Turbulence ahead (Bain and Co in the HBR)

As most of my updates now go to my clients rather than here on my blog, this post may seem out of place compared to previous writings.  However I’ve become increasingly concerned about the failure of governments to understand the implications of the:

  1. interplay of complex systems that form the framework of modern society (including the complex system that is the climate)
  2. effects of automation
  3. alarming rise in inequality
  4. threats from cybersecurity

There are significantly more risks to consider in the years ahead, and these have severe implications for stability.  Bain and Company has completed some good work on this recently, and a summary has just appeared on the HBR site.  I don’t usually include large quotes here, but this piece of work is a concise summary that is hard to beat (the highlights are mine):

The benefits of automation, by contrast, will flow to about 20% of workers—primarily highly compensated, highly skilled workers—as well as to the owners of capital. The growing scarcity of highly-skilled workers may push their incomes even higher relative to less-skilled workers. As a result, automation has the potential to significantly increase income inequality.

The speed of change matters. A large transformation that unfolds at a slower pace allows economies the time to adjust and grow to reabsorb unemployed workers back into the labor force. However, our analysis shows that the automation of the U.S. service sector could eliminate jobs two to three times more rapidly than in previous periods of labor transformation in modern history.

Of course, the clear pattern of history is that creating more value with fewer resources has led to rising material wealth and prosperity for centuries. We see no reason to believe that this time will be different—eventually. But the time horizon for our analysis stretches only into the early 2030s. If the automation investment boom turns to bust in that time frame, as we expect, many societies will develop severe imbalances.

The coming decade will test leadership teams profoundly. There is no set formula for managing through significant economic upheaval, but companies can take many practical steps to assess how a vastly changed landscape might affect their business. Resilient organizations that can absorb shocks and change course quickly will have the best chance of thriving in the turbulent 2020s and beyond.

The full report from Bain is also well worth reading, and is available here.

Luck = success?

A university study in Italy has simulated the effect of luck on wealth creation.  The study showed that richer people were more likely to be also lucky.   While this study was focused on individuals, it also looked at the wider implications, and concluded that casting wider for insights will provide better returns than placing specific bets.

If this research is able to be reproduced, it would give further support to the idea that expanding an organisation’s field of view will create long term returns.

Full details here

Things creep up on you…

The Financial Times has published an article on the death of retail in the USA.  In addition to being an interesting read about the impact of technology on jobs, it also contains a great quote about the risk of not having a view over the horizon, and the boiling frog effect:

Wayne Wicker, chief investment officer of ICMA-RC, a pension fund for US public sector workers says “These things creep up on you, and suddenly you realise there’s trouble. That’s when people panic and run for the exit.”

I’m betting that senior teams in the companies mentioned in the article have been sitting in their comfortable paradigms for too long, and their own biases have been filtering signposts that may have helped anticipate what’s coming.

Must read article on knowledge and AI

The smart, insightful and deep-thinking David Weinberger has published a must-read article on Wired about the implications of AI on the human concept of knowledge.  Rather than paraphrase his excellent writing, I’m going to extract some of the key sections:

We are increasingly relying on machines that derive conclusions from models that they themselves have created, models that are often beyond human comprehension, models that “think” about the world differently than we do.

But this comes with a price. This infusion of alien intelligence is bringing into question the assumptions embedded in our long Western tradition. We thought knowledge was about finding the order hidden in the chaos. We thought it was about simplifying the world. It looks like we were wrong. Knowing the world may require giving up on understanding it.

If knowing has always entailed being able to explain and justify our true beliefs — Plato’s notion, which has persisted for over two thousand years — what are we to make of a new type of knowledge, in which that task of justification is not just difficult or daunting but impossible?

Even if the universe is governed by rules simple enough for us to understand them, the simplest of events in that universe is not understandable except through gross acts of simplification.

As this sinks in, we are beginning to undergo a paradigm shift in our pervasive, everyday idea not only of knowledge, but of how the world works. Where once we saw simple laws operating on relatively predictable data, we are now becoming acutely aware of the overwhelming complexity of even the simplest of situations. Where once the regularity of the movement of the heavenly bodies was our paradigm, and life’s constant unpredictable events were anomalies — mere “accidents,” a fine Aristotelian concept that differentiates them from a thing’s “essential” properties — now the contingency of all that happens is becoming our paradigmatic example.

This is bringing us to locate knowledge outside of our heads. We can only know what we know because we are deeply in league with alien tools of our own devising. Our mental stuff is not enough.

The world didn’t happen to be designed, by God or by coincidence, to be knowable by human brains. The nature of the world is closer to the way our network of computers and sensors represent it than how the human mind perceives it. Now that machines are acting independently, we are losing the illusion that the world just happens to be simple enough for us wee creatures to comprehend.

Additional Conference Presentation Notes

Late last week I spoke at a conference in New Zealand which had an unusual audience.  It was made up of deep thinkers who deal regularly with ambiguity at the sharp end of policy.  The Q&A session was fascinating, and a lot of attendees asked for more information.  With this in mind, here’s a few bullet points that provide more context on some of the topics:

Practical Tips for Online Privacy

  • never connect to a public wifi, even in hotels – they’re magnets for hackers and stealing your data is literally child’s play.
  • when going online away from work or home, either use your mobile phone as a hotspot, or purchase a virtual private network service.  It increases security and makes it harder to steal your data when online. I use this service.
  • cover the front facing camera on your laptop – it’s relatively easy for hackers to access the camera even when it looks like it’s not turned on
  • when you’re browsing online, it’s very easy for advertisers to track you and show ads targeted at you across different websites.  It’s a significant privacy intrusion that you can combat with this tool.

VUCA

Read/Viewing

  • A short video on the Cynefin framework for complexity
  • an interview that explains more about software biases with Cathy O’Neil – author of the book Weapons of Math Destruction
  • a sobering view of the future is painted in the book Homo Deus.  Here’s a review of the book in The Guardian

 

 

 

Human predictions about AI winning games are wrong

When Kasparov challenged the IBM chess-playing computer called Deep Blue, he was absolutely certain that he would win.  An article in USA Today on 2 May 1997 quoted him as saying “I’m going to beat it absolutely.  We will beat machines for some time to come.

He was beaten conclusively.

In early 2016 another landmark was reached in game-playing computing, when AlphaGo (DeepMind) challenged Lee Se-dol to a game of Go.  The Asian game is a magnitude more complex than chess, and resulted in Lee making the observation that “AlphaGo’s level doesn’t match mine.”

Other expert players backed Lee Se-dol, saying that he would win 5-0.  In the end he only won a single game.

Now the same team that developed AlphaGo is setting it’s sights on a computer game called StarCraft 2. This is a whole new domain for artificial intelligence because, as The Guardian points out:

StarCraft II is a game full of hidden information. Each player begins on opposite sides of a map, where they are tasked with building a base, training soldiers, and taking out their opponent. But they can only see the area directly around units, since the rest of the map is hidden in a “fog of war”.

“Players must send units to scout unseen areas in order to gain information about their opponent, and then remember that information over a long period of time,” DeepMind says in a blogpost. “This makes for an even more complex challenge as the environment becomes partially observable – an interesting contrast to perfect information games such as Chess or Go. And this is a real-time strategy game – both players are playing simultaneously, so every decision needs to be computed quickly and efficiently.

Once again, humans believe that the computer cannot beat humans.  In the Guardian article, the executive producer for StarCraft is quoted as saying “I stand by our pros. They’re amazing to watch.”

Sound familiar?

If AI can win at a game like StarCraft, it’s both exciting and troubling at the same time.

It will mean that an AI will have to reference ‘memory,’ take measured risks and develop strategy in a manner that beats a human. These three things – pattern recognition (from memory), risk taking, and strategy, are skills that command a premium wage in economies that value ‘knowledge workers.’

In 2015 a research team at Oxford University published a study predicting 35% of current jobs are at “high risk of computerisation over the following 20 years.”  The StarCraft challenge might cause them to revise this prediction upwards.

Making Sense of Current VUCA Levels: Carlota Perez

Among colleagues around the world at the moment, there’s a definite recognition that VUCA is increasing.  One of more interesting theories about why this is happening comes from the work of academic Carlota Perez who has studied long-wave change theories for three decades.  In a nutshell, she believes that we’re currently transitioning from what she calls the “installation period” (where technology is developed) to the “deployment period” (where economic booms occur).  Perez believes that the levels of VUCA we are seeing now are reflective of the transition.

So how do you know when you’re in the gap between the two?  Here’s one metric that she uses to support her view:

During Installation, there is always strong asset inflation (both in equity and in real estate) while incomes and consumption products do not keep pace. This creates a growing imbalance in which the asset-rich get richer and the asset-poor get poorer. When salaries can buy houses again, we will be closer to the golden age.

In many countries around the world there is a profound disconnect between average income and the ability to buy a house. For example in Canada the average home price was $480,743 for July 2016 while the average Canadian employee makes just over $49,000 a year. 

In parts of the UK such as Trafford (and it’s important to note that this isn’t London) house prices are now 8.9 times higher than average wages and 7 times higher in Stockport. In Manchester, the number has risen to 5.1 times in 2015.

In New Zealand the average house price is now six times the annual household income.

One of the other key changes Perez points to as an indicator, is the birth of new economic instruments:

…there need to be innumerable investments and business innovations to complete the fabric of the new economy. Here’s one small example: Millions of self-employed entrepreneurs work from home with uneven sources of income. Where are the financial instruments to smooth out their money flow so they can work and live without anxiety?

This sounds remarkably like the innovations surrounding the deployment of blockchain, where one of the best quotes that I’ve heard about this technology is that:

If the Internet is a disruptive platform designed to facilitate the dissemination of information, then Blockchain technology is a disruptive platform designed to facilitate the exchange of value.

Perez quotes two other indicators that can be used to spot the transition: the first is more financial regulation at a global level.  However the complexity at play here is that in a world that is heading away from globalisation, it’s very difficult to bring nations together to agree on these types of initiatives.  It may take another severe financial crisis to induce a global agreement.

The final indicator is increasingly stable industry structures, and I’d argue that currently this is harder to discern.  However one signal may be in the form of  digital consolidation of internet traffic by Google, Apple, Microsoft, Facebook and Amazon.  Most of the world’s internet flows through one of these organisations and they also act as enablers – for example the creation of a store front with Amazon with promotion via Facebook/Google.

Whichever way you look at the current macro global situation, it’s clear we’re not in what Perez calls the “Golden Age.”  Perez herself notes that the Golden Age might not even eventuate, and that patterns from the past might not foretell the future:

Historical regularities are not a blueprint; they only indicate likelihood. We are at the crossroads right now.

Media reporting and chaos

This is a long but very worthwhile read from The Guardian that feeds into some of the reasons why VUCA is increasing.  The key paragraphs are below:

Twenty-five years after the first website went online, it is clear that we are living through a period of dizzying transition. For 500 years after Gutenberg, the dominant form of information was the printed page: knowledge was primarily delivered in a fixed format, one that encouraged readers to believe in stable and settled truths.

Now, we are caught in a series of confusing battles between opposing forces: between truth and falsehood, fact and rumour, kindness and cruelty; between the few and the many, the connected and the alienated; between the open platform of the web as its architects envisioned it and the gated enclosures of Facebook and other social networks; between an informed public and a misguided mob.What is common to these struggles – and what makes their resolution an urgent matter – is that they all involve the diminishing status of truth. This does not mean that there are no truths. It simply means, as this year has made very clear, that we cannot agree on what those truths are, and when there is no consensus about the truth and no way to achieve it, chaos soon follows.

Source: How technology disrupted the truth | Katharine Viner | Media | The Guardian

VUCA gets an ‘S’ and a ‘T’

Eric McNulty is the director of research for Harvard’s National Preparedness Leadership Initiative.  On O’Reilly he’s published a very accessible piece about VUCA (volatility, uncertainty, complexity and ambiguity) where he’s added S and T.

The two additions are system-scale change and ubiquitous transparency, and Eric explains them further:

If VUCA were not daunting enough, I will add two new elements that take us from VUCA to VUCAST. They are system-scale change and ubiquitous transparency.

System-scale change can be seen in four mega-trends that I have been following since 2008. These are what I call “Pillar Trends” because they are global, will affect virtually everyone, have a discernable long-term trend curve (even if final outcomes are not clear), and no single individual or organization can alter their basic trajectory (the pillars are climate change, aging, urbanisation and technology).

Ubiquitous transparency is a direct outgrowth of the last component of system-scale change. You have to assume that almost anyone can know almost anything in almost real time. While this will cause some organizations to try to lock things down more tightly than ever, expectations of transparency will also grow.

I’ve also noticed these two components on the rise – my term for transparency is “the perfectly informed consumer” (however this cannot be added to VUCA to make a better acronym).

Leading in a time of tumultuous change: Our VUCAST world – O’Reilly Media

Complexity and technology

This is an insightful piece from the NY Times about the rise of American tech giants, but it also touches on an issue which increases the VUCA score of the world (my emphasis in bold below):

“What’s happening right now is the nation-state is losing its grip,” said Jane K. Winn, also a professor at the University of Washington School of Law, who studies international business transactions. “One of the hallmarks of modernity is that you have a nation-state that claims they are the exclusive source of a universal legal system that addresses all legal issues. But now people in one jurisdiction are subject to rules that come from outside the government — and often it’s companies that run these huge networks that are pushing their own rules.”

Ms. Winn pointed to Amazon as an example. The e-commerce giant sells both its own goods and those from other merchants through its marketplace. In this way, it imposes a universal set of rules on many merchants in countries in which it operates. The larger Amazon gets, the more its rules — rather than any particular nation’s — can come to be regarded as the most important regulations governing commerce.

Source: Why the World Is Drawing Battle Lines Against American Tech Giants