Category: Society

What makes us curious?

From Tim Harford’s “How to make the world add up”.

Per George Loewenstein a behavioral economist, curiously starts to glow when there is a gap between what we know and what we want to know. The sweet spot for curiosity is between knowing nothing and (the illusion of) knowing everything.

“Curiosity is fueled once we know enough to know that we don’t know”

Literacy does not make us better humans, Curiosity does.

From Tim Hartford’s “how to make the world add up” : a study by Dan Kahan showed that scientific literacy actually reinforce biases and tribalism BUT ‘scientific curiosity’ reduces them! The more curious we are the less tribalism influences our views, and thankfully there is no correlation between curiosity and political affiliation so that trait is present across the political spectrum.

Nate Silver’s book “The Signal and the Noise”

 

The book by Nate Silver “The Signal and the Noise …” is an amazing read. Very well written, entertaining as well as deep, it holds lessons and learnings that are applicable in our daily personal and professional lives. Its stated purpose is to look at how predictions are made, their accuracy, in several fields : weather, stock market, earthquakes, terrorism, global warming … But beyond that simple premise, it is a real eye opener when it comes to describing some of the deeply flawed ways in which we humans analyze the data we have at hand, and take decisions.

Nate Silver has very skeptical towards the promises of Big Data, and believes that the exponential growth in available data in recent years only makes it tougher to separate the grain from the chaff, the signal from the noise. One of the way he believes we should strive to make better forecasts, is to constantly recalibrate our forecasts based on new evidence, and actively test our models to improve our predictions and therefore our decisions. The key to doing that is Bayesian statistics … This is a very compelling, if complex, use of the Bayes Theorem, and it’s detailed through a few examples in the book.

As he explains, in the field of economics, the US govt publishes some 45,000 statistics. There are billions of possible hypotheses and theories to investigate, but at the same time “there isn’t any more truth in the world than there was before the internet or the printing press”, so “most of the data is just noise, just as the universe is filled with empty space”.

The Bayes Theorem goes as follows :

P(T|E) = P(E|T)xP(T) / ( P(E|T)xP(T) + P(E|~T)xP(~T) )

Where T is the theory being tested, E the evidence available. P(E|T) means “probability of E being true if we assume that T is true”, and notation ~T stands for “NOT T”, so P(E|~T) means “probability of E being true if we assume that T is NOT true”.

A classical application of the theorem is the following problem : for a woman in her forties, what is the chance of her having a breast cancer if she had a mammogram indicating a tumor ? The basic statistics are the following, with their mathematical representation if T is the theory “has a cancer” and E the evidence “has had a mammogram that indicates a tumor” :

– if a woman in her forties has a cancer, the mammogram will detect it in 75% of cases – P(E|T) = 75%

– if a woman in her forties does NOT have a cancer, the mammogram will still erroneously detect a cancer in 10% of cases – P(E|~T) = 10%

– the probability for a woman in her forties to have a cancer is 1.4% – P(T) = 1.4%

With that data, if a woman in her forties has a mammogram that detects a cancer, the chance of her actually having a cancer is of …. less than 10% !!! That seems totally unrealistic – isn’t there an error rate of only 25% or 10% depending how you read the above data ? The twist is that there are many more women without a cancer (98,6%) than women having a cancer at that age (1.4%), so the number of erroneous cancer detections, even if they represent only 10% of the cases where women are healthy, will be very high.

That’s what the Bayes theorem computes – the probability of a women having a cancer if her mammogram has detected a tumor is :

P(T|E) = 75%x1.4% / ( 75%x1.4% + 10%x98.4% ) = 9.6 %

Nate Silver uses that same theorem in another field – we have many more scientific theories being published and tested every day around the world than ever before. How many of these as actually statistically valid ?

Let’s use the Bayes theorem : if E is the experimental demonstration of a theory, and T the fact that the theory is actually valid, and with the following statistics :

– a correct theory is demonstrated in 80% of cases – P(E|T) = 80%

– an incorrect theory will be disproved in 80% of cases – P(E|~T) = 20%

– proportion of correct to incorrect theories – P(T) = 10%

In that case, the probability of a positive experiment meaning a theory is correct is only of 30% – again a result that goes against our intuition, as it seems from the above statistics that the “accuracy” of proving or disproving theories is 80% !!! The Bayes Theorem does the calculation right, and takes into account the low probability of a new theory being valid in the first place :

P(T|E) = 80%x10% / ( 80%x10% + 20%x90% ) = 30 %

There again, events with rare occurrences (valid theories) tend to generate lots of false positives. And this results in real life in a counter-intuitive fact : at the same time as there is a huge proliferation of published scientific research, it has been found that two-thirds of “demonstrated” results cannot be reproduced !!!

So … this book should be IMO taught in school … It gives very powerful and non-intuitive mental tools to make us better citizens, professionals and individuals. I don’t have much hope of this making its way into the school curriculum any time soon, so don’t hesitate, read this book, and recommend it to your friend and family 🙂

 

Democracy for the digital age

At dinner in NYC with Koen and Ann, we had a very interesting discussion about democratic processes. Belgium, France and the USA were obviously great material, respectively with their deliquescent state, banana republic, and polarised politics. Add to these a declining participation to the voting process, and it really looks like there is an opportunity to do better than these old democracies.
It should probably not surprise us, as our political representation systems date back from times when the fastest one could travel was on horseback, when most people lived tilling the soil, and few could read and write. The state then had much less complexities to manage, and the pace of change and decision making was measured in months, years or decades.
Isn’t it time then to move to more direct systems where citizens with access to immense amounts of data and analysis can directly participate in dialog, express their opinions, and take decisions without having to vote for “representatives” ?
This of course would be a huge shift, one that will be resisted by the current professional political class. It is also a complex one, which will require to reinvent all the safeguarding mechanisms, the checks and balances that took centuries to evolve.
But isn’t it already happening ? The political class in France recently showed how out of touch it was with the public opinion during the DSK sex scandal. They initially made statements supporting DSK, hinting that aggressive sexual advances was nothing to be fussy about, really an expression of French Don-Juanism. Within days or hours of their first reactions, they adjusted their stance, no doubt as their political advisors decrypted the online forums… The real-time data mining and analytics around social networks is already shaping the actions of politicians. We should probably take control of that process before they learn how to subvert it.

“The great stagnation : how America ate all the low hanging fruits” by Tyler Cowen


Just finished a book by Tyler Cowen, “The great stagnation : how America ate all the low hanging fruits”. It is a short book with depth, which lays out facts and ideas in a very crisp and engaging manner.

The author’s theory is that the US have reaped the low hanging fruits of productivity, and that its future material and financial growth is at risk. He details three key areas that fueled past productivity, but will not drive progress going forward :
– access to free land, from the 17th century to the end of the 19th century
– improvements in education. The percentage of the population graduating from High School grew from 6% in 1900 to 60% in 1960, and 74% today. Only 0.25% of people went to college in 1900, a number which has grown to 40% today. But we seem to have reached the limit of these improvements, as college drop-out rates have grown from 20% in the 60s to 30% now …
– a host of technological breakthroughs from 1880 to 1940. These have slowed down since then, and as the author puts there is not much difference between a kitchen or a house) today and one in the 50s in terms of the basic functionalities that had then become available (fridge, TV …). 80% of the economic growth from 1950 to 1993 actually came from innovations that happened before that time.

The author links that last point with the drastic reduction in the rate of growth of the median income, starting in 1970. His view is that discoveries since then have been geared towards private goods rather than goods for the larger public. The impact of the Internet is much more complex though and there is a whole chapter on that, which I will comment on later.

There is a whole section then looking at how we have tended to overestimate productivity through the GDP calculations :
– government spending is always factored in the GDP at cost, regardless of the utility or value created. This does not take into account the fact that as government grows there will be a diminishing return on that value. Since the 19th century the cost of government (excluding redistributions) has grown from 5% of GDP to 15-20%, which means we have overestimated the GDP growth, and the productivity, derived from that growth in spending.
– there is a similar issue with Healthcare, which is 15% of GDP in the US. Its efficacy is impossible to determine, and there is an established disconnect across modern countries between the spend, and metrics such as average life span.
– same thing with Education, which represents 6% of US GDP. Reading and mathematics scores at the age of 17 have not changed since the early 70s, while the expenditure corrected for inflation has doubled per pupil.

The looming question that the author then tackles is of the impact of the Internet. To summarise, he says that the Web provides huge innovation for the mind, not for the economy. It makes us happier and enables personal growth, but does not impact the economy very much, as so much of the content is free or very low cost.
So the Internet is also not properly reflected in GDP and productivity metrics, and that is one area where GDP underestimates the positive impact of technological change.

The issue though with the Internet revolution are the following :
– we have been counting on real productivity and material economic impact to generate future revenues and pay off our debts …
– the benefits from that revolution are unequally shared. Using the Internet positively is a function of one’s cognitive powers, while past inventions were usable equally by everyone.
– it creates few jobs. Google 20 000 employees, Facebook 1700…

The author then goes into an analysis of the current Economic crisis, which he sees as a result of overconfidence across our society in productivity. I am not convinced that should be the only explanation, but this is at least a refreshing view and a new angle.

Looking forward, despite the gloomy title of his book, Mr Cowen sees some positive future trends :
– india and china growth will create larger markets that will reward innovations again. They have so far grown by imitating the west, they will probably fuel innovation in the future.
– Internet might start generating growth. It creates a “cognitive surplus” (Clay Shirky) as billions of people are getting smarter and better connected, which would have positive effects on innovation.
– the Obama administration has taken steps to reform education

He conclude with an appeal to raising the status of scientists in our society, to make science and technology aspirational and rewarding careers for our children … Could not agree more !

http://www.amazon.com/Great-Stagnation-America-Low-Hanging-Eventually/dp/0525952713/ref=sr_1_1?s=books&ie=UTF8&qid=1309751050&sr=1-1

Wikileaks, good bad or indifferent ?

About a month back when the wikileaks disclosures began, we had a discussion with Aouda on wikileaks : was it right to divulge state secrets, including some that could give information to terrorists ?

As a business professional, my first reaction was to disagree. Even with the highest desire for openness and inclusiveness, we all know that we cannot always tell the naked truth. It could be misinterpreted, or used against the interests of the business. Or it could be that some things are just speculations, “what-if” scenarios that won’t end up being implemented, so why create anxiety or disruptions by communicating them ?

Aouda was reacting instead out of principles, and thought that the transparency brought about by wikileaks was a fantastic innovation.

Why did I personally change my mind on the matter and become an advocate of wikileaks ? I guess it boils down to some moral aspirations, coupled with some dose of cynicism and realism.

From a young age I’ve always dreamt of a world where the weak would be protected from the brute. This meant there had to be a way to immediately alert everyone to injustices being committed. That’s where the internet changes everything. Where it took a Zola to defend a Dreyfus, anyone today with a blog can draw the attention to events happening on the other side of the earth. See what just happened in Tunisia, where one of the most repressive police states could not hide the death of demonstrators.

So internet, and wikileaks, is probably the kind of “alert system” I was hoping for !

Beyond childhood dreams and naive aspirations, transparency could well be to public policies what democracy is to political systems. Churchill famously said that “Many forms of Government have been tried and will be tried in this world of sin and woe. No one pretends that democracy is perfect or all-wise. Indeed, it has been said that democracy is the worst form of government except all those other forms that have been tried from time to time.”.

Similarly, transparency will create privacy issues, will stir unwarranted troubles, but will on balance better than anything else drive fair play, honesty and justice.

Just my 2 cents here, so if you want to dig further, i found on this great french blog by Francis Pisani (http://pisani.blog.lemonde.fr/ Click here to follow) the following links to articles in english. Enjoy !

“Government should be transparent by default , secret by necessity.”

Heather Brooke, The Guardian

And the final word goes to Joseph Pulitzer himself : “There is not a crime, there is not a dodge, there is not a trick, there is not a swindle, there is not a vice which does not live by secrecy.”

Demography, Economy and Society

A theme is emerging in lots of recent readings – the impact of demographics on society and economy. We’ve probably ridden a wave of demographic explosion in the West over the past 50 years with the Baby Boom. And it’s interesting to look at the excesses of the bubble years, and the current bust, as the result of the savings of retiring Baby Boomers looking for high yields.

An example I recently read explained the interest rates as the demand-supply balance between the older and younger generations. The older people have savings, and in order to secure their retirement want to lend it to secure regular yield, as high as possible, ie high interest rates. The younger generation has no savings, but wants to borrow money to buy a home, start a business, and are looking for low interest rates. The proportion of both population hence drives the interest rate level – it is high if there is a large proportion of young people, low if there’s an excess of old people.

Aouda and I were born when the Baby Boomers entered the workforce, and when I read this all of a sudden the high interest rates my parents paid on their mortages started to make a lot of sense – as did the current low interest rates !

Of course, our world itself is highly bipolar in this regard – one of the biggest difference between the West and the high-growth countries is the demographic structure. Just look at an interactive map of the world as they now exist, and just browse various countries for the average age of their citizens, you will be amazed at the differences – US and Europe at 40 years (and sorry Mr Rumsfeld, there’s really no “Old Europe” and “New Europe” – it’s all pretty old all the way to Russia), versus India at 25 and Africa at 20 years of average age ! (Never forget Africa and its 1 Billion of people, even if they don’t make the news as they’ve not taken off economically yet). Very interestingly, China is already at an average age of 35 years, quite close to the US average age actually – not clear what the implications are, except it might mean China might be the Japan of yesteryears, which after explosive growth attracting everybody’s attention will rapidly stabilize and have to cope with its own issues.

This is such a fascinating topic, especially when you think beyond economics and look at the societal implications. A large young population giving us Woodstock, the Hippies and May ’68, what will these same folks drive in our culture and politics as they retire and become unsurprisingly conservative ?

Aouda is reading a book called “The 4th Turning” about supposed patterns in generations behaviors – interesting to see how that can shed some light into this issue !