then the education “cost crisis” will solve itself. (And if you buy into Moore’s Law, the fact that that educational revolution is 15 years away predicts that our educational solutions tapping into into these AI technologies will suck for the next 10 years, and then suddenly become viable. Getting a head start here isn’t going to help much.)

But what about the next fifteen years?  The automation that is here now, today, the nature of distributed knowledge, here, today, makes our pedagogy of the center increasingly obsolete. The nature of the robo-future (and my partner Nicole tells me to stop using robot when I mean automation because I sound insane, but there you go) — the nature of the robo-future is that the predictable, the central, the places that exhibit best practice and utilize core domain knowledge will be hollowed out. *Are* being hollowed out.

Calls for efficiency in education are fine, and talk about afforadibilty and social justice is critical. But by the time that teaching — one of the hardest jobs to automate — is significantly automated we will be at the end of the robo-revolution, not the beginning. And if we really think that’s the case, what we’re teaching students now seems a much more pressing issue than how we’ll teach them years from now. What we need above all else is not an education that is powered by automation, but an education that is a response to it.

6 thoughts on “A Pedagogy of the Edges (or, the Wrong Robots)

  1. BTW, this is my argument against the “Mobile Learning Revolution” as well. By the time the classroom finds the niche for mobile, every other thing is the world is already going to be transformed by it. Heck, the mobile revolution has already happened in the workplace ages ago.

    So what’s the best response:

    a) How do we use mobile in the classroom to be more efficient?

    b) How does the presence of mobile in the world change the nature of work, citizenship, and our necessary preparation for it?

    There’s nothing at all wrong with asking question A, but asking A without B is meaningless, and B by itself would be just fine.

  2. My daughter’s school has this motto that I loved on first sight and seems to be addressing this: “we learn to learn”. The world is changing so fast (not just the tech, but also the rules) that it makes no sense to teach people stuff that will be obsolete by the time they have to use it. It makes so much more sense to teach them how to grasp information, how to filter it, process it, transform it, how to collaborate, how to adapt to new scenarios.

    There is so much talk about including technology in the classroom… but technology is just a tool. It’s not using tablets or specific software that’s going to change education. You can adapt completely traditional education (quite robotic if you ask me) to an online platform. Or you can teach collaboration (a key skill in the digital age) in a bare classroom. I find worrying that a lot of programs trying to include technology in the classroom are just concerned with the tool (what to do with a mobile, what to do with a tablet, should I do an online class), when the big deal is that the rules have changed, that they will keep on changing, and we need to learn/teach how to adapt (and then keep moving).

    I agree and disagree with the robo-believers. I do think that the future will bring less and less teacher-powered education, however, I don’t think that will be the consequence of automated processes, but rather the consequence of more self-driven, less hierarchical, less structured processes (granted, powered by technology). Maybe we will all be teachers. Or something like that.

    On the subject of learning and unlearning… I don’t know, I do get the point. I used to work in adult education and the longer people has been in a field, or the more expert they are, the harder it is for them to try anything different. Experience is invaluable, but it also creates biases that can be hard to overcome; we look at the world through the glasses of our experience and it’s not always easy to take them out.

  3. What a thoughtful blog. Thank you. I will quote you a lot for this: “What we need above all else is not an education that is powered by automation, but an education that is a response to it.” I could not agree more. Beautifully stated.

    I learned a lot from your post–but that’s not what Toffler means by unlearning since I basically agree and you moved my thinking a bit further in a direction it’s already in. Unlearning is more radical in its about-face. For me, unlearning means systematically working through habits formed by certain previous patterns of behavior, work, or intellect that no longer are serving you and that need to actually be broken (or, in my Derridian mode), deconstructed before you can figure out what you need to do to learn more effectively in a new direction. If you have an awful problem with your golf swing, you don’t just learn a new one. You have to unlearn your posture, grip, all that and really break it down, understand what you are doing in an unproductive way and grapple with it before you can make way for the new. We usually “unlearn” during tragedy or accident–you break your leg and the world is a different place; so is it when you lose a loved one. I like to construct learning experiences that help my students see their habits (that’s the first step in clearing the cognitive brush) in order to work towards learning something new. On a simple level, all learning is like that but, for the really basic things, it requires more introspection and systematic putting aside of past patterns.

    Is this specifically for the 21st century as Toffler says? Nah. He’s a futurist. Go figure. I think people have always had to un-learn in the sense I’m saying and always lifelong. But I do think in times of tremendous change, more of our habits are challenged and our patterns fail us and so the unlearning mantra is helpful, even if highly imperfect.

    That’s my take anyway!

  4. Really like the notion of a pedagogy of the edges. The good thing about edges is falling off them, making mistakes, getting it wrong. Formal schooling celebrates and rewards getting it right, which is to me, a huge problem. It basically means that errors and mistakes have to be glossed, swept away or tolerated insofar as the person doing the learning works her/his way to the right answer. There may have been some justification for a right answer pedagogy pre the Net but I am doubtful about that, see, for example, Rancière, J. (1991). The ignorant schoolmaster: five lessons in intellectual emancipation. Stanford, Calif.: Stanford University Press. I’m also encouraged by Stuart Firestein’s passion for ignorance (Firestein, S. (2012). Ignorance : how it drives science (Kindle ed.). New York: Oxford University Press.), or Martin Schwartz’s notion of productive stupidity. All of which is to humbly suggest that perhaps a modified version of the misappropriated Toffler quote might become: The illiterate of the 21st century will not be those who get things wrong, but those who cannot get past being right.

    For me, the problem word is learning, what I prefer to call the L-word to mark it as more of an unknown than a known. It’s used so easily to gloss so many different practices that it can be pretty much meaningless. It is the practices we know so little about, what do people actually do. There is a massive amount of glossed accounts of learning. There is a paltry amount of accounts of the actual practices of someone who is said to be doing the L-word.

    The irony here, when thinking about “automated learning”, is that machines (a better word than robots I think) are being taught to “learn” by making mistakes.

    To keep this short, for me, the real issue is how we, the language-bearing actors, learn to work with/complement what machines are good at or soon will be. This is a non-trivial problem. Tyler Cowen touches on this notion of the human/machine “team” in his recent book. There are lots of ways into the problem but I’m interested in the notion of delegation of work to a machine which happens in an almost automatic manner now.

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