Unlearning 101

Jack Uldrich on the Future ... and Unlearning

In the past year, I have given dozens of keynote presentations to a variety of clients. Below is a short 10-minute speaking demo. If you are looking for an engaging, entertaining and informative keynote speaker for your conference or event, please contact either Mimi Hair or Ryan Foltz at Leading Authorities or Angela Schlep at Executive Speakers Bureau.

The Future Will Require a Whole Lotta Unlearning

If something doubles just ten times it is one thousand (1024 times to precise) larger. This is an important concept to grasp if you want to better contemplate the future.

Why? Because no fewer than nine technological trends—semiconductors, data storage, bandwidth, genomics, gene sequencing, robotics, nanotechnology, brain scanning and scientific knowledge—are doubling anywhere from every 6 to 18 months.

To put this in some perspective, consider the following examples.

If the military is currently deploying 1000 robots in Afghanistan but the number is doubling every year by 2020 that means there will be one million robots deployed in the country. This will change warfare as we know it.

If Wal-Mart is currently deploying 1 million RFID (radio frequency identification) tags but that number is doubling every year this suggests by 2020 that there will be 1 billion RFID tags deployed. This will fundamentally transform the global supply chain management system.

And if gene sequencing equipment can today translate one billion sequences every few hours (at an estimated cost of $20,000) but the technology is doubling year year, this implies we will be able to translate one trillion genes an hour by 2020. If this comes to pass, sequencing your genome will not only take minutes it will cost pennies on the dollar. Such a change could radically transform how we treat disease and will have profound implications for both the health care and the pharmaceutical industries.

A million, a billion and a trillion might not seem that different (perhaps because they rhyme) but here’s one way to think of the change coming our way:

One million seconds was 12 days ago;
One billion seconds was 32 years ago;
One trillion seconds takes us back to the year 30,000 B.C.

My advice? Buckle up because your future is about to expand in a million, a billion and a trillion different directions.

Unlearning & the Rise of the Supercomputer

Marshall McCluhan once famously said, “First, we shape our tools and then our tools shape us.” As a professional futurist, I have been trying to explain how some of our tools are getting exponentially more powerful. In turn, these tools are accelerating the advances that will soon shape our future and, by virtue of their findings, necessitate unlearning. Nowhere is this more true than in the field of supercomputers. 

According to this ComputerWorld article, supercomputers with 100 million cores and capable of one quintillion calculations per second—or 1,000,000,000,000,000,000 for those of you counting at home—will arrive around 2018. This growing processing power is important because it will help innovative researchers, scientists and entrepreneurs design next-generation materials, drugs, bio-fuels, batteries and much, much more. 

 One area merits special attention and that is in the area of how supercomputers are yielding new insights about the brain. As scientists learn more about how the brain really operates, I am convinced that we will need to unlearn much of what we now think we "know" about the brain. 

To better understand supercomputers amazing power, I invite you to watch this two-minute video I put together last year. Although be forewarned, one quadrillion is already rather quaint:

BMW Unlearns

The German automaker BMW, in introducing its "Light Visionary Model" prototype automobile -- which it dubs GINA (Geometry and Functions in "N" Adaption), writes this: "The key to affecting the development of tomorrow's mobility lies in our readiness to challenge what is established and in the ability to present new options." In short, BMW is unlearning.

I encourage you to watch the short video below. If you notice how doors and hoods no longer open so rigidly -- they gently fold and zip open instead -- or how the lights do open but they "blink" open (much like human eyes) instead, I think you'll agree that the benefits of unlearning could give BMW a very distinct competitive advantage in the near future. I particularly like Chris Bangle's quote at the end of the video: "Context over dogma." Words to live by!

 

The German automaker BMW, in introducing its "Light Visionary Model" prototype automobile -- which it dubs GINA (Geometry and Functions in "N" Adaption), writes this: "The key to affecting the development of tomorrow's mobility lies in our readiness to challenge what is established and in the ability to present new options." In short, BMW is unlearning.

I encourage you to watch the short video below. If you notice how doors and hoods no longer open so rigidly -- they gently fold and zip open instead -- or how the lights do open but they "blink" open (much like human eyes) instead, I think you'll agree that the benefits of unlearning could give BMW a very distinct competitive advantage in the near future. I particularly like Chris Bangle's quote at the end of the video: "Context over dogma." Words to live by!

To Unlearn: Put on a New Hat

I have recounted before how scientific and technical knowledge is doubling every seven years and have pointed out that if this trend continues everything known today will represent just 1 percent of the sum total of world knowledge in 2050. Consider then how a significantly better understanding of the human brain might influence not just science but economics. For instance, we know that, contrary to most economic theory, many people do not always act rationally when it comes to making spending and investing decisions. What will a better understanding of the brain portend for decision-making in this regard?

The answer is likely to be quite a lot. Take the following example. If given a choice between winning $150 or losing $100 on a coin flip (that is, where the odds of heads or tails are equal), many people refuse the deal because they fear the prospect of losing $100 more than they appreciate the benefit of gaining $150. This is the case even though the game is strongly tilted in their favor. The chances are that you will win $75 ($150 x .5) versus losing $50 ($100 x .5)—and this means that if you played the game ten times, on average, you would win $250. Still, most people are reluctant to even accept the bet over ten attempts. What is at work here is something called loss aversion, and it demonstrates that, contrary to rational economic theory, people can and still do make bad decisions—frequently.

A second example involves gift receipts. When people are asked if they would prefer to be given a $15 gift receipt to Amazon.com today or receive a $20 gift receipt in two weeks, a surprising number select the first choice in spite of the long-term economic advantages of the second option. What scientists have discovered is that in both this instance and the coin-flipping example there is disproportionate amount of activity in the limbic area of the brain. Neuroeconomics suggests that such information might be useful in determining how to help people make better long-term decisions such as preparing for retirement.

What else might change as a result of an enhanced understanding of the human brain? For one thing, marketing will. After the 2007 Super Bowl, in which advertisers plunked down a healthy $2.6 million for a thirty-second spot, researchers at UCLA showed that Coca-Cola’s commercials scored the best at connecting with peoples’ emotions and leaving them with a positive feeling. It obtained this information by using functional magnetic resonance imaging (fMRI) to watch how people’s brains responded to  ads.

If neuromarketing is the next wave, it might, among other things, require marketing executives for beer companies to unlearn the notion that scantily clad women, talking frogs, "trendy" vodka or funny shots of a young man getting hit in the groin are neither the best or only way to sell their product.

Medicine is another field ripe for an information explosion. In many instances doctors are today treating some diseases on the basis of limited information. As the connections between the brain and other parts of the body, including the human heart, become better understood, new methods of treatment are sure to arise. Similarly the relationship of whether a disease is the result of genetic or environmental factors, at the present, is also only vaguely appreciated. As new findings come to light, many of these relationship will be better understood. This will require medical professionals to unlearn old ways of practicing their profession and relearn new ones.

A perfect example is the case of Barry Marshall. In the early 1980s he was a practicing physician in Australia with virtually no research experience. Still, he became convinced that ulcers were caused not by stress and spicy food but by a bacteria called Helicobacter pylori. When he presented his theory before a conference of experts in Brussels in 1983 he was practically laughed off the podium. To make a long story short, in 1994 the National Institute of Health concluded that most ulcers were caused by the bacteria, and in 2005 Marshall and his colleague Robin Warren were awarded the Nobel Prize in Medicine. (A staggering number of ulcer sufferers are still unaware that antibiotics can cure them, but that’s another problem.)

To bring it back to a slightly more practical level, we know some lessons on unlearning are already out there. Anyone who has read Michael Lewis’s superb book Money Ball knows that Billy Beane, the general manager of the Oakland Athletics, had been able to keep his team consistently competitive -- until this year -- by unlearning the baseball business.

Instead of relying on the subjective opinions of crusty old baseball scouts who have spent their lives around the game and claim they can spot the next “phenom” from a mile away, Beane replaced many of them with Ivy League graduates who can crunch players’ statistics on their laptop computers using sophisticated statistical models and complex algorithms. In so doing he has been able to make George Steinbrenner, who thinks nothings of spending $180 million annually in an attempt to get back to the World Series, look foolish for the past eight years. (Personally, I'm hoping the Yankees will lose again this fall.)

It is with some irony then that another good quote on unlearning comes from Satchel Paige, who once said, “It’s not what you don’t know that hurts you. It’s what you know that just ain’t so.” A lot of baseball minds think they know what makes a great hitter or a great pitcher. Unfortunately the continued failure of certain managers and teams strongly suggests that Mr. Paige was right. A lot of what they think they know “just ain’t so.”

Lest one thinks that there aren’t many opportunities to unlearn things, let us quickly look at a second example. In The Wisdom of Crowds, James Surowiecki points out that David Romer, an economist at Berkeley,  used statistical probabilities to determine whether NFL coaches would have been better off going for a touchdown on fourth and goal or kicking a field goal. What he discovered is nothing short of startling. In 1,100 different situations where he determined the coach would have been better off going for it, the coaches opted to kick it 992 times. Eighty-eight percent of the time they made the wrong choice!

Why would NFL coaches make the wrong decision almost nine out of ten times? A big part of the answer is loss aversion. They are afraid of losing three points. The purpose of the game, however, is to win, and by unlearning some old things and relearning new things NFL coaches can jump the curve. Exponential executives can do the same thing by adopting different ways of thinking about old problems.

For more sports-related unlearning, check out these old articles:

Unlearn the Running Rules

Practice Your Unlearning Game

 

Unlearning Statistics

"There are three kinds of lies: lies, damn lies and statistics." Mark Twain

This past Friday Bjorn Lomborg had a thoughtful editorial entitled Technology Can Fight Global Warming. As a professional technologist and futurist, I couldn’t agree more and I have written about this idea frequently. Nevertheless, I find Lomborg’s use of statistics highly unprofessional. To wit, as the basis for his argument, he claims that a high CO2 tax “will reduce world GDP a staggering 12.9% in 2100--the equivalent of $40 trillion a year.”

It is amazing to me that the editors of the Wall Street Journal allow such drivel to be published. No one—and I mean no one—can predict what the future will be like in 91 years. (To understand why see my recent article The Future is Unpredictable). It is even more ridiculous that Lomborg pinpoints the figure at 12.9%. I mean, really, if you are going to guess what impact a future tax is going to have on the economy why not have a little intellectual humility and give yourself some leeway by suggesting the economy will drop by a more rounded figure such as 13%.

There is a famous quote by Andrew Lang that bears repeating here: "An unsophisticated forecaster uses statistics as a drunken man uses lamp-posts—for support rather than illumination.”

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A Future of Black Swans

The World is Changing: Unlearn!

Take a look at the pictures to the right. What's wrong with them? The answer would seem pretty obvious: they are upside down.

But that is wrong. They are only "wrong" from your perspective. From outer space there is no up or down, so the globe can just as correctly be viewed from one perspective as the other. And, regarding the map, had the first explorers been from Chile -- as opposed to Europe -- the first map of the world might have placed South America on the top and North America on the bottom. If so, we might view today's more common map as the one that is "wrong."

Yesterday, I posted a link to this video, which does an excellent job of explaining how fast the world of social media is changing. To understand the speed and pace let me highlight a couple of findings. It took 38 years before 50 million people had a radio. Television reached that milestone in 13 years, and the Internet only 4 years. I don't know the exact figure for Twitter but it is certainly less than four years.

I also liked the twist on the famous quote about Las Vegas. What happens in Vegas no longer "stays there," it also stays on Facebook, Twitter, Flickr, YouTube and Digg -- forever.

The world is changing faster than many of would like -- and more than most of us care to admit. To survive, I remain convinced one of the more critical life skills you can possess is an ability to unlearn because the way you might view the world is likely not the only way to see the world.

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Learning to Unlearn

The Time to Unlearn is Now!

This is the latest iteration of famous "Shift Happens" video with a focus on social media. If nothing else, it should serve as a reminder of to all of us why we must constantly unlearn. Enjoy!

Unlearning Prediction

"Those who have knowledge, don’t predict. Those who predict, don’t have knowledge.” Lao Tzu

This famous quote was uttered over 2500 years ago and may strike some people as odd that, as a professional futurist, I have chosen to highlight it.

My rationale is two-fold. First, as I have said many times before, the chief responsibility of a futurist is not to “predict” the future but rather outline a range of future possibilities. Second, and more important, I have highlighted the quote because it is true.

If you have not already read Nassim Taleb's outstanding book, The Black Swan: The Impact of the Highly Improbable, do so as soon as possible. On Page 177 of the book, Taleb has an illustration of the scattering effect which artfully explains why predicting the future—especially for longer time frames—is virtually impossible.

Because I can’t reprint the figure here, I am left with Taleb’s analogy for understanding the scattering effect: the prediction of a billiard ball.

Assuming one has knowledge of the location of every ball and the speed and accuracy of the cue ball, it is relatively easy to predict the movement of the ball after the first shot. A person might even expect that, due to the growing computational power of computers, the second, third and fourth degree movements can be estimated with great accuracy. The problem, however, grows increasingly complex with each subsequent movement and after the ninth movement the gravitational pull of a person standing at the next pool table exerts enough of an effect to alter the trajectory of the ball. And after 56 movements even the smallest particle on the outer edge of the universe will effect the trajectory!

The bottom line is this: There are simply too many factors to consider when contemplating the future 20, 30, 50 or 100 years out. (Even a small effect today can have outsized implications 50 years hence). The situation, of course, becomes even more complicated because of Taleb’s main thesis which is that “Black Swans”—described as “high impact, low probability” events—tend to shape the future more than “expected” trends.

Therefore, whether a future “Black Swan” takes the shape of a pandemic, an asteroid, an E-bomb, a rogue terrorist attack, a North Korean or Iranian nuclear attack, an unexpected breakthrough in quantum computing or synthetic biology, or, more likely, some “unknown unknown;” the future will be difficult too predict because we don’t have—and won’t ever have—enough knowledge about the future.

Unlearning Information

Unlearning information. It's sounds paradoxical, right? After all, who in their right mind, would want less information? Well, you might if you want to succeed in the future.

Consider this quote which I came across in Jonah Lerner's informative new book, "How We Decide":

"A wealth of information creates a poverty of attention."

It is counter-intuitive but often having access to too much information can lead people to make worse decisions.

For example, in a classic study, one group of MIT graduate students were given access to a steady stream of financial information -- CNBC, Barron's, The Wall Street Journal, etc -- while a second group was only given information on the changing price of a stock.

Given this disparity which group do you think did a better job in selecting stocks? Most people would assume the first group. After all isn't this why people read the Wall Street Journal and watch the analysts on CNBC? Well, you would be wrong. The second group -- the group with less information -- performed better.

Various versions of this experiment have been conducted with other groups, including college counselors who were asked to predict the future success of different students. One group was provided high school transcripts, SAT/ACT test scores, application essays and were even allowed personal interviews with the students. The second group was only given access to transcripts and SAT scores.

Again, the group with less information performed better. One big reason why this occurs is because when people are inundated with too much information they tend to think of all information as being equal. In the process, they lose track of what information is really important. More problematic is the idea that with more information people become increasingly confident of bad decisions!

The bottom line is not just as Jonah Lerner says that "Knowledge has diminishing returns," but rather as Nassim Taleb wrote in the Black Swan that "Additional knowledge of the minutiae of daily business can be useless, even toxic."

So there you go. De-toxify your system. Unlearn. Put down the newspapers and blogs; stop watching TV news programs; and quit following everyone on Twitter -- you'll make better decisions because of it.