Some reflections on the changes underway in executive education and the link to ‘un-thinking’ learning organisations and artificial intelligence.

Learning and teachability

In some ways, the pandemic lockdown has improved my travel and exploration of the world. I used to wake every second Monday at 4am, achieving the minimum cognitive function to find my gate at Lisbon airport around 6am and then gradually wake up on a train into a city (usually, but not always London) and then sit through a regular meat-space client project meeting that was formulaic, un-demanding and fundamentally lacking in human connection. But since that stopped, I have found myself working on projects in the Middle East, Africa and Asia, connecting with people through the little Zoom letterbox; and I have met and got to know some wonderful people and colleagues. Perhaps the constraint of virtual connection prompts us to share more social surface area so that we can find our common interests and connections – I don’t know – but somehow I feel there is more motivation to connect, and more humility in our shared experience, than I felt before.

This work has been mostly related to leaning, either as academic director of leadership development programmes or as faculty, which is something I have always enjoyed doing. It has made me think more about the mysterious process of learning, and especially about the importance of being ‘teachable’, ready to unlearn bad habits, and also the importance of knowing what you don’t know. I enjoy crossing swords with very senior people and really challenging them to think critically about their assumptions and be open to new domains of knowledge such as digital architecture and the shape and leadership practice of digital, connected organisations. Their fear of digital, combined with impostor syndrome and the vertigo senior people sometimes feel, has in my experience been a major barrier to organisational transformation as people often prefer to ignore or stand against new ideas that require them to re-think how they work. But most of all, I enjoy working with emerging leaders, especially very mixed international cohorts, because they are more ‘teachable’ and start from an assumption that they know less than they probably do. In general, they know what they don’t know and are highly motivated to close that gap, rather than show how smart they are.

I think we are still in the foothills of major change in how and what we learn in the digital world, and there are some interesting startups and scale-ups who will challenge the comfortable position of the Twentieth Century business schools.

Martin Parker recently wrote in the Guardian about (metaphorically) burning them down, in an analysis that was as much political and about their social role as it was about their effectiveness in preparing leaders to do their jobs:

If we want those in power to become more responsible, then we must stop teaching students that heroic transformational leaders are the answer to every problem, or that the purpose of learning about taxation laws is to evade taxation, or that creating new desires is the purpose of marketing. In every case, the business school acts as an apologist, selling ideology as if it were science.

I don’t fully share the same anti-capitalist perspective. For me, the problem with teaching a dual-class hierarchical hero leadership model is that it (a) clearly does not work; and, (b) assumes an organisational structure that is the opposite of where we are headed. I remain optimistic that there are many ways to run very successful businesses in free (not un-regulated) and competitive markets that do not depend on an entitled management class and a two-tier workforce.

Lazy Leaders?

Perhaps the management culture promoted by business schools also does not do enough to prepare leaders for the sheer grind needed to sustain business improvement or change efforts over the long-term. Elsbeth Johnson shared an interesting piece in Strategy+Business that suggests looking at just the first few months of a transformation project can give the false impression that the middle management ‘permafrost’ is holding back the valiant change efforts of visionary leaders, but if you look at the whole cycle, she says the opposite is often the case:

When we use this lens to explore why managers are routinely being asked to go above and beyond, we find that it’s usually because leaders have failed to do one or more of the following: First, they weren’t clear enough about what they wanted; second, they were not realistic about how long execution would take or how much it would cost; and third, they weren’t consistent enough in the signals they sent about what was important.

My move upstream to focus on digital leadership skills and leadership development was originally borne of a frustration that too many leaders had no idea what they were doing when it came to digital transformation, but rather than admit that and devolve efforts downstream to people in their organisations who understood the challenge, they would bizarrely do the opposite and take more control of this work because they recognised its strategic importance, and they believed in their inherent genius and ability to make good decisions even without understanding the domain.

But that is just the first problem to unlock, and thankfully we are seeing more leaders with the humility to understand what they don’t know. The second, bigger and more exciting challenge is how to create organisational structures that not only encourage learning at every level, but also create the basis of a learning organisation. And the last thing a learning organisation needs is the illusion that it is run by a mega-brain hero at the top.

Learning without thinking

If we try to imagine the organisational landscape beyond the first phase of digital transformation that will take us from pyramids to platforms, then the work of Boundaryless based on lessons from Haier and other platform organisations is probably correct in focusing on ecosystems of mutually-accountable micro-enterprises with support systems that seek to maximise the conditions of emergence.

To me, what a learning organisation and an evolutionary ecosystem have in common – somewhat counter-intuitively – is that constant learning and adaptation occurs best without thinking.

I really enjoyed this article by Jacob Browning in Noema magazine about learning without thinking, where he says:

We should be clear that much human learning has itself been, and still is, mindless. The history of human tools and technologies — from the prehistoric hammer to the current search for effective medicines — reveals that conscious deliberation plays a much less prominent role than trial and error.

This is, of course, also what machine learning seeks to achieve, but in a much more limited way than humans and other animals are capable of.

The New York Times carried an interesting piece last week entitled Whatever Happened to IBM’s Watson? – a salutary warning about the limits of Artificial Intelligence, which has been massively over-hyped and over-stated in recent years. This also reminded me of the fascinating emerging race in the automotive sector between the celebrity hare (or unicorn?) of Level 4 autonomous driving versus the tortoise of Level 2 advanced driver-assistance systems (FT $). ADAS systems are evolving quite rapidly and are already quite profitable, whereas autonomous driving projects are a money pit from which scalable, widely deployable systems may not emerge for another decade, if at all.

 

A confession: I don’t even want my car to drive itself all the time. ADAS is fine, and I am sure it will gradually take on more low level driving functions. The perfect balance, as in so many other areas of technology, is to use smart tech to augment my human instincts and skills, not to try to replace them. Driving is a task that does not always benefit from thinking, but rather subconscious and fingertip knowledge – experience, pattern recognition and intuition really make the biggest difference. My home country has a rate of death on the roads that is roughly double my previous country on a per capita basis. Crazy speeding, tailgating and veering onto and off of highways where on-ramps are often entertainingly positioned right before off-ramps. Anticipation is everything. The colour, model, year, tyre condition and lane position of a car, plus the seating position, clothes and head movements of its driver, are all relevant weak signals that help me spot potential suicide overtakers or undertakers and avoid them on the highway. I couldn’t explain all the criteria my brain uses, because it is an unconscious process, but I just *know* which car ahead of me is going to pose a risk, and I act accordingly. I am really not convinced LIDAR, Tesla Vision or other input systems attached to a machine learning system can do the same, but I welcome smarter driver assistance systems that can gently help in the background and avoid obvious imminent collisions or risks that my forward-facing human vision system doesn’t pick up.

I suspect that if we can reduce our reliance on the heroic leader model and embody the evolutionary approach of learning without thinking in our organisational structures, whilst doing a better job of encouraging continuous learning (and thinking!) among the people who work within them, we will achieve a lot more with digital transformation.