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The New Learning Organization

2013 June 15

Before the industrial revolution, people were valued for knowing a trade.   However, when machines took over physical labor, those skills became devalued and most people either performed simple, repetitive tasks or managed those who did.

By the late 20th century, a knowledge economy began to take hold.  Now, workers’ value lay not so much in their labor , but in specialized knowledge, much of which was inscrutable to their superiors.  In order to thrive, enterprises had to become learning organizations.

Now, we are entering a new industrial revolution and machines are starting to take over cognitive tasks as well.  Therefore, much like in the first industrial revolution, the role of humans is again being rapidly redefined.  Organizations will have to change the way that they learn and managers’ primary task will be to design the curricula.

First Principles vs. Experience

The true nature of knowledge has been a source of fierce debate for over two thousand years, beginning with a disagreement between Plato and his most famous student, Aristotle.

Plato believed in ideal forms.  To him, true knowledge consisted of familiarity with the forms and virtue (which, in modern terms would be closer to ability than to morality) was a matter of actualizing the forms in everyday life.  Plato would have felt comfortable as a factory manager whose workers carried out instructions to the tee.

Aristotle, on the other hand, believed in empirical knowledge, that which you gain from experience.  In contrast to Plato, we can imagine Aristotle as a Six Sigma black belt, constantly analyzing data in order to come up with a better way of doing things.

Both methods, the indoctrination of principles and the collection of data have played a role in learning organizations.  The difference now is that much of the learning is being taken over by machines.

How Machines Are Learning To Take Over

Not so long ago, we depended on human knowledge for many things, such as setting up travel itineraries, trading financial instruments and buying media that are highly automated today.  As we progress, new areas such as making medical diagnoses, legal discovery and even creative output are becoming mediated by computers.

Perhaps not surprisingly, the algorithms blend Platonic and Aristotelian approaches just like humans do.  Initially, their thinking is driven by time honored principles supplied by human experts (sometimes called “God parameters”).  Then, as more information comes in, the computer begins to learn from its own mistakes, getting better and better at its task.

This process continues at accelerating speeds.  Much like the rise of the knowledge economy empowered knowledge workers, because they had expertise that their bosses didn’t, computers are now coming up with answers that knowledge workers themselves can’t understand.  That will prove incredibly disruptive in the years to come.

It also presents a particularly thorny problem: How can organizations empower employees whose skills are being outsourced to the cloud?

Consequences of An Algorithmic Age

Just as the first industrial revolution transformed business and society, this new algorithmic age will bring not just efficiency, but significant, cultural changes.  While the future is uncertain, some of the shifts are already becoming clear:

Bayesian Strategy:  The knowledge economy coincided with the rising influence of business strategists.  Highly trained executives would analyze business conditions and devise intricate plans for the future.  Managerial performance, therefore, was widely evaluated as a function of their ability to “execute the plan.”

However, good strategy is becoming less visionary and more Bayesian.  Strategic plans will play a similar role to “God parameters” that will be honed through an evolutionary process of simulation and feedback.  Strategists, to a great extent, will become hackers rather than planners.

Brands as Open API’s:  One little noted consequence of the knowledge economy is the rise of intangible value, which often far exceeds tangible assets in corporations.  Brands, therefore, became tightly controlled assets that were nurtured and protected.

That’s changing as brands are becoming platforms for collaboration rather than assets to be leveraged.  Marketers who used to jealously guard their brands are now aggressively courting outside developers with Application Programming Interfaces (API’s) and Software Development Kits (SDK’s).  Our economy is increasingly becoming a semantic economy.

Firms ranging from Microsoft to Nike to The New York Times have also created accelerator programs, where young companies get financial, managerial and technical support to come up with new innovations (and potentially, enhance the business of their benefactors).

The Human Touch:  While much of the discussion about the rising tide of technology focuses on cognitive skills, Richard Florida argues that social skills will be just as important.  Many of the fastest growing professions are those which emphasize personal contact.

As computers take over more of the work, the role of humans will increasingly focus on caring for other humans.

Flying By Wire

Pilots don’t fly planes anymore, not really.  Whereas they used to have direct control over the aircraft, now they fly by wire.  Today, their instruments connect not to the airplane’s mechanism, but to computers which carry out their commands, modulated by the collective intelligence gained from millions of similar flights.

In essence, pilots perform three roles: they direct intent (where to go, how fast, when to change course), manage knowledge and (rarely) take over during emergencies.  Professionals in other industries will have to learn to perform their jobs in a similar way.

The function of organizations in the industrial age was to direct work.  The function of organizations in the algorithmic age will be to focus passion and purpose.

Managers, rather than focusing on building skills to recognize patterns and take action, will need to focus on designing the curricula, to direct which patterns computers should focus on learning and to what ends their actions should serve.

– Greg


8 Responses leave one →
  1. June 16, 2013

    What a great and important read. The discussion about what will humans do more of and the social skills is of course highly relevant when looking ahead.

    Could you elaborate a bit more on that? What kind of jobs do you see more of in the future? How can people create value (for each other)?


  2. June 16, 2013

    Thanks Jonathan,

    For a good overview, check out Richard Florida’s article linked in above. He describes it in much more elegant detail than I ever could.

    However, put simply, I describe the phenomenon as “When barbers become stylists,” which I describe in an earlier post. Here’s what I said there:

    Back when men tended to have the same haircut, you went to barber shops mostly for the conversation and a quick trim. These days, it’s hard to find a regular barber, they’re all stylists.

    We now demand a suite of services, including financial planners, yoga instructors and other personal service consultants that few of us would have bought a generation ago.

    Hope that’s helpful.

    – Greg

  3. June 16, 2013

    Thanks, Greg. And yes, Florida’s article is very impressive, not least in how effortlessly he writes off the mainstream tech debate as being too influenced by dystopians vs utopians – and thus, in the end, not very realistic or useful.

    I also enjoyed his views on raising the bar in service job and engaging “the creative talents of all of our people” – although this vision actually seems a bit utopian. What are your thoughts?

  4. June 16, 2013


    Well, I think there’s a lot of truth to what he’s selling (i.e. the Creative Class), but I also think it’s always important to keep in mind that he’s a policy entrepreneur.

    With that said, I think his last book, about the “Great Reset” will end up being amazingly prescient, but visions that will take 20 or 30 years to play out don’t sell very well, so he’s back to selling the Creative Class:-)

    – Greg

  5. June 17, 2013


    Very, very impressive post.

    But – it is time to pass from maxim like Richard Florida’s: “liberated from hierarchies that often waste their time and talents, people will be able to discover their most productive roles” – to pass to description of New Economy and to definitions of new entities.

    If hierarchies have gone away and new economical architecture is shaped in form of Ecosystems (like Apple, Google, Facebook, etc.) so, what are the new jobs in New Economy?

    Let’s assume that processing of information and transactions transfer from hierarchy to ecosystem model. But ecosystem should have differently new architecture based on multi-agent model (vs multi-level hierarchy), cognitive collective intelligence (with cognitive structurization of the information and intellectual content delivery vs non-structured content and e-mail communications), institutional regulations (with digital e-registers, e-repositories and arbitrage system vs analog tangible old-fashioned regulators) and also with 5 cybernetic feedback systems for self-regulation (based on Stafford Beer’s Viable System Model).

    So, instead of middlemen and managers new job will appear as communicators, business analytical mediators, managers of e-companies, e-entrepreneurs, etc. To describe these new jobs and economical ecosystem means to create new jobs for unemployed economists and lawyers.

    Unlike the 2008 today’s crisis is not financial but economical (humanitarian and social). New technologies bring differently new values which should be processed in a new (a little bit improved and expanded) economical model…


  6. June 17, 2013

    Interesting ideas, as always.

    Thanks Sergei.

    – Greg

  7. December 1, 2023

    Greg, this 2013 post was prescient, and now that ChatGPT has come out, some of its predictions are harder-hitting than ever.

    After the initial shock of ChatGPT’s fluent parroting of mediocre ad copy, it’s reassuring for this copywriter to think about the analogy given of the pilot. Because yes, humans will still have a role in directing intent and tweaking the output, even as machines take over more tasks.

    I think this is a hopeful and realistic vision for the future of work and learning.

    Would be curious about your take on recent developments.

    Brent Miler

  8. December 1, 2023

    Thanks so much for reminding me about this Brent!

    Here’s a more recent post I wrote shortly after Chat GPT4 was launched:

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