Peter Thiel on the Role of Technology and Globalization in Our Economy

Peter Thiel tends to be best known as an investor and entrepreneur. He is a co-founder of PayPal and the first investor in Facebook, both of which have made him wealthy and well-known.

I tend to be more interested in Peter Thiel for his regular and careful analysis of economic and technology trends. Though Thiel is a self-described conservative libertarian and Ron Paul supporter, his analysis tends to be more nuanced and thoughtful than a lot of people give it credit for.

Two weeks ago he gave a fascinating talk at the DLD 2013 Conference entitled “Developing the Developed World”. Thiel’s analysis mostly centers on the prospects for economic growth in the foreseeable future. His analysis takes into account both the instability related to our recent economic crisis, as well as the prospect that much of the growth that previously drove our economy may have been an historical anomaly.

Growth from Globalization or Technology Innovation?

Thiel’s primary thesis categorizes the two driving factors of the future of our economy as globalization and technological innovation. In Thiel’s view, globalization is the economic growth from copying existing technologies and models from the developed world to the developing world. Technological innovation, on the other hand, is growth derived from the creation of new things. Thiel’s conclusion is that sustainable growth requires strategies to pursue both.

As TechCrunch reported:

In Thiel’s view, four things are likely to happen to the current group of developed countries. Growth and innovation can continue at a decelerating rate, they can enter a cyclical pattern of growth and collapse, completely collapse, or continue to accelerate. In the end, of course, the only acceptable option in his view is accelerated growth.

Exponential Technology Growth: The Singularity

Since Thiel’s prescription emphasizes the need for innovation growth to accelerate, rather than stagnate, Thiel focuses on the potential for continued exponential growth in computing power and software. Thiel is a well-known supporter of singularity studies, the prediction that exponential technological progress will lead to a point in the near future where artificial intelligence outpaces collective human intelligence and leads to a new era of rapid progress. In the DLD speech, Thiel notes the continued importance of Moore’s Law and accelerating innovation growth as a potential driver of economic recovery. He cites examples such as the future of self-driving cars, and bioinformatics as possible technologies to lead this growth.

This is fun stuff to think about.

I’m excited see if some of these themes are given more depth in Peter Thiel’s up-coming book “The Blueprint: Reviving Innovation, Rediscovering Risk, and Rescuing the Free Market”

You can watch Peter Thiel’s entire 50-minute talk at the DLD Conference is here:

From DealBook: Tech-Wary Buffett Shies Away From Facebook

Warren Buffett

While investors are salivating over the Web’s hottest start-ups, Warren E. Buffett of Berkshire Hathaway, long reticent of technology companies, has no plans to take the plunge into the social networking space.

“It’s not my game,” he said in an interview with DealBook at the Allen & Company conference here. “The world is changing, and I’m lagging behind.”

Mr. Buffett said he was not exactly sure what to make of the multibillion-dollar valuations of Facebook, Groupon, Zynga, LinkedIn and the like.

“A few of them will be worth enormous amounts,” he said. But “I don’t know which ones.”


10 Steps to Risk-Proofing our Economy


Nassim Taleb’s Financial Times op-ed recommends 10 fixes to our economy

Last week in the Financial Times, Nassim Taleb published an op-ed entitled, “Ten principles for a Black Swan-proof world.” In it, Taleb lays out a number of major economic reforms we could make to limit the likelihood of catastrophic risk in the future (expanded upon in the full FT article):

  • 1. What is fragile should break early while it is still small.
  • 2. No socialisation of losses and privatisation of gains.
  • 3. People who were driving a school bus blindfolded (and crashed it) should never be given a new bus.
  • 4. Do not let someone making an “incentive” bonus manage a nuclear plant – or your financial risks.
  • 5. Counter-balance complexity with simplicity.
  • 6. Do not give children sticks of dynamite, even if they come with a warning.
  • 7. Only Ponzi schemes should depend on confidence. Governments should never need to “restore confidence.”
  • 8. Do not give an addict more drugs if he has withdrawal pains.
  • 9. Citizens should not depend on financial assets or fallible “expert” advice for their retirement.
  • 10. Make an omelette with the broken eggs.

I have mentioned Taleb’s recommendations on rethinking on the economy before. He’s not always right, but he’s certainly worth understanding. In this case, his 10 principles are unlikely to be implemented, but maybe policy makers should give them some consideration.

Taleb is the author of the tremendously interesting (though somewhat disjointed) books “Fooled by Randomness” and “The Black Swan” and is also the subject of a great essay by Malcolm Gladwell. Check him out.

Your Finger Length Determines Your Ability to Make Money?

finger length

When (Not Very) Good Reporting Goes (Extra) Bad

So there’s this news story zooming around the world right now.

Maybe you’ve seen it or heard about it.

First, some high-profile researchers from Cambridge University in the UK last week published an article, “Second-to-fourth digit ratio predicts success among high-frequency financial traders” in the journal Proceedings of the National Academy of Sciences (”PNAS”).

Two days later, the story was reprinted in The Economist as, “Digitally Enhanced – Successful financial traders are born as well as made.”

Then, this morning, the Economist story was reprinted in the Star Tribune as, “Looking for a winner? Check the ring finger – Cambridge study shows: successful financial traders are born as well as made.”

The study found that men working as “high-frequency” stock traders often had longer ring fingers than middle fingers – a trait that is known to be a sign of high levels of testosterone. The articles then drew the conclusion that a useful way to find out if someone is good at making money is to measure their fingers.

Here’s my beef with all of this.

I’ve read the Economist and Star Tribune articles and the abstract from PNAS, but full text PNAS articles require a password, so I haven’t read the full version of the original study

The Problem of Sample Size and Source

The study that claims to have drawn scientific conclusions regarding all “high-frequency” traders sampled a recruited group of 44 people from a single trading floor with 200 people total. That is, there is no indication that this group was at all randomized, or representative of the makeup of any other trading floor in the world. Also, even if it were 44 random people, that doesn’t seem to me like enough people to draw useful medical or statistical correlations.

The study makes it very clear that trader “experience, counted for a lot.”  I can’t figure out how a study can use such a tiny sample size, which finds one strong correlative factor (experience),  and still draw any conclusive findings related to the correlation of another far-weirder factor.

The Problem of Specialty Generalization

Next, though the original study makes clear that they were only analyzing the limited sub-group of “high-frequency” traders, the news reports made the much broader claims that “successful financial traders are born as well as made” and that “making money comes naturally to some people — specifically to men exposed to high levels of testosterone before they were born.” It should be totally obvious to anyone that even a valid study of “high-frequency” traders doesn’t by logical extension make any claims about “successful traders” generally or even worse, people good at “making money.”

The Problem of Survivorship Bias

Survivorship Bias is the logical error of drawing conclusions about an activity based only on data related to those successful at the activity, while ignoring data related to anyone who attempted the same activity, but failed.  Here, the researchers only studied current traders’ fingers, not the fingers of anyone who had failed in the same role.  If they were to do the additional research and find that failing “high-frequency” traders also have long ring fingers, then maybe finger length/testosterone predicts for an interest in that kind of work more than predicting for success in that work, as both the study and articles claim.

The Problem of Hindsight Bias

Hindsight Bias is the logical error of drawing conclusions about future success based on past success. This concept has tremendous application in the field of finance.  In this case, the study and the article drew the conclusion that because these traders had been successful in the past, that they were, therefore, going to be successful at the work in the future.  That is, they explicitly made the claim that 44 people who have been successful at this kind of trading were therefore talented at it.  Is it possible that “high-frequency” trading takes a tremendous amount of skill?  Certainly.  Is it also possible that “high-frequency” trading just takes a lot of luck and the “survivors” that were sampled happened to be the lucky few? Seems possible.  The big problem is, this question is not addressed.  We are just told, as fact, that “success” at this kind of work is a game of skill, not chance.

The Problem of Drawing Practical Recommendations from Scientific Research

Journalists know that most people who read their articles (especially in science reporting) will assume that the whole article is based on valid scientific study. These journalists know that very few readers will ever bother trying to find and read the original study. Yet, here these articles try to convince people that maybe they need to start worrying about the finger length of their family’s financial advisor or banker. This crazy-generalized claim is never made in the original study, but it certainly helps a newspaper editor get excited about publishing the article. Shame on them.

This is all to say that (1) I’m highly skeptical of the original Cambridge study; (2) I’m disappointed in the mainstream media who report on these findings and draw their own conclusions from it, without showing any skepticism themselves; and (3) it’s made worse when media outlets republish other’s flawed reporting without any original analysis on their part.

Am I being too harsh? Probably.

But if you’re interested in learning more about cognitive biases, logical errors, and financial trading, I highly recommend Nassim Nicholas Taleb’s book “Fooled by Randomness.”

For an overview of Taleb’s theories, check out Malcolm Gladwell’s New Yorker article, “Blowing Up.”