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.

Nanotechnology, Google & Unlearning

As a professional futurist who has written two books on the topic of nanotechnology, including The Next Big Thing is Really Small: How Nanotechnology Will Change the Future of Your Business, but is now interested in how the skill of unlearning can help society better prepare for the future, I couldn’t but help notice this article: Does Google Alter How We Think About Nanotech.

According to the research, people searching the term “nanotechnology” on Google are being directed toward more healthcare-related searches. Now there are legitimate questions about the relationship between nanoparticles and human health and these concerns shouldn’t be dismissed, but it is equally problematic that people’s perceptions about nanotechnology are being based on popularity. As the article states: “Sergey Brin and Larry Page created Google to sort search results, in part, based on how popular particular sites were. For science information, that means that surfers may be offered the most popular results rather than the ones that best represent the current state of science”.

As I wrote earlier today, exposing yourself to unlearning is difficult, and it isn’t made any easier if search engines are steering people toward “popular” information as opposed to the most scientifically valid information.

To this end, it is worth keeping in mind this wonderful quote from Galileo: “In questions of science, the authority of a thousand is not worth the humble reasoning of a single individual.”

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Nanotechnology in 250 Words or Less

 

The Lesson of the Lily Pad

I was recently asked by a leading nanotechnology consultant, Rocky Rawstern, if I could say anything on the topic of nanotechnology to a wider audience but keep it under 250 words, what would I say? Here was my response:

To those who don’t believe nanotechnology will change the world in the near future just because it hasn’t accomplished much in the last 20 years, consider this little quiz: If a single lily pad began doubling on a pond on the first day of June and doubled each day thereafter until the entire pond was covered by the end of the month, on Day 20 what percentage of the pond would be covered with lily pads?

The answer is one-tenth of one percent. That’s right, .1%! What happens over the next 10 days is a little short of amazing—the entire pond gets covered. Such is the nature of exponential growth.

Now, advances in nanotechnology aren’t quite experiencing exponential growth but they are close and over the course of the next decade nanotechnology’s impact on material sciences, medicine, and energy are going to be—like the lily pads’ spread over pond in the last few days— extraordinary.

 

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:

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.

Unlearn By Dispelling Old and New Ignorance

In his famous speech at Rice University where he declared that it was America’s intention to put a man on the moon by the end of the decade, President Kennedy said “the greater our knowledge increases, the greater our ignorance unfolds,” adding that “the vast stretches of the unknown and the unanswered and the unfinished still far outstrip our collective comprehension.”

 

Kennedy went on to offer a historical perspective for the magnitude of change society had experienced over the short course of human history. He asked his audience to condense the 50,000 years of man’s recorded history into the span of fifty years. Under this scenario, Kennedy noted that not much happened for the first forty years. Ten years ago, man emerged from his cave, and only five years ago did he learned to write. Christianity appeared two years ago, the printing press this year, and just two months ago the steam engine appeared. Last month electric lights, telephones, automobiles, and airplanes became available, and only last week did we develop penicillin, television, and nuclear weapons. To reach “the stars before midnight tonight,” Kennedy then poignantly added that Americans would have to “dispel old [and] new ignorance.”

 

Since achieving Kennedy’s goal in 1969, progress has continued exponentially. (Ironically, perhaps, with the exception of space exploration which, as Monday's 40th aniversary of the moon landing reminds us, has not made much progress.) Taking his historical analogy a little further, however, in the last proverbial "day" computers, biotechnology, the Internet, and the sequencing of the human genome have all appeared on the scene.

 

What Kennedy's analogy reminds us it that will need to continue to “dispel old ignorance” -- or continuously unlearn if you will -- only on a faster scale.

Unlearning the Future

Carl Sagan once advised the public to “never underestimate the power of exponential.” It was sound advice. Unfortunately, as with so much other wise counsel, it is easy to dismiss.

You shouldn’t.

Consider just a few recent examples of exponential growth. In 1998, a small Silicon Valley start-up was conducting 25 million web-based searches a day. The company had developed an impressive technology but it hardly seemed transformative. Ten years of exponential growth later, though, and Google has changed everything from how people get their news and entertainment to how politics and health care are practiced.

Wikipedia offers yet another example of exponential growth. Who amongst us could have imagined in 2001 when the first 100 Wikipedia entries were placed on the Internet that within eight years the site--which relies on free labor no less--would become the most widely used information source in the world?

It would be easy to believe that Google and Wikipedia are unique and, as such, represent one-time anomalies. They are not.

Ironically, if you type the word “exponential” into Google, the first search item that comes up is an entry from Wikipedia. If one then clicks on the list of “exponential topics” at the bottom of the definition there is an odd looking word: zenzizenzizenzic.

The term is defined as a number to its eighth power. Thus, the zenzizenzizenzic of 2 is 2(8)--or 256.

Now, zenzizenzizenzic might seem like a rather innocent concept but recall that Google and Wikipedia both experienced zenzizenzizenzic-like growth and, in the process, transformed a number of industries; and, in the coming decade, so too will a number of other emerging technologies.

Consider, for example, that Intel Corporation recently announced it had successfully doubled--to 2 billion--the number of transistors it has crammed onto its next-generation computer chip.

The real world manifestation of Intel’s zenzizenzizenzic is that we can now purchase a computer over 200 times more powerful than the one we bought a 1997--at one-third the cost.

Moreover, because the semiconductor industry will likely continue its little trick of effectively doubling the number of transistors it can place on a computer chip every 18 months this implies that by 2020 the zenzizenzizenzic of today’s 2 billion transistor could morph into a 500 billion transistor computer chip. Try wrapping your mind around what such super-powerful computers might enable us to do and achieve.

Exponential growth is not simply limited to the computer and Internet industries. Data storage, bandwidth, gene sequencing and even the growth of synthetic diamonds are all expected to undergo zenzizenzizenzic progression in the coming decade.

In fact these fields are just the tip of the proverbial iceberg. According to Gartner Research, the field rapid prototype manufacturing (i.e. machines which can physically print objects) will grow more than 100-fold. And in the past year, researchers in Finland have replaced a patient’s lower jaw with synthetic material growth from stem cells; researchers at the University of Minnesota have successfully demonstrated that they could grow a beating rat heart from living cells; and self-driven robotic cars have successfully navigated through an urban environment. Progress in these fields will not stop.

It has been said that the future is here, it is just unevenly distributed. This is true and if one studies the amazing technological progress occurring in information technology, biotechnology, nanotechnology, neurotechnology and robotics and then applies the power of zenzizenzizenzic to these advances, it is easy to understand how it would behoove us all to reconsider Carl Sagan’s sage advice and begin preparing ourselves for a great deal of unlearning. 

Is It Time to Unlearn the Scientific Method?

Last summer, Chris Anderson, the editor of Wired, wrote an excellent article entitled "The End of Theory: The Data Deluge Makes Scientific Method Obsolete” in which he convincingly argued that massive amounts of data, in combination with sophisticated algorithms and super powerful computers, offer mankind a whole new way of understanding the world.

Anderson believes that our technological tools have now progressed to the point where the “old way” of doing science—hypothesize, model and test—is becoming obsolete. In its place, a new paradigm is now emerging whereby scientists, researchers and entrepreneurs simply allow statistical algorithms to find patterns where science cannot.

If Anderson is correct—and I am open to the idea that he could be—this will take science in a whole new direction. In short, instead of modeling and waiting to find out if hypotheses are valid, the scientific community can instead rely on intelligent algorithms to do the heavy lifting.

Before this vision can be achieved, however, it will require a great many brilliant scientists to unlearn the idea that their “model-based” method of trying to make sense of today’s increasingly complex world is the only way to search for new meaning.

The implication for a field such as biology which, as Anderson points out is actually becoming more difficult to model as we learn more about it (due to our limited understanding of how genetics, microbes, personal behavior, the environment, and a host of other factors work in partnership to determine a person’s health), could be profound. More specifically, we will be able to analyze data without allowing hypotheses (which are, perhaps, wrong) to cloud our view of what the data is really showing us.

What If Society Has to Unlearn Death?

In 1899, just a few years before the Wright brothers achieved their historic accomplishment, Lord Kelvin—then one of the world’s brightest men and most accomplished scientists—declared heavier than air machines to be “impossible.”

He was wrong.

To add insult to injury, Lord Kelvin was proved wrong by a pair of bicycle repairmen from Dayton, Ohio.

A few years ago, a relatively unknown computer scientist, Aubrey de Grey, declared that aging should not be viewed as something which will necessarily ultimately result in death. Rather, he theorized that aging is a disease and should instead be treated as such.

The outcry from the scientific community was similar to Lord Kelvin’s reaction to human flight. One group of scientists even declared that de Grey’s idea was “so far from plausible that it commands no respect at all within the informed scientific community.”

Well, according to this article in Wired, the idea is now beginning to gain some acceptance within scientific circles.

To be sure, society is still a long way from de Grey’s goal of ending aging but, as I have written before, I’d encourage people to not dismiss the idea entirely. For if he is right, it will require society to unlearn a great many ideas which it now holds as dear.

In fact, the scale of unlearning our current paradigm of “death as an inevitability” could make other past historic paradigm shifts—such as the idea that the earth is not at the center of the universe (an idea for which Aristarchus was run out of Alexandria and Galileo was forced to recant under edict of the Catholic Church) or Darwin’s theory of evolution—look like child’s play.

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