Category Archives: Work, worker, workplace

To code or not to code, is that the question?

Over 2016-2017 Deloitte Centre for the Edge collaborated with Geelong Grammar School to run a national series of roundtables where we unpacked the common catchphrase “everyone should learn how to code” as we have noticed that there was no consensus on what ‘coding’ was, and it seemed to represent an aspiration more than a skill. We felt that the community had jumped from observation (digital technology is becoming increasingly important) to prescription (everyone should learn how to code) without considering what problem we actually wanted to solve.

What we found from the roundtables was interesting. First, yes, everyone should learn how to code a little, mainly to demystify it. Coding and computers are seen as something of a black art, and that shouldn’t be the case. A short compulsory coding course would also expose students to a skill and career that they might not have otherwise considered. However, the bigger problem lurking behind the catchphrase was the inability for many workers to productively engage with the technology. Many of us suffer from learned helplessness, where we’ve learnt that we need to use digital tools in particular ways to solve particular problems, and if we deviate from this then all manner of things go wrong. This needs to change.

The result of the roundtables were written up and published but Deloitte and Geelong Grammar School.

Cognitive collaboration

I have a new report out on DU PressCognitive Collaboration: Why humans and computers think better together – where a couple of coauthors and I wade into the “will AI destroy the future or create utopia” debate.

Our big point is that AI doesn’t replicate human intelligence, it replicates specific human behaviours, and the mechanisms behind these behaviours are different to those behind their human equivalents. It’s in these differences that opportunity lies, as there’s evidence that machine and human intelligence are complimentary, rather than in competition. As we say in the report “humans and machines are [both] better together”. The poster child for this is freestyle chess.

Eight years later [after Deep Blue defeated Kasparov in 1997], it became clear that the story is considerably more interesting than “machine vanquishes man.” A competition called “freestyle chess” was held, allowing any combination of human and computer chess players to compete. The competition resulted in an upset victory that Kasparov later reflected upon:

The surprise came at the conclusion of the event. The winner was revealed to be not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time. Their skill at manipulating and “coaching” their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grandmaster opponents and the greater computational power of other participants. Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process. . . . Human strategic guidance combined with the tactical acuity of a computer was overwhelming.1)Garry Kasparov, “The chess master and the computer,” New York Review of Books, February 11, 2010, View in article

So rather than thinking of AI as our enemy, we should think of it as supporting us in our failings.

We’re pretty happy with the report – so happy that we’re already working on a follow on – so wander over to DU Press and check it out.

References   [ + ]

1. Garry Kasparov, “The chess master and the computer,” New York Review of Books, February 11, 2010, View in article

You can’t democratise trust

I have a new post on the Deloitte Digital blog.

There’s been a lot of talk about using technology to democratise trust, and much of it shows a deep misunderstanding of just what trust is. It’s implicitly assumed that trust is a fungible asset, something that can be quantified, captured and passed around via technology. This isn’t true though.

As I point out in the post:

Trust is different to technology. We can’t democratise trust. Trust is a subjective measure of risk. It’s something we construct internally when we observe a consistent pattern of behaviour. We can’t create new kinds of trust. Trust is not a fungible factor that we can manipulate and transfer.

Misunderstanding trust means that technical solutions are proposed rather than tackling the real problem. As I conclude in the post:

If we want to rebuild trust then we need to solve the hard social problems, and create the stable, consistent and transparent institutions (be they distributed or centralised) that all of us can trust.

Technology can enable us to create more transparent institutions, but if these institutions fail to behave in a trustworthy manner then few will trust them. This is why the recent Ethereum hard fork is interesting. Some people wanted an immutable ledger, and they’re now all on ETC as they no longer trust ETH. Others trust the Ethereum Foundation to “do the right thing by them” and they’re now on ETH, and don’t trust ETC.

To code or not to code, is that the question?

Centre for the Edge is dipping our toe into the education waters again after last years report, , Redefining EducationWe’re collaborating with Geelong Grammar‘s School of Creative Education to look into “Does everyone need to learn how to code?”

Computers are at the heart of the economy, and coding is at the heart of computers. Australia’s prosperity depends on equipping the next generation with the skills they need to thrive in this environment, but does this mean that we need to teach everyone how to code? Coding has a proud role in digital technology’s past, but is it an essential skill in the future? Our relationship with technology is evolving and coding, while still important, is just one of the many new skills that will be required.

Prime Minister Malcolm Turnbull has called for the country’s schools to introduce IT skills to students much earlier than they do now, suggesting that children as young as five or six should be introduced to coding. President Obama affirmed the need for coding education in his final state of the nation address. Some educators, however, are already pointing out that that teaching coding on its own might not be enough.

We will be holding a series of round table discussions across Geelong, Melbourne,  Sydney, Adelaide and Perth in May 2016 to explore the following questions:

  • What is the intention behind “we need to teach everyone to code”?
  • What educational and social outcomes we should be striving for?
  • Are there key skills from “learning to code” not covered in the current curriculum?
  • Is there a better definition for digital literacy?
  • How does digital literacy relate to coding and the rest of computer science?
  • How do we demystify digital technology and bring the community along?

Please contact me if you are interested in participating.

To code or not to code, is that the question?

Image: Ruiwen Chua.

Be careful what you measure

Tyler Cowen has an article over at MIT Technology Review, Measured and Unequal, that discusses how improved measurement of workers might be a fundamental driver of inequality in the workplace of the future.

Consider journalism. In the “good old days,” no one knew how many people were reading an article like this one, or an individual columnist. Today a digital media company knows exactly how many people are reading which articles for how long, and also whether they click through to other links. The exactness and the transparency offered by information technology allow us to measure value fairly precisely.

The result is that many journalists turn out to be not so valuable at all. Their wages fall or they lose their jobs, while the superstar journalists attract more Web traffic and become their own global brands. Some even start their own media companies, as did Nate Silver at FiveThirtyEight and Ezra Klein at Vox. In this case better measurement boosts income inequality more or less permanently.

The assumption behind this sort of piecework measurement is that all the value realised by an article is due to the sweat and toil of a more-talented-than-usual journalist. If your article gets the clicks, then it must be because you are so good at what you do.

Unfortunately the world is not so simple.

We might choose to build our organisations around this sort of idea (and indeed, BuzzFeed et al work this way) but it tends to foster a short term and overly transactional view of work that ignores a lot of the value that workers, or a community of workers might create.

The first problem is the obsessive focus on outputs, on the assumption that the worker is responsible for all the value created. Outputs depend on inputs, and not just the worker’s skills. You can’t make a silk purse out of a sow’s ear, as the saying goes.

While the worker might be skilled, their work is also dependant on the quality of the materials they have to work with. Take the journalism example. A manager somewhere is splitting up the work, either by handing out the story ideas or by allocating topics to individuals. Not all ideas or topics are equal. It’s possible for someone to come from outside this system by finding a new approach—as Nate Silver did with a data-drivern approach—but that’s the exception rather than the rule. It’s more typical for the quality of the value of the outputs to be bound by the quality of the inputs, not the effort of the individual.

We see something similar in sales. It’s easy to sell in a rising market, and a booming market will see many sales people getting large commissions for no reason other than turning up. In a down market, though, its a different story, and we punish some of our best people for working hard just to bring anything into the business.

If we want to reward individuals based on their contribution then we need to quantify the amount of value they added, rather than the amount of value they lucked into. If we don’t then we’ll create a feeding frenzy for the juicy bits of work, while other less attractive (but possibly no less important in the overall scheme of things) get ignored.

Unfortunately it’s surprisingly difficult to measure value-add for many workers as it can be challenging to gauge the quality of the materials that they have to work with. A good example of this are the efforts in the US to measure teachers on the value they add in the class room, efforts which are struggling as it seems nearly impossible to objectively measure the quality of the students that they have to work with. There’s just too many variables.

Second is the problem of cumulative advantage. Success typically brings more success for no other reason than you were successful. Consider the opportunities created when you win an Oscar. The Oscars are an annual competition, so they’re awarded even if the year’s releases aren’t particularly good (such as if there’s a writers strike during most of the past year).

It doesn’t matter how you win the Oscar—either by creating great art and a big box office success, or simply be being the best of a bad lot—the attention that the Oscars garners you brings you to the attention of the world and the opportunities start flowing in. This improves the quality of the materials you can choose to work with. You might break the VW emissions story due to dumb luck, but it results in more story ideas flowing your way. You might not be the best journalist, you might not even be the journalist best positioned to make the most of the idea, but the idea is yours none the less.

Entire careers are built on the back of a lucky break followed by cumulative advantage. While this is good for the few lucky individuals, it’s not so good for the firm as it means that the firm might not be making the most of the materials at its command (though picking winners does make it easier for management). Nor is it much good for the equally talented individuals who weren’t quite so lucky.

Third is the problem of context. It’s rare, these days, to work in isolation. The context we’re in provides us with resources and connections that we couldn’t get elsewhere, or even just a boss that we can work with. While we might thrive in one environment, we struggle in others. One good example is star analysts, who often struggle when they leave the firm where they built their reputation. Some of that value in the outputs created might be the result of a productive work culture or effective management structure and team, factors that are the result of the everyone’s contributions, and not just the contributions the individual creating the deliverable.

Mr Cowen’s problem is that he has mistaken ease for cost. It’s cheaper than ever to measure all sorts of factors associated with work. At the same time, work has evolved making it hard know what to measure. While it might be cheap to generate all sorts of stats on worker activity, it’s not easy to tie these back to productivity.1)Aside, that is, for work situations which are explicitly configured as piece work, such as Uber drivers.

The root cause of this a recent shift (possibly sometime around 2005) from value being defined by the producer, to being defined by the consumer. The emergence of the consumer internet put the consumer in control as it enabled the consumer to have more information on a product than the merchant or producer, and the ability to source the product from any merchant around the globe. This was followed by the more recent emergence of social media, enabling consumers to turn to their peer, rather then brands.

Value used to be defined in terms of product features and functions, and we could measure a worker’s productivity by their contribution to creating these features and functions. Frederick Taylor started the trend by measuring how long it took for a man to unload a cart. The modern version is the basis of Mr Cowen’s article: counting the number and reach of articles carrying a byline, or worker surveillance where everything a worker types at a computer, everything they do is logged, recorded, and measured.

Value today is defined by a customer’s relationship to a product. Value is relative and shifting because it is a function of an expanding choice space for consumers. While all your workers contribute to creating this value, it’s not always obvious how to quantify their contribution.Their contribution might also be different for each customer, as relative value means that each customer could possibly conceive value differently.

Any retailer who heads down the omnichannel path, for example, needs to deal with the challenging of aligning a salesforce measured on their sales with a strategy that has sales skipping across multiple channels and contact points as the customer learns about the firm, develops their own understanding of what value is created, and winds their way to a decision. When you consider this it’s not surprising the Apple’s stores (some of the most profitable in the world) are not measured on sales, and fall under the marketing budget.

In the mean time we have many firms racing to quantify and optimise individual tasks that their workers undertake. This might drive improvements in a short term and overly instrumentalist definition of productivity, and result in a few lucky individuals receiving large pay checks. In the longer term the same strategy is destroying the value created for the customer, and possibly taking the firm’s future with it.

Image: Lainey Powell

References   [ + ]

1. Aside, that is, for work situations which are explicitly configured as piece work, such as Uber drivers.

How much do we need to know?

We used to be defined by what we knew. But today, knowing too much can be a liability.

Google, for example, is putting its trust in (potentially uncredentialled) “capable generalists” rather than “experts”.1)Laszlo Bock, Google’s Vice-President of People Operations, at The Economist’s Ideas Economy: Innovation Forum on March 28th 2013 in Berkeley, California. Expertise still matters for narrowly focused highly-technical roles but Google has found that in most instances a capable generalist will arrive at the same solution as an expert, while in some cases they will come up with a new solution that is superior to those proposed by the experts.

Expertise, and being an expert, implies having the hard-won knowledge and skills that make you a reliable judge of what is best or wisest to do. It’s an inherently backwards-looking concept, ascribing value to individuals based on their ability to accumulate experience and then generalise from it, taking generic solutions that have worked in the past and applying them to specific problems encountered today.

This is an approach that worked well in the past when knowledge and skills were expensive and difficult to acquire, and the problems we tackled later in our career were similar to those encountered at the start. Society has spent centuries reorganising work and dividing it into ever more narrowly defined specialisations to enable individuals to focus on, and develop expertise in, specific jobs.

Take the case of the Brunels in the 1800s: Marc, who built the first tunnel under the Thames,2)Marc Brunel was, in the early 1800s, the engineer responsible for the first tunnel to be dug under a substantial river. and his son, Isambard, creator of the Great Britain.3)Isambard Brunel built the SS Great Britain, in the late 1800s, the longest ship in the world at her time and the first iron steamer with a screw propeller. Both Marc and Isambard roamed across architecture, and civil and mechanical engineering, designing everything from buildings and manufacturing processes through railways to steam engines and ships, covering most of the technologies we associate with the industrial revolution.

Overtime all these technologies became increasing complicated and entailed, requiring you to acquire more and more knowledge and skills before you could be productive and contribute your own ideas and findings. The ground covered by the two Brunels has been divided into a range of highly specialised disciplines, each with their own narrowly defined education and credentialing process.

Digital technology, however, is changing our relationship with knowledge and, consequently, with expertise. The pithy version of this is “it’s not what you know, it’s what you can google”. By allowing us to easily capture and transmit knowledge, and by providing new means of communicating with our peers, the growth of digital technology is tipping the balance of power from narrowly defined expertise to more broadly defined capability. Knowledge is available on demand via online resources and social media while skills are being captured in software packages, shifting what used to be stocks to flows.4)The shift from stocks to flows @ PEG The generalist is no longer at a disadvantage to the specialist, as most (if not all) specialist knowledge and skills are available on-demand.

I heard a nice example of this a while ago when I was listening to Film Buff’s Forecast5)Film Buff’s Forecast @ RRR. The show was interviewing a director who also lectured at a local university. The director opined that the current graduating class had a lot more sophisticated understand of film, and were more sophisticated in their approach to their work, than he and his class were back in the early seventies. In his view this wasn’t because they current class were inherently smarter. It was because the majority of their time at university was invested in exploring the possibilities provided by film as a medium, and developing an understanding of what they might do within the medium. This is in contrast to the director’s class back in the early seventies, when the majority of a student’s time was spent finding, accessing, and internalising knowledge stocks.

The example the director gave was of a student being directed to some technique that Alfred Hitchcock used.6)Unfortunately I don’t remember which technique was mentioned. Back in the seventies this would have implied many afternoons spent in the stacks at the library looking for film criticism that discussed the technique, so that the student could develop an understanding of it and know in which films the best (and worst) examples could be seen, followed by a search of the rep theatres to find screenings of key films.

That same understanding can be obtained via an afternoon on the couch browsing the internet with the following day spent streaming films from Netflix.

Today we invest our time exploring the problem we’re trying to solve, and the context we’re solving it in, rather pouring most of our effort into finding the information we need.

We’re also increasingly finding ourselves asked to solve new problems, create new products and services, and, in some cases, even rethink how entire industries and sectors of the economy work. This is what we commonly refer to as digital disruption, even though that term fails to capture the full extent of the social change that is bearing down on us.

Take the construction industry for example. Technology has been used to streamline or automate many tasks making today’s construction industry a different beast to the construction industry of our grandparents, but it is still an industry that adheres to a fundamental craft-based paradigm, with skilled trades people working onsite to create bespoke buildings.

A range of technological and social changes are about to transform the construction industry from a craft-based paradigm to a flexible-manufacturing paradigm, skipping over the traditional industrial paradigm in the process.

My favourite example of this is Unitised Building7) who have developed a new construction process (as opposed to a technology) that enables them to construct a mid-rise building in a fraction of the time and with a fraction of the money, of a traditional approach. This building system is completely digitised, with the building design in 3D modelling tools before the design is broken down and sent to numerically controlled machines for part fabrication and assembly on the shop floor. Assembled modules are trucked to the construction site where one is lifted into place every eight minutes after which the various connectors snapped together and gaps plastered over. A process that took months now takes weeks and the cost is shafted in the process.

One9 Apartments
One9 Apartments under construction by Unitised Building

The shift from craft to flexible manufacturing has a dramatic impact on the skills required from the workforce, moving from deep expertise in building to general design, digital modelling and construction skills. The focus has shifted from needing people who can work within the established building system (people with deep expertise who can generalise experience and then apply these general solutions to specific problems) to people who can work to develop and improve a new building system (people with broader skills who can find new problems to be solves, and solutions to these new problems).

A similar trend can been seen across all sectors. We’re moving from working in the system that is a business, to working on the system. The consequence of this is that its becoming more important to have the general capabilities and breadth of experience that enable us to develop and improve the system in novel directions, than it is to have deep, highly entailed experience in working within the current system. There will always be a need for narrowly focused expertise in highly technical areas, but in the majority of cases the generalist now has an advantage over the specialist.

This raises an interesting conundrum. While you might not need to know as much as you did in the past, it’s not clear just how much you do need to know now. This is a particular problem for educators and firms as they want to arm the individuals under their care with the knowledge and skills required to be successful in the workplace. Teaching too little means that the individual will not be effective at what they do. Teaching too much implies that we are wasting the individual’s time (and money, in many cases).

Focusing on understanding how much to teach might be asking the wrong question though. In many cases the only person who can judge how much knowledge is enough will be the individual, as “how much is enough” will be determined by the problem that they are trying to solve and the context that they are trying to solve it in.

We need to break down the problem a bit more if we’re to understand what question we should be asking.

First, we do know that you need enough knowledge to be dangerous; to be conversant in the domain, to be able to understand and describe the problem, and to be able to interact and discuss what you are doing with the others who you are collaborating or working with. That film director mentioned above needs to be able to understand the criticism that they are reading, knowing the key concepts, technical terms and idioms that form the language of film. Similarly for our flexible-manufacturing building system, where you would need to understand the basic language of building, digital design, and flexible manufacturing if you expect to be productive and contribute.

Second, we need to equip the individual with the tools they need to manage their own knowledge and their access to knowledge. If the only person who can determine how much knowledge is enough is the individual, then we need to empower them by providing them with the tools they need to manage knowledge for themselves.

This can be further broken down into the following.

You need to understand limits of your current knowledge (or, put another way, you need to know when to go looking for new knowledge). This may be as simple of coming across new terms and concepts that you don’t understand, through to having the sensitivity to realise that your lack of progress in a task is due to the knowledge (the ideas and skills) that you’re applying being insufficient, and you need to find a new approach that is based on different knowledge.

You need to be aware of what additional knowledge you might draw on, so that you can you can reach out and pull it in as needed. This is a process of eliminating the unknown unknowns: reading blogs, going to conferences, participating in communities of practice, and even having conversations at the water cooled, so that your aware of the other ideas out there in the community, and other other individuals who are working in related areas. You can only draw on new knowledge if you’re aware that it exists, which means you must invest some time in scanning the environment around you for new ideas and fellow travellers.

You also need the habits of mind – the attitudes and behaviours – that lead you to reach out when you realise that you’re knowledge isn’t up to the task as had, explore the various ideas that you’re aware of (or use this awareness to discover new ideas), and then pull in and learn the knowledge required.

Finally, you need to be working in a context where all this is possible. To many work environments are setup in a way that prevents individuals from either investing time in exploring what is going on around them (and eliminating unknown unknowns), taking time out from the day-to-day to learn what they need to learn on-demand, or from taking what they’ve learnt and doing something different (deviating from the defined, approved and rewarded process).

So question we asked at the start of this post – How much do you need to know? – is clearly the wrong question to be asking.

Rather than focus trying to know (or teach) everything that might be relevant (the old competence model) we need to move up a level, focusing on metacognition. This means providing people with the tools needed to manage knowledge their own: fostering the sensitivity required to know when knowledge and skills have run out, creating time and space so that they can invest in their own knowledge management, and encouraging the habits of mind that mean that they have the ability and attitude to do something about it.

Image: Isambard Kingdom Brunel preparing the launch of ‘The Great Eastern by Robert Howlett

References   [ + ]

1. Laszlo Bock, Google’s Vice-President of People Operations, at The Economist’s Ideas Economy: Innovation Forum on March 28th 2013 in Berkeley, California.
2. Marc Brunel was, in the early 1800s, the engineer responsible for the first tunnel to be dug under a substantial river.
3. Isambard Brunel built the SS Great Britain, in the late 1800s, the longest ship in the world at her time and the first iron steamer with a screw propeller.
4. The shift from stocks to flows @ PEG
5. Film Buff’s Forecast @ RRR
6. Unfortunately I don’t remember which technique was mentioned.

Redefining education

Our latest piece at the Centre for the Edge is out: Redefining education.1)Peter Evans-Greenwood, Peter Williams, Kitty O’Leary (2015) The paradigm shift: Redefining education, Deloitte Australia.

When we did an Australian version of the Shift Index2)The Shift Index in Slides @ PEG we saw that while Australia has a pretty good digital foundation and society seems to be adapting to the shift fairly well, we’re not realising as much value as it could be. Or put another way, while we’re using digital technology to create new knowledge flows, we’re not as proficient at realising their value.

With the Shift Index complete we turned our attention to education, as it seemed logical that education would be the most effective fulcrum to use to improve our performance.

We took the major trends from the Shift Index – the move from stocks to flows, and from push to pull – and, as a bit of a thought experiment, applied them to the education sector to see what we came up with. This resulted in a slide deck The Future of the Education Sector3)The Future of the Education Sector @ PEG and now this report.

The major finding in the report is that our relationship with knowledge is changing, and consequently our relationship with education is changing. The snappy version of this is “Why remember what you can google?”. The longer story has interesting implications for the education sector as by changing what it means to be educated has all sorts of potential knock-on effects for education and educators.

The report is our attempt move the current debate beyond pedagogy and edu-tech, funding and Australia’s ranking on international league tables to consider if our changing relationship to knowledge (the shift from knowledge stocks to knowledge flows, highlighted in the report) is changing the role and purpose of education and (by extension) the education sector.

The report is on Deloitte’s web site, and I’d love to year your throughs.

References   [ + ]

1. Peter Evans-Greenwood, Peter Williams, Kitty O’Leary (2015) The paradigm shift: Redefining education, Deloitte Australia.
2. The Shift Index in Slides @ PEG
3. The Future of the Education Sector @ PEG

Education and learning are different things

Education and learning are very different things. It seems that we often confuse the two, to our detriment.

The other day I bumped across a fascinating article, Giving Teaching Back to Education,1)Biesta, G.J.J. (2012). Giving teaching back to education: Responding to the disappearance of the teacher. Phenomenology and Practice 6(2), 35-49. by Gert Biesta.3)Gert Besta’ home page The author makes that argument that we should allow teachers to teach. While there is definite benefits from having teachers play the guide on the side role, we also need them to be the sage on the stage.

He makes a good case for his main thesis, and I recommend reading the paper, but what I found interesting was a section early in the piece where he makes the strong distrinction between learning and teaching.

Learning is something personal. It’s something that you, an individual, does. Learning has you pulling in new knowledge and skills, experimenting and testing them, before you adopt what works for you while rejecting that which doesn’t.

Education, on the other hand, is something that’s done to you. It’s an intervention, a black box where the student enters on one side and leaves on the other changed in some way. This change may be the acquisition of knowledge, as it was so often in the past. It could be the acquisition of attitudes and behavours that you couldn’t develop on our own. Or it might even be the development of an awareness of the intersection between what you’re good at and what you like.

Learning is (ideally) something that you do continually. Education is something that you seek out when you need help.

This leads us to the somewhat radical conclusion that schools – or any educational instutition for that matter – are not places of learning. The place of learning is whereever the student is. Sometimes that place of learning is located at the educational institution. Often it’s not.

Calling any educational instutition a place of learning is a bit silly as it implies that learning is restricted to occurring at discrete and well-defined places (even if these places are virtual), when clearlly it could and should happen anywhere. Indeed, during the development of a recent Centre for the Edge report in the changing nature of education (more on that in the weeks to come) we even heard one senior K12 education state that their school is not a place of learning – it’s a place of education – as the learning should occur where ever the student is.

Making a clear distinction between learning and education also leads us to the conclusion that a lot of the discussion about life-long learning is really talk of periodic, life-long reeducation. I’m not sure that periodic, life-long reeducation makes any sense for students who are quite capable of managing their own learning. It does, however, make a lot of sense for educational instutitions who intend to charge students each time they return to the knowledge well.

Finally, the confusion between education and learning means that all the problems in the education sector are treated as learning problems. This worries me as it’s becoming clear that many of these problems stem from our inability to develop a shared understanding of what it means to be educated in this day and age.

It’s clear that the modern workplace is placing new demands on workers. Analysis skills used to be top of the list – the ability to to pull problems apart, optimise the pieces, and then put them back together. Now it’s creativity that’s in demand – the ability to pull together disparat ideas and make something new. We used to work alone, sitting in our office. Now we work in teams, often with members drawn from different organisations and cultures. And so on…

Today your value to the firm is not based on what you can prove that you know or can do, but in what the firm expects you to achieve. Firm’s are looking for individuals who a demonstrable interest in a problem the firm has; someone who has a track record of integrating new ideas from other disciplines and domains to create new, novel solutions; an individual who can effectively integrate into the firm’s team; and someone who’s background and culture will helps broaden as well as deepen the reach of the firm when searching for ideas.

This new generation of workers – Google calls them “smart creatives”2)Eric Schmidt & Jonathan Rosenberg (2014), How Google Works, Grand Central Publishing – have different educational needs.

As we say in the Centre for the Edge’s education report:

The goal of a formal education should be to prepare students for life after their formal education. In a world dominated by change it would be wise to define ‘being educated’ as having the ability ‘to adapt to whatever life might bring’. An increasingly important part of education – and intervention – will therefore be to instil in students the importance of continually updating and expanding their own knowledge stocks, as well as fostering within them the sensitivity to know when they need to do this. Doing this is a skill in and of itself. It is a skill built on habits of mind, the attitudes and behaviours that a student develops during their formal education.

Education and learning might have been synonymous in the past. primarily as educators had a virtual monopoly on knowledge. That is no longer true as it’s not what you know, it’s what you can google that matters.

What we think of as education is expanding and changing in repose to the changing nature of society. Education and learning are now very different things but we continue to view all problems in the education sector as learning problems, to our own detriment.

References   [ + ]

1. Biesta, G.J.J. (2012). Giving teaching back to education: Responding to the disappearance of the teacher. Phenomenology and Practice 6(2), 35-49.
2. Eric Schmidt & Jonathan Rosenberg (2014), How Google Works, Grand Central Publishing
3. Gert Besta’ home page

The Future of the Education Sector

We’ve spent the last six months or so at the Centre for the Edge looking into how the trends we saw in the Australian Shift Index (i.e. the shift from knowing something, to being able to google it) might be changing the education sector.

Our hypothesis was that digital technology has changed our relationship with knowledge, and that this has, in turn, driven changes in business and society making the existing education sector (and the model behind it) increasingly irrelevant. This means that the problems confronting educational institutions don’t arise from a lack of technology or pedagogy (and MOOCs will not save the world), but from a mismatch between the perceived purpose and role of education, and the demands of the modern worker.

To help get the creative juices flowing we put some of our thoughts onto some slides which we then used to spark conversations with a wide range of folk within traditional education institutions, and elsewhere. Given that we’re in the process of pulling together a report the details our findings we thought that it would be worthwhile to share the slides, so you can find them embedded below as well as in SlideShare.

Image: Francisco Osorio

Henry Ford, 1919

Business men go down with their businesses because they like the old way so well they cannot bring themselves to change. One sees them all about – men who do not know that yesterday is past and woke up this morning with their last year’s ideas.

Henry Ford, My Life and Work (discussing the disruption that the mass produced car was bringing across so many sectors)