HESA

Higher Education Strategy Associates

Tag Archives: Automation

February 09

Skills and Youth

What with the Advisory Council on Growth’s paper on skills, and the Expert Panel on Youth Employment wrapping up, public policy is suddenly back to a focus on skills – and in particular what skills youth should have.  So, let’s talk about that.

While some in the federal government will state forcefully that they are not – repeat NOT- going to be like the previous government and tell students what fields they should study (read: welding), literally every time skills come up they start babbling about coding, tech and whatnot.  So as near as I can tell, this government is just as directive about skills as the previous one, it’s just that a) they’re pushing a different set of skills and b) they aren’t actively trashing programs of study they see as less valuable, the way the Tories did with sociology.

The Liberals’ urge to get everyone tech-ing is understandable, if shallow.  What’s the one part of the youth labour market where kids are doing better than ever?  Engineering and computer science.  Are tech-enabled industries the wave of the future?  Well, kinda, depending on your definition of what that means.  But let’s think a little bit more about what that means.

Consider what I would call “hard” tech skills: the people who actually do code or computer science for a living. There’s just not that many of them around.  And here’s a secret: even if Canada becomes some kind of massive tech haven, there still won’t be that many around.  It’s simply not a high-employment industry.  Defining it really ambitiously and assuming high rates of growth, these jobs might equal five percent of the labor force.  So, yeah, let’s increase the size of engineering and CS programs, a bit.  But that’s not a skills solution for the economy as a whole.  We need something for the other 95% of the population.

Now, there’s a broader set of tech skills that matter to a broader subsection of the population.  Some people call these “coding skills” but it’s actually closer to digital literacy.  Basically, people who work with databases all the time – whether they are in accounting or sales or advertising or what have you – can become more productive if they better understand the logic behind databases and have some understanding of how algorithms might improve their use.  Artists and designers can command higher salaries if they have some digital skills.  To be clear – this doesn’t mean we need more credentials in these areas.  It means we need more people in the workforce who possess thee skills as part of their toolkit.  They could learn this stuff through coding schools or “bootcamps”, or maybe more colleges and universities could integrate these skills into existing programs but more likely most people are going to acquire these skills informally.  Which is fine, as long as they have them.

But still, put those two sets of tech skills together and you’re covering maybe a quarter of the labour force.  And that’s not good enough.  What are we going to do for everyone else?

No one has a crystal ball that can help understand what jobs of the future look like.  But it does seem the case that if technology is going to be as disruptive as the tech-boosters think it will be, then a lot of jobs are going to be automated.  In fact, human employment will be increasingly be concentrated in things that computers or robots cannot do.  And in the main, those are either jobs that require a wide variety of physical skills or jobs that involve judgement and empathy.  Last year, Geoff Colvin wrote a book on this subject called Humans are Underrated, which is worth reading if you’re into this topic.

Put it this way.  We’ve got a minority of our future workers who will be working hard to make better robots and algorithms to do things humans can’t do (at least not near the price computers can do it).  But we’re also going to have a majority of our future workers who are going to have to work hard at making themselves unreplaceable by machines by employing very human skills like empathy and narrative.  Why in the name of all that’s holy would we focus our energies just on the first group of workers?  Why not acknowledge what’s actually happening in the labour market and say: we’re going to work on both?

A final point about skills and youth.  As I noted back here something really does seem to have changed in the labour market after 2008.  Full-time enrolment rates in particular have shifted downwards – but this is much more pronounced among the younger age groups (15-19) than it is among older ones (25-29).  This is consistent with a theory of skills-biased technological change: younger people have fewer skills than older ones.  But be careful here in equating the acquisition of skills with obtaining an education.  Employers want people who can get a job done: by and large when they talk about “skills shortages” what they actually mean is “experienced worker shortages”, because to them acquired tacit knowledge matter at least as much formally-acquired knowledge.   To put that a little more concisely: it’s not just that education is more important than ever, but experience is also more important than ever, especially for young people.

I know the Expert Panel will be thinking about these issues, because they kindly invited me to a roundtable event last week and we talked about all this (thanks, Vass!).  But the people who really need to be thinking about these issues are colleges and universities – perhaps more the latter than the former.  Study after study for the last two decades have shown that the number one reason students attend university is to get a god job.

As I’ve just run through, jobs are about experience and skills.  Could be tech skills, could be empathy/narrative skills: either is fine.  Slowly, institutions are coming around to the idea that experience matters and so work-integrated learning is expanding.  Great.  Hard tech skills?  We’ve got a lot of that covered.  Integrating second-level tech skills into other programs in Arts, Science and business.  Getting there (in some places, anyway).  But the narrative/empathy stuff?  I know some people blather on about how humanities give you these skills somehow by osmosis, but do they really?  Who’s checking?  How is it being measured?  And why on earth would we want to limit that stuff to the Liberal Arts anyway?

If I were a university President, these are the kinds of things I’d be asking my Deans to think about.

April 08

ATMs and the Future of Education

I recently came across a fascinating counterintuitive piece of trivia in Timothy Taylor’s Conversable Economist blog.  At the time ATMs were introduced in 1980, there were half a million bank tellers in America.  How many were there 30 years later, in 2010?  Answer: roughly 600,000.  Don’t believe me?  See the data here.

Most people to whom I’ve told this story tend to get confused by this.  ATMs are one of the classic examples about how technology destroys “good middle class jobs”.  And so the first instinct many people have when confronted with this information is to try and defend the standard narrative – usually with something like “ah, but population growth, so they still took away jobs that could have existed”.  This is wrong, though.  When we look at manufacturing, we see absolute declines in jobs due to (among other things) automation.  With ATMs, however, all we see is a change in the rate of growth.

The key thing to grasp here is that the machines did not put the tellers out of business; rather, they modified the nature of bank telling.  To quote Taylor, “tellers evolved from being people who put checks in one drawer and handed out cash from another drawer to people who solved a variety of financial problems for customers”.

There’s an important truth here about the way skill-use evolves in the economy.  When most people think about technological change and its impacts on skills, they initially tend to presume “more machines → high tech → more tech skills needed → more STEM”.  But actually this is, at best, half the story.  Yes, new job categories are springing up in technical areas that require new forms of training.  But the more important news is that older job categories evolve into new ones with different kinds of requirements, and requiring a different skill set.  And in most cases, those new skills are – as in our bank teller example – about problem-solving.

Now, as a society, every time we see job requirements changing, our instinct is to keep kids in school longer.  But: a) pretty soon cost constraints put a ceiling on that strategy; and, b) this approach is of limited usefulness if all you’re doing is teaching the same old things for longer.

At a generic level, it’s not hard to teach in such a way that you’re giving students necessary skills to thrive in the future labour market.  Most programs, at some level, teach problem-solving (identifying a problem, synthesizing data about it, coming up with possible solutions, evaluating them, and coming up with a solution), although not all of them test for them explicitly, or explain to students how these skills are likely to be applied later on.  More could be done with respect to encouraging teamwork and interpersonal skills, but these aren’t difficult to add (although having the will to add them is something different).

The more difficult problem has to do with understanding where technology is likely to replace jobs and where it is likely to modify them.  What do driverless cars mean for the delivery business?  At a guess, it means an expanded market for the delivery of personalized services during commuting time.  Improved automatic diagnostic technology or robot pharmacists?  More demand for health professionals to dispense lifestyle and general health counselling.  Increased automation in legal affairs?  Less time on research means more time for, and emphasis on, negotiation.

I could go on, but I won’t.  The point, as Tyler Cowen makes in Average is Over (a book whose implications for higher education have been criminally under-examined) is that the future in many fields belongs to people who can best blend human creativity with the power of computers.  And so the relevant question for universities is: to what extent are you monitoring technology trends and thinking about how they will change what you teach, how you teach it, and how you evaluate it?  Or, put differently: to what extent are your curricula “future-ready”?

In too many cases, the answers to these questions land somewhere between “not very much” and “not at all”.  As a sector, there is some homework to be done here.