Failures in Foresight: The Failure of Segregation

In this post we’ll embark on a journey back in time, to the year 2000, when you were young and eager students. You’re sitting in a lecture given by a bald and handsome futurist. He’s promising to you that within 15 years, i.e. in the year 2015, the exponential growth in computational capabilities will ensure that you will be able to hold a super-computer in your hands.

“Yeah, right,” a smart-looking student sniggers loudly, “and what will we do with it?”

The futurist explains that the future you will watch movies, and hear music with that tiny computer. You exchange bewildered looks with your friends. You all find that difficult to believe in – how can you store large movies on such a small computer? The futurist explains that another trend – that of exponential growth in data storage – will mean that your hand-held super-computer will also store tens of thousands of megabytes.

You see some people in the audience rolling their eyes – promises, promises! Yet you are willing to keep on listening. Of course, the futurist then completely jumps off the cliff of rationality, and promises that in 15 years, everyone will enjoy wireless connectivity almost everywhere, at a speed of tens of megabytes per second.

“That makes no sense.” The smart student laughs again. “Who will ever need such a wireless network? Almost nobody has laptop computers anyway!”

The futurist reminds you that everyone is going to carry super-computers on their bodies in the future. The heckler laughs again, loudly.

 

phone-1031070_1920.jpg
The smartphone: a result of several trends coming into fruition together. Source: Pixabay.

 

The Failure of Segregation

I assume you realize the point by now. The failure demonstrated in this exchange is what I call The Failure of Segregation. It is an incredibly common failure, stemming from our need to focus on only a single trend, and missing the combined and cumulative impacts of two, three or even ten trends at the same time.

In the example above, the forecast made by the futurist would not have been reasonable if only one trend was analyzed. Who needs a superfast Wi-Fi if there aren’t advanced laptops and smartphones to use it? Almost nobody. So from a rational point of view, there’s no reason to invest in such a wireless network. It is only when you consider three trends together – exponential growth in computational capabilities, data storage and wireless network – that you can understand the future.

Every product we enjoy today, is the result of several trends coming into fruition together. Facebook, for example, would not have been nearly as successful if not for these trends –

  1. Exponential growth in computational capabilities, so that nearly everyone has a personal computer.
  2. Miniaturization and mobilization of computers into smartphones.
  3. Exponential improvement of digital cameras, so that every smartphone has a camera today.
  4. Cable internet everywhere.
  5. Wireless internet (Wi-Fi) everywhere.
  6. Cellular internet connections provided by the cellular phone companies.
  7. GPS receiver in every smartphone.
  8. The social trend of people using online social networks.

These are only eight trends, but I’m sure there are many others standing behind Facebook’s success. Only by looking at all eight trends could we have hoped to forecast the future accurately.

Unfortunately, it’s not that easy to look into all the possible trends at the same time.

facebook-time-waste.jpg
Facebook: another result of the aggregation of several trends together. Source: LimeTree Online

A Problem of Complexity

Let’s say that you are now aware of the Failure of Segregation, and so you try to contemplate all of the technological trends together, to obtain a more accurate image of the future. If you try to consider just three technological trends (A, B and C) and the ways they could work together to create new products, you would have four possible results: AB, AC, BC and ABC. That’s not so bad, is it?

However, if you add just one more technological trend to the mix, you’ll find yourself with eleven possible results. Do the calculations yourself if you don’t believe me. The formula is relatively simple, with N being the number of trends you’re considering, and X being the number of possible combinations of trends –

equation2

It’s obvious that for just ten technological trends, there are about a thousand different ways to combine them together. Considering twenty trends will cause you a major headache, and will bring the number of possible combinations up to one million. Add just ten more trends, and you get a billion possible combinations.

To give you an understanding of the complexity of the task on hand, the international consulting firm Gartner has taken the effort to map 37 of the most highly expected technological trends in their Gartner’s 2015 Hype Cycle. I’ll let you do the calculations yourself for the number of combinations stemming from all of these trends.

The problem, of course, becomes even more complicated once you realize you can combine the same two, three or ten technologies to achieve different results. Smart robots (trend A) enjoying machine learning capabilities (trend B) could be used as autonomous cars, or they could be used to teach pupils in class. And of course, throughout this process we pretend to know that said trends will be continue just the way we expect them to – and trends rarely do that.

What you should be realizing by now is that the opposite of the Failure of Segregation is the Failure of Over-Aggregation: trying to look at tens of trends at the same time, even though the human brain cannot hold such an immense variety of resultant combinations and solutions.

So what can we do?

 

Dancing between Failures

Sadly, there’s no golden rule or a simple solution to these failures. The important thing is to be aware of their existence, so that discussions about the future cannot be oversimplified into considering just one trend, detached from the others.

Professional futurists use a variety of methods, including scenario development, general morphological analysis and causal layered analysis to analyze the different trends and attempt to recombine them into different solutions for the future. These methodologies all have their place, and I’ll explain them and their use in other posts in the future. However, for now it should be clear that the incredibly large number of possible solutions makes it impossible to consider only one future with any kind of certainty.

In some of the future posts in this series, I’ll delve deeper into the various methodologies designed to counter the two failures. It’s going to be interesting!

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7 thoughts on “Failures in Foresight: The Failure of Segregation

  1. Amazing post. Not just due to the valuable content, but also since you made your points super-clear and simplified the whole thing.
    Now here’s a question, and please be honest about it – how much are you, and other futurists you know derived by intuition and gut feelings? I mean, as you explained – the potential futures are countless, and like everything in life you might be influenced by your gut more than real “stats” or any rational thoughts.
    ???

    Like

    1. Thank you so much.
      As for your question, the answer is complicated. Futurists are human beings like anyone else, so they have their all intuitions, gut feelings, and generally world views that direct their interpretation of the future and of existing trends.
      That said, several methods in futures studies, like Causal Layers Analysis revolve around the idea that all of the underlying assumptions about the future and the present are identified and analyzed, so that the ‘lenses’ through which you interpret the trends will be clear to everyone. I think this kind of approach reduces the risk of relying on the gut alone, or at least makes clear where your gut enters the equation.

      Like

  2. I work at BQR where we produce software for reliability and safety analysis. Specifically, we have a Fault Tree Analysis (FTA) tool:

    http://www.bqr.com/care/care-dfr-package/care-fta/

    The tool was designed for calculating probabilities of combined failure events, but it could also be used for predicting future technologies like you described.

    An interesting question regards correlations between different events. In the FTA jargon, these are “common cause” events.

    Like

    1. A.I. algorithms (which include your tool) are definitely being used to calculate probabilities by matching trends together. Arod Balisa, Ori Nachum and me have developed a similar tool for forecasting the possible futures of crime by matching many potential technologies together, and also for analyzing possible results of the political race in Israel.

      Like

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    Like

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