Rational Thinking

Here is an example of using bayesian reasoning to wriggle between the extremes of ignoring a possible problem and giving oneself over to despair. This is from Tim Harford's blog in which he has allowed "Sophy" to post:

You’re a woman in her early fifties. You’re invited to a breast cancer screening unit, and you go along hoping for the all-clear. After all, 99 per cent of women your age do not have breast cancer. But … the scan is positive. The screening process catches 85 per cent of cancers. There is a chance of a false alarm, though: for 10 per cent of healthy women, the screening process wrongly points to cancer. What are the chances that you have breast cancer?

Over 50,000 British women face this awful question each year. I first encountered it – in a less alarming context – as an undergraduate economist. And I was in the audience recently when David Spiegelhalter used it as an example in his Simonyi Lecture, “Working Out the Odds (With the Help of the Reverend Bayes)”. The numbers approximately reflect the odds faced by women who go for breast cancer screening. And the answer – courtesy of the Reverend Bayes in question, who died 250 years ago – is surprising.

Bayes was concerned with how we should understand the notion of “probability”, and how we should update our beliefs in light of new information.

A Bayesian perspective on the apparently grim screening result tells us that things are not as bad as they seem. The two key pieces of information point in different directions. On the one hand, the positive scan substantially worsens the odds that you have cancer. But on the other, the odds are worsening from an extremely favourable starting point: 99 to 1 against. Even after the positive scan, you still probably don’t have cancer.

Imagine 1,000 women in your situation: 990 do not have cancer, which means we can expect 99 false positives, far more than the 10 women who do have cancer. This is why any apparent sign of cancer should be followed up with further tests in the hope of avoiding unnecessary treatments. The chance that you have cancer is 9 per cent – up dramatically from 1 per cent, but with plenty of room for optimism.

None of this proves screening is pointless. It can save lives, but it raises dilemmas. The UK’s breast cancer screening programme is currently under review. A systematic analysis published by the Cochrane Collaboration found that for every woman who had her life extended by early detection and treatment, there would be 10 courses of unnecessary treatment in healthy women, and more than 200 women would experience distress as the result of a false positive.

Bayesian reasoning has implications far beyond cancer screening, and we are not natural Bayesians. Daniel Kahneman, a psychologist who won the Nobel memorial prize in economics, discusses the issue in a new book, Thinking, Fast and Slow. I recently had the opportunity to quiz him in front of an audience at the Royal Institution in London. Kahneman argues that we often ignore baseline information unless it can somehow be made emotionally salient. New information – “possible cancer” – tends to monopolise our attention.

Another example: if somebody reads the Financial Times, should you conclude that they are more likely to be a quantitative analyst in an investment bank, or a public sector worker? Before you leap to conclusions, remember that there are six million public sector workers in the country. Base rates matter.

Sometimes there is no objective base rate and we must use our own judgment instead. I think homeopathy is absurd on theoretical grounds; others find it intrinsically plausible. Bayesian analysis tells us how to combine those prior beliefs – or prejudices – with whatever new evidence may come along.

Whenever you receive a piece of news that challenges your expectations, it’s tempting either to conclude that everything has changed – or that nothing has. Bayes taught us that there’s a rational path between those two extremes.

The value of mathematics, or logic, and rational thinking is that it gives you tools to work through the muddle of real life. Even models can be useful to provide a guide in a murky area. But the trick is to always realize that these tools are idealizations. The actual world isn't mathematical, logical, rational, or capturable in a model.

ECRI on the US Economy

ECRI seems to be the best prognosticator of the economy. This interview of Lakshman Achuthan reveals a serious concern about the direction of the US economy:

The Missing US Energy Policy

I remember teaching high school social studies classes from materials stating that "the end of oil" was at hand. I had to tell them that they would have to give up the idea of owning cars and heating their homes.

Needless to say, that doom-and-gloom scenario never came true. Instead I discovered that my father in the 1930s had been told about "the end of oil" while he was in school. Oh, and over the last 20 or 30 years the idea of "peak oil" has been very popular.

Here is a bit from an article in the Wall Street Journal pointing out that the Bakken formation in North Dakota and Montana puts America back into the same league as Saudia Arabia with oil reserves:

Harold Hamm, the Oklahoma-based founder and CEO of Continental Resources, the 14th-largest oil company in America, is a man who thinks big. He came to Washington last month to spread a needed message of economic optimism: With the right set of national energy policies, the United States could be "completely energy independent by the end of the decade. We can be the Saudi Arabia of oil and natural gas in the 21st century."

"President Obama is riding the wrong horse on energy," he adds. We can't come anywhere near the scale of energy production to achieve energy independence by pouring tax dollars into "green energy" sources like wind and solar, he argues. It has to come from oil and gas.

You'd expect an oilman to make the "drill, baby, drill" pitch. But since 2005 America truly has been in the midst of a revolution in oil and natural gas, which is the nation's fastest-growing manufacturing sector. No one is more responsible for that resurgence than Mr. Hamm. He was the original discoverer of the gigantic and prolific Bakken oil fields of Montana and North Dakota that have already helped move the U.S. into third place among world oil producers.

How much oil does Bakken have? The official estimate of the U.S. Geological Survey a few years ago was between four and five billion barrels. Mr. Hamm disagrees: "No way. We estimate that the entire field, fully developed, in Bakken is 24 billion barrels."

If he's right, that'll double America's proven oil reserves. "Bakken is almost twice as big as the oil reserve in Prudhoe Bay, Alaska," he continues. According to Department of Energy data, North Dakota is on pace to surpass California in oil production in the next few years. Mr. Hamm explains over lunch in Washington, D.C., that the more his company drills, the more oil it finds. Continental Resources has seen its "proved reserves" of oil and natural gas (mostly in North Dakota) skyrocket to 421 million barrels this summer from 118 million barrels in 2006.

"We expect our reserves and production to triple over the next five years." And for those who think this oil find is only making Mr. Hamm rich, he notes that today in America "there are 10 million royalty owners across the country" who receive payments for the oil drilled on their land. "The wealth is being widely shared."

The actual estimating of "reserves" is tricky. The lesson I learned is that governments don't estimate oil reserves. They rely on oil companies. And oil companies have no incentive to find oil for more than a 20 year window into the future, so they will always be predicting the "coming end of oil". Here's the Wikipedia estimate of oil reserves.

Another fundamental lesson to learn from the ridiculous history of decade after decade "end of oil" proclamations: modeling is hard. The conclusions follow very closely from your assumptions. The infamous Club of Rome made ridiculous assumption that "most of the exploitable oil has already been found" and that "energy use will rise exponentially". Both of these are wrong. The amount of reserves is a function of need and ingenuity. The use of energy is tied to technological innovation. Cars today normally get three times and could easily get five times the mileage of cars 50 years ago. As a society matures, infrastructure expenditures fall relative to other consumption, so energy use falls. Oil use has been declining for over a decade in the US. It isn't growing exponentially.

Paul Krugman Despairs the Economics is Not a Science

Paul Krugman has devoted his career to economics and has won a Nobel Prize, but he fells that he is living through a "Dark Age" in which economics has unlearned the lessons of the past. He is really despondent. Here is the relevant piece from a post on his NY Times blog:

I’ve never liked the notion of talking about economic “science” — it’s much too raw and imperfect a discipline to be paired casually with things like chemistry or biology, and in general when someone talks about economics as a science I immediately suspect that I’m hearing someone who doesn’t know that models are only models. Still, when I was younger I firmly believed that economics was a field that progressed over time, that every generation knew more than the generation before.

The question now is whether that’s still true. In 1971 it was clear that economists knew a lot that they hadn’t known in 1931. Is that clear when we compare 2011 with 1971? I think you can actually make the case that in important ways the profession knew more in 1971 than it does now.

I’ve written a lot about the Dark Age of macroeconomics, of the way economists are recapitulating 80-year-old fallacies in the belief that they’re profound insights, because they’re ignorant of the hard-won insights of the past.

What I’d add to that is that at this point it seems to me that many economists aren’t even trying to get at the truth. When I look at a lot of what prominent economists have been writing in response to the ongoing economic crisis, I see no sign of intellectual discomfort, no sense that a disaster their models made no allowance for is troubling them; I see only blithe invention of stories to rationalize the disaster in a way that supports their side of the partisan divide. And no, it’s not symmetric: liberal economists by and large do seem to be genuinely wrestling with what has happened, but conservative economists don’t.

And all this makes me wonder what kind of an enterprise I’ve devoted my life to.

I'm stunned that the field has shown itself that incompetent in the face of the 2008 financial crisis. But the academics fell in love with their models, the math, and the simplifying assumptions required to make the math and the models work. They took their eye off what is critical to any real science: the facts. They've turned economics into a branch of theology where the divines of the field debate the number of angels dancing on the head of a pin. They've gotten away from the hard insights of Keynes from the Great Depression. Tragic.

The Failings of Economic Theory

Paul Krugman has given an address entitled "The Profession and the Crisis" which excoriates economists for failing to understand the 2008 crisis. Here is one bit from that lecture:

But what became clear in the policy debate after the 2008 crisis was that many economists — including many macroeconomists — don’t know the simplest multiplier analysis. They literally know nothing about models in which aggregate demand can be determined by more than the quantity of money. I’m not saying that they have looked into such models and rejected them; they are unaware that it's even possible to tell a logically consistent Keynesian story. We’ve entered a Dark Age of macroeconomics, in which much of the profession has lost its former knowledge, just as barbarian Europe had lost the knowledge of the Greeks and Romans.

As long as monetary policy could bear the burden of macroeconomic stabilization, this didn’t seem to matter too much: even as equilibrium business cycle theory became increasingly dominant in graduate study, central banks, like medieval monasteries, kept the old learning alive. But once we were hit with such a severe banking and balance sheet crisis that monetary policy hit the zero lower bound, it was crucial that the economics profession be able to weigh in knowledgeably and coherently on other possible actions. And it turned out that it couldn’t.

You often hear people saying that the crisis has revealed the need for new economic thinking, for new ideas about macroeconomics. Yet the first priority seems to be to resuscitate old ideas. Brad DeLong describes an interview of Larry Summers by Martin Wolf as follows: “Asked to name where to turn to understand what was going on in 2008, Summers cited three dead men, a book written 33 years ago, and another written the century before last.” And in my view, Summers basically got it right.

How did all this knowledge get lost? Well, being the age I am, I was able to watch the transformation of macroeconomics in real time, and I’d say that what happened was a runaway social process.

First, success in academic economics came from publishing “hard” papers — meaning papers that used rigorous and preferably difficult mathematics. This in itself biased publication toward equilibrium business cycle models, as opposed to the ad hoc modeling typical of what I consider useful macroeconomics. Graduate education, in turn, became increasingly focused on the kind of work that could get published and lead to tenure. Successive cohorts of students were trained only in the newly rigorous version of macro, which had lost touch with the field's previous intellectual achievements.

And as these cohorts became professors in their turn, they closed off both publication and promotion to anyone who questioned the dominant academic approach. Robert Lucas wrote more than 30 years ago — approvingly! — about how participants in seminars would “whisper and giggle” when someone presented a Keynesian analysis. No wonder that any non-equilibrium ideas dropped out of the curriculum and the conversation.

All of this would have been OK if the triumph of anti-Keynesianism was justified by superior empirical success. But it wasn’t. As I read the history of the equilibrium approach, it's a story of failing upward. Lucas-type models clearly failed to account for the duration of slumps; rather than reconsider flexible prices and rational expectations, Lucas's followers moved on to real business cycles (RBC). RBC models failed to generate any strikingly successful predictions, and in fact lost whatever plausibility they had once productivity started becoming pro-cyclical rather than counter-cyclical. But by that time the people doing these models didn’t know that there was any alternative.

And the result was that faced with a severe economic crisis, the profession spoke with a cacophony of voices. Or maybe a better way to put it is that the policy debate of 2009–2010 was virtually indistinguishable from the policy debate of 1931–1932. Long-refuted doctrines that should have been consigned to the dustbin of history were stated as if they were fresh new ideas — and they were fresh and new to many economists, because our profession had lost so much of its heritage.

In short, in responding to the crisis, the profession presented a sorry spectacle of unnecessary ignorance that didn’t even recognize itself as ignorance, of bitter debate over issues that were resolved many decades earlier. And all of this, of course, made the profession mostly useless at a time when it could and should have been of great service. Put it this way: we would have responded better to this crisis if macroeconomics had been frozen at the level of knowledge it had in 1948, when Paul Samuelson published the first edition of his famous textbook. And the result has been to leave actual policy discussion without any discipline from the people who should be shaping that discussion: politicians and officials have been free to follow their prejudices and intuitions, never mind the lessons of history and analysis. Economists have failed to fulfill their social function.

The failure of economics is much more than a professional failure. It has demonstrated that the system of economics education, promotion and jobs, the publishing of papers, etc. has failed utterly. It has allowed smart people to convince themselves that they could ignore reality and focus on their "pretty models". Worse, it allowed them to actively purge dissidents and close up the professional shop. Sadly, this is exactly what climate scientists are doing with their models and the doling out of IPCC favoured funding. Like Keynes said of economics (in the long run we are all dead) can be said of science (it is a self-correcting search for truth, but in the short run it can be drastically wrong and the "long run" in which truth is finally achieved may effectively be so far in the future as to be non-existent, i.e. "science" can become a cult and not truly science at all).

Paul Krugman on Global Warming

I like Paul Krugman. I read most of what he writes and find him to be very bright and I generally agree with him. But I part company with him when he puts his "climatologist" cap on and pontificates as he has in his latest NY Times op-ed column:

The second part of Mr. Perry’s statement is, as it happens, just false: the scientific consensus about man-made global warming — which includes 97 percent to 98 percent of researchers in the field, according to the National Academy of Sciences — is getting stronger, not weaker, as the evidence for climate change just keeps mounting.

In fact, if you follow climate science at all you know that the main development over the past few years has been growing concern that projections of future climate are underestimating the likely amount of warming. Warnings that we may face civilization-threatening temperature change by the end of the century, once considered outlandish, are now coming out of mainstream research groups.

But never mind that, Mr. Perry suggests; those scientists are just in it for the money, “manipulating data” to create a fake threat. In his book “Fed Up,” he dismissed climate science as a “contrived phony mess that is falling apart.”

Krugman and I agree on holding Rick Perry in low esteem for his anti-science views. But I disagree with Krugman over global warming.

Take a look at this 130 year record of temperature anomaly data from NASA (note: "anomaly" means deviation from the average over the 130 year baseline):

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I don't see any "trend" and certainly no "runaway global warming" in the above graph.

OK... I cheated a bit. That is the continental US data. I trust that more than the global datasets because the network of stations in the US is thicker and is more likely to be monitored and calibrated better than measurements around the world. Also, the "world" is 3/4 ocean and there really are no stations gathering data there (sure some buoys and radiosondes that are occasionally dropped) like the coverage of the US. Here is the NASA global anomaly data:

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I prefer the following satellite temperature observations which uses the same sensor over the whole face of the earth. The only problem with satellites is calibrating the sensor and degradation of the sensor over time. But I trust the satellite more than I trust all the stations in the above "world" datasets (especially the “missing” stations covering 3/4 of the face of the earth, i.e. the oceans which aren't measured but "extrapolated" and sometimes for hundreds and even a thousand miles)

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To my eye, the above shows no discernible temperature "trend". Sure you can fit a line through the data and get a slight rise over time, but the signal is lost in the noise. I wouldn't trust that "trend".

The satellite is the most reliable, objective, global measure of "warming" and it doesn't support the purple prose of Paul Krugman:

we may face civilization-threatening temperature change by the end of the century

Neither Krugman nor I are climatologists. When Krugman cites 97% of "researchers in the field" believe in "global warming", I say so what? If you had canvased physicists in 1905 for a "belief" in warped space and time dilation you would have found 99.9% rejected the theory as preposterous. But Einstein's theory is true and is used every day in GPS systems and in the appropriate physics calculations. Science isn't a democracy where you vote on your favourite theory to establish its truth. It is consensus. But not a voting consensus. It is a hard fought consensus arrived at over time by experiment and working with the theory. Global warming isn't anywhere near that kind of "established" science right now.

I believe Paul Krugman is wrong and time will prove it. In the interim, I continue to admire him and agree with most things he says. I simply ignore his pontificating on "climate change". We both agree 100% that climate is changing and has always been changing. Where we disagree is over "anthropocentric global warming". I will admit that CO2 and other green house gases are increasing temperatures but I think he has the basic science corrupted by a reliance on computer modeling. I think the models are misleading. I think the science is incomplete:

• I believe that studies of cloud formation such as Svensmark's theory of sun-cosmic ray-cloud interaction will change "received" opinion


• I believe that Roy Spencer's cloud feedback mechanism will change "received" opinion


• I believe that Richard Lindzen's critique of climate models will change "received" opinion

I'm not a climatologist. I may be completely wrong. But I do read and I don't see the "consensus" that Al Gore, the IPCC, and Paul Krugman claim has "settled the science". I do see ambiguous data. I do see ideas struggling for a hearing. And I'm aware of how the funding agencies are creating a "false consensus" by putting money out there for "global warming" research. For years I've watched senior scientists who are beyond the tyranny of the funding agencies struggle with theories outside the "mainstream" of global warming. They struggle for a hearing. Since science isn't a beauty contest, I believe that eventually these voices will be heard and the simple "greenhouse gas" story will end up extensively revised by a much more sophisticated understanding of climatology.

Oh... and I heartily agree with Krugman's complaint about the anti-intellectualism and anti-science of the Republican party:

Now, we don’t know who will win next year’s presidential election. But the odds are that one of these years the world’s greatest nation will find itself ruled by a party that is aggressively anti-science, indeed anti-knowledge. And, in a time of severe challenges — environmental, economic, and more — that’s a terrifying prospect.

Stiglitz Gets a Laugh at the Idea that Macroeconomics is in Its Golden Age

Here is a lecture by George Stiglitz with the title "Imagining an Economics tthat Works: Crisis, Contagion and the Need for a New Paradigm" at the 2011 meeting of The Lindau Nobel Laureate Meetings at Lindau. He savages the state of macroeconomics: the fact that the 2008 economic collapse was not foreseen and has given no useful guidance in how to extract the world economy from the crisis:



Here is the abstract for this lecture:

The standard macroeconomic models have failed, by all the most important tests of scientific theory. They did not predict that the financial crisis would happen; and when it did, they understated its effects. Monetary authorities allowed bubbles to grow and focused on keeping inflation low, partly because the standard models suggested that low inflation was necessary and almost sufficient for efficiency and growth. Advocates of capital market liberalization argued that it would lead to greater stability: countries faced with a negative shock borrow from the rest of the world, allowing cross-country smoothing. The crisis showed the deep flaws in this thinking, but policymakers have been slow to rethink the paradigms they relied on. There is a need for a fundamental re-examination of the models. This lecture first describes the failures of the standard models in broad terms, and then develops the economics of deep downturns, and shows that such downturns are endogenous. Further, the lecture will argue that there have been systemic changes to the structure of the economy that made the economy more vulnerable to crisis, contrary to what the standard models argued. In particular, the lecture will explore how integration can exacerbate contagion; and how a failure in one country can more easily spread to others. There are conditions under which such adverse effects overwhelm the putative positive effects. Finally, the lecture will contrast the policy implications of our framework with those of the standard models; for instance, how capital controls can be welfare enhancing, reducing the risk of adverse effects from contagion.

Spinning Scare Stories

Here is a bit about Greenland which should puzzle those who are convinced that the world is going to hell in a handbasket by anthropogenic (i.e. "man made") global warming. This is a bit from a post by S Jay Porter on the Watts Up With That? blog:

In 1991, two caribou hunters stumbled over a log on a snowy Greenland riverbank, an unusual event because Greenland is now above the treeline. (1) Over the past century, further archaeological investigations found frozen sheep droppings, a cow barn, bones from pigs, sheep and goats and remains of rye, barley and wheat all of which indicate that the Vikings had large farmsteads with ample pastures. The Greenlanders obviously prospered, because from the number of farms in both settlements, whose 400 or so stone ruins still dot the landscape, archaeologists guess that the population may have risen to a peak of about five thousand. They also built a cathedral and churches with graves which means that the soil must have been soft enough to dig, but these graves are now well below the permafrost (2).

There is also a story in ‘Landnamabok, the Icelandic Book of Settlement, which tells of a man who swam across his local fjord to fetch a sheep for a feast in honour of his cousin, the founder of Greenland, Erick the Red. Studies of Channel swimmers show that 10C would be the lowest temperature that a man would be able to endure for such a swim, but the average August temperature of water in the fjords along the southern Greenland coast now rarely exceeds 6C. The water at that time must therefore have been at least 4C warmer and probably more than that which means that the summer temperatures (for the air) in the fjords in southern Greenland would then have been 13C-14C, (3) as compared with the present temperatures mentioned above.

It follows that temperatures must have been higher than those of today’s during that first settlement of Greenland which lasted from approximately 900 until the mid-1400s AD, when these settlements died out. There is no written explanation for this sudden demise but climate scientists have discovered that Iceland, like the rest of Europe, was gripped by a rapid and centuries-long drop in temperature, known as the Little Ice Age. And in a recent study, William D’Andrea and Yongsong Huang of Brown University, Providence RI (4) have traced the variability of the Greenland climate over a period of 5,600 years when previous inhabitants were also subjected to rapid warm and cold swings in temperatures

Yet the whole reason for the existence of the Intergovernmental Panel of Climate Change (IPCC) is to thrust upon the world’s population the idea that industrialisation in the West over the last 100 years and our profligate use of fossil fuels is producing a run-away heating of the planet through the emission of greenhouse gases, mainly CO2, which unless checked will lead to its — and humanity’s — death.

There is much more. Go read the whole post.

I find it funny that for 30 years IPCC has been telling us that the world is in a runaway global warming, but I sure as heck can't see the results. I bought a house behind a dike in 1983 and worried -- because of IPCC projections -- that I might have to abandon it by 2000 because of rising sea levels. The sea didn't rise. The house is still quite safe. Here in the Pacific Northwest we've had an unusually cold wet winter and no spring (a typical La Niña pattern). I see that the Antarctic ice sheet has a greater extent this summer than its 30 year average and there is no obvious pattern of a runaway "melting" of that ice cap. There is a slight melting in the arctic ice cap, but as the above story about Greenland should make clear, and this postings on ice-free conditions and submarine observations shows, it has melted in the past.

I've got no beef with the idea that humans can be affecting the climate. I just don't think that the modeling is convincing. And I do believe there is a witch hunt going on forcing climatologists to "toe the line" on global warming or lose their funding (see this and read it all very carefully because Roger Pielke Sr. is a solid climatologist).

I'm OK on environmentalism and conservation. I'm not OK with fanaticism. I trust science but I don't trust modeling (since I did computer modeling during my career and know how much of an "art" it is and how little of a "science"). What bugs me the most is that guys like Al Gore are selling global warming while in the business of making money off the global warming scare (via cap & trade) and while living a very wasteful, CO2 spewing lifestyle with multiple mansions with lots of floodlights and heating for next to no occupants in the homes:

Utility records show the Gore family paid an average monthly electric bill of about $1,200 last year for its 10,000-square-foot home.

The Gores used about 191,000 kilowatt hours in 2006, according to bills reviewed by The Associated Press spanning the period from Feb. 3, 2006, to Jan. 5. That is far more than the typical Nashville household, which uses about 15,600 kilowatt-hours per year.

How many houses can you live in at one time? (see this Business Insider report on his other mansion on the West Coast).

If I'm going to be lectured about CO2 and global warming, it had better be from somebody who is "holier than thou". Sadly, Al Gore doesn't pass the sniff test.

And fanatics like Al Gore stampede people into "solutions" which create more problems, e.g. this story about biodegradable products that create more problems than they solve by releasing even more powerful greenhouse gases than the "problem" waste they are trying to replace.

Here's the kind of "global warming" that I can buy into...

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The above graph shows oscillations which are well known in climatology. It shows an upward trend which I can buy as something to be understood (is a mix of forces on a larger scale including human infusion of greenhouse gases in the atmosphere), and a clear demonstration of the alarmism of the IPCC with their runaway global heat death prediction which diverges from reality (see the dot marking 2009).

The Collapse and Failure of Modern "Economics"

Here is a bit from an article in Foreign Affairs magazine which is reprinted in the blog Crooked Timber. The article looks at how monetary and economic policy in Europe is failing as that continent falls under the sway of "austerity" and the incompetence of "modern" economics:

The EU is now drifting toward a thinly disguised version of the gold standard, which wreaked economic havoc in the 1920s and led to a toxic political fallout. Under that system, European states had fixed exchange rates. During economic crises, they refused to increase government spending because of a failure to either understand or care that monetary disturbances and shocks to demand could lead to joblessness. The result was generalized misery. Governments responded to economic crises by allowing unemployment to go up and cutting back wages, leaving workers to bear the pain of adjustment. As Golden Fetters, Barry Eichengreen’s classic history of the period, shows, the gold standard began to collapse when workers in Europe gained the power to vote out of office the parties that supported austerity.

...

This approach cannot be sustained for long. The EU has never had much popular legitimacy: many voters have gone along with it so far only out of the belief that their politicians knew best. Today, they are more suspicious. And if they come to think that further European integration is causing more economic hardship, their suspicion could harden into bitterness and perhaps even xenophobia. Ireland’s new finance minister, Michael Noonan, has told voters that the EU is a game rigged in Germany’s favor; editorials in major Irish newspapers warn of Germany’s return to racist imperialism. As economic shocks hit other EU countries, politicians in those states will also look for someone to blame.

If the EU is to survive, it will have to craft a solution to the eurozone crisis that is politically as well as economically sustainable. It will need to create long-term institutions that both minimize the risk of future economic crises and refrain from adopting politically unsustainable forms of austerity when crises do hit. They must offer the EU countries that are the worst hit a viable path to economic stability while reassuring Germany, the state currently driving economic debates within the union, that it will not be asked to bail out weaker states indefinitely.

...

Contrary to the beliefs of nearly all anti-Keynesians—and, regrettably, some Keynesians, too—Keynesianism demands more, not less, fiscal rectitude in normal times than does the orthodox theory of balanced budgets that underpins the EU. John Maynard Keynes argued that surpluses should be accumulated during good years so that they could be spent to stimulate demand during bad ones. This lesson was well understood during the golden age of Keynesian social democracy, after World War II, when, aided by moderate inflation, the governments of the countries in the Organization for Economic Cooperation and Development greatly reduced their ratios of public debt to GDP. This approach should not be confused with the opportunistic support for large budget deficits evident, for example, among advocates of supply-side economics. If anything, “hard” Keynesianism suggests that the problem with the macroeconomic rules governing the euro is not that they are too tough and too detailed but that they are not tough or detailed enough. States in the eurozone should not be allowed to run moderate budget deficits in boom years, the Keynesian argument goes; instead, they should be compelled to run budget surpluses. The surpluses could then be saved in rainy-day funds or used to pay down government debt or, if the country had reached a satisfactory debt-to-GDP ratio, spent as a fiscal stimulus in the event of a crisis. Unlike the kind of budget management advocated by the German government, this approach does not seek to eliminate or minimize governments’ leeway to conduct fiscal policy. It gives governments up-front the means to manage demand whenever they might need to.

The call for "hard Keynesianism" is the right call. It is the call that points out that the last 80 years of "economics" has been a disaster and a mistake built around lovely mathematics but an idiotic understanding of markets and humans.

I think it is funny. The call for "hard Keynesianism" is the call to go back to Joseph in Egypt in 1000 BC when during the 7 fat years the Pharaoh stored up surpluses from the land to feed the people during the 7 lean years. That "modern" economics doesn't understand this need to lean against the wind says volumes about the incompetence of "modern economics".

Confusing the Tool with the Object of Study

There is an interesting controversy in biology over the concepts of eusociality and inclusive fitness.

This blog posting by Carl Zimmer on the Discover magazine site sums up the state of the controversy and identifies the key paper that is driving the current intellectual battles. Zimmer sides with the mathematical modelers. The other side is led by E. O. Wilson and is represented by this paper "The Evolution of Eusociality" in the Nature journal.

But I worry that the argument of inclusive fitness is an example of science mistaking the tool for the object of the science. Sure, if you make the assumptions of inclusive fitness you "explain" a large number of eusocial species. But I fear that models, as tools to tweeze out principles and help understand complex phenomena, get reified into "solutions" when in fact they are idealizations and can't handle all cases.

Carl Zimmer is dismissive of the E. O. Wilson paper, but it appears to me that Wilson has a valid criticism of the modelers. His point is the eusociality, while being extremely successful as a strategy, is rare in nature because it requires some unlikely series of steps and especially because it requires multilevel selection (a viewpoint that is anathema to the inclusive fitness crowd and many geneticists). But nature is complex and the drive to find simple models boxes you in conceptually. It is as if physics only allowed ideal gas laws and ignored any explanatory mechanisms that went below the level of an idealized billiard ball (i.e. models that attempt to describe real gas behaviour).

In a multicellular organism you have "eusociality" at a level of cells. Clearly you have reproductive division of labour, overlapping generations, and cooperative care of the young. And in this case, this is a degenerate and simplistic case of "inclusive fitness" because the genes in all cells are exactly the same. The odd cells that don't fit this pattern, e.g. blood cells, in fact do have the same genes until late in their "maturation" where they discard the nucleus with the DNA and go into a robo-mode. So in fact they do fit exactly the assumptions of inclusive fitness. But what about symbionts? How do lichen flourish? How does this cooperation arise since the originating algae/cyanobacterium and the fungus share no DNA? It does despite no fitting the mathematical model of inclusive fitness.

I like Wilson's attempt to understand the rise of eusociality in five phases:

1. Formation of groups in a freely mixing population.


2. Historical accidents that lead to the accumulation of traits that make the change to eusociality more likely (i.e. preadaptions).


3. The rise of eusocial alleles.


4. Natural selection operating on emergent traits among the cooperating organisms in a eusocial group.


5. Natural selection operating on competing eusocial groups with their variant emerging eusocial traits.

That explanation has the richness to ring true to me. It is a much more credible account than the simplistic inclusive fitness model which is a simple calculation that can't explain how eusociality arises and changes over time.

I enjoy Carl Zimmer, but I think he has made a mistake in picking a "winner" in this controversy. Sure the inclusive fitness guys may have the "numbers" to be persuasive. But science isn't a political contest. Ultimately it is effectiveness of a theory in explaining the real world. It may take some time, but I expect that Wilson and his crowd will win this argument, not the simple modelers of the inclusive fitness crowd. They have a very useful tool for analysis, but (in my humble opinion) they've made the mistake of confusing the tool with their object of study.

Getting Climate Worries into Perspective

Here's a bit from a very nice essay by MIT's atmospheric physcist and lead author of IPCC's Chapter 7, 'Physical Climate Processes and Feedbacks', Richard Lindzen. He is telling people to not fall for the doom-and-gloom hysteria about climate change being pushed by the climate modeling community:

The notion of a static, unchanging climate is foreign to the history of the earth or any other planet with a fluid envelope. The fact that the developed world went into hysterics over changes in global mean temperature anomaly of a few tenths of a degree will astound future generations. Such hysteria simply represents the scientific illiteracy of much of the public, the susceptibility of the public to the substitution of repetition for truth, and the exploitation of these weaknesses by politicians, environmental promoters, and, after 20 years of media drum beating, many others as well. Climate is always changing. We have had ice ages and warmer periods when alligators were found in Spitzbergen. Ice ages have occurred in a hundred thousand year cycle for the last 700 thousand years, and there have been previous periods that appear to have been warmer than the present despite CO2 levels being lower than they are now. More recently, we have had the medieval warm period and the little ice age. During the latter, alpine glaciers advanced to the chagrin of overrun villages. Since the beginning of the 19th Century these glaciers have been retreating. Frankly, we don’t fully understand either the advance or the retreat.

For small changes in climate associated with tenths of a degree, there is no need for any external cause. The earth is never exactly in equilibrium. The motions of the massive oceans where heat is moved between deep layers and the surface provides variability on time scales from years to centuries. Recent work (Tsonis et al, 2007), suggests that this variability is enough to account for all climate change since the 19th Century.

...

Climate alarmists respond that some of the hottest years on record have occurred during the past decade. Given that we are in a relatively warm period, this is not surprising, but it says nothing about trends.

Given that the evidence (and I have noted only a few of many pieces of evidence) strongly implies that anthropogenic warming has been greatly exaggerated, the basis for alarm due to such warming is similarly diminished. However, a really important point is that the case for alarm would still be weak even if anthropogenic global warming were significant. Polar bears, arctic summer sea ice, regional droughts and floods, coral bleaching, hurricanes, alpine glaciers, malaria, etc. etc. all depend not on some global average of surface temperature anomaly, but on a huge number of regional variables including temperature, humidity, cloud cover, precipitation, and direction and magnitude of wind. The state of the ocean is also often crucial. Our ability to forecast any of these over periods beyond a few days is minimal (a leading modeler refers to it as essentially guesswork). Yet, each catastrophic forecast depends on each of these being in a specific range. The odds of any specific catastrophe actually occurring are almost zero. This was equally true for earlier forecasts of famine for the 1980's, global cooling in the 1970's, Y2K and many others.

So relax. Don't let the Chicken Little's worry you. The world will go on. There is no ultimate catastrophe lurking around the corner.

Models vs. Facts

From a post on the Watts Up With That? blog comparing official predictions about the upcoming winter by the UK Met (meteorological) office, and the facts about the actual winter. This should make you awfully nervous to take any "long term" weather (or climate) forecast seriously:

Met Office 2008 Forecast: Trend of Mild Winters Continues

Met Office, 25 September 2008: The Met Office forecast for the coming winter suggests it is, once again, likely to be milder than average. It is also likely that the coming winter will be drier than last year.

Reality Check: Winter of 2008/09 Coldest Winter For A Decade

Met Office, March 2009: Mean temperatures over the UK were 1.1 °C below the 1971-2000 average during December, 0.5 °C below average during January and 0.2 °C above average during February. The UK mean temperature for the winter was 3.2 °C, which is 0.5 °C below average, making it the coldest winter since 1996/97 (also 3.2 °C).

Met Office 2009 Forecast: Trend To Milder Winters To Continue, Snow And Frost Becoming Less Of A Feature

Met Office, 25 February 2009: Peter Stott, Climate Scientist at the Met Office, said: “Despite the cold winter this year, the trend to milder and wetter winters is expected to continue, with snow and frost becoming less of a feature in the future.

“The famously cold winter of 1962/63 is now expected to occur about once every 1,000 years or more, compared with approximately every 100 to 200 years before 1850.”

Reality Check: Winter Of 2009/10 Coldest Winter For Over 30 Years

Met Office, 1 March 2010: Provisional figures from the Met Office show that the UK winter has been the coldest since 1978/79. The mean UK temperature was 1.5 °C, the lowest since 1978/79 when it was 1.2 °C.

Met Office July 2010: Climate Change Gradually But Steadily Reducing Probability Of Severe Winters In The UK

Ross Clark, Daily Express, 3 December 2010: ONE of the first tasks for the team conducting the Department for Transport’s “urgent review” into the inability of our transport system to cope with snow and ice will be to interview the cocky public figure who assured breakfast TV viewers last month that “I am pretty confident we will be OK” at keeping Britain moving this winter. They were uttered by Transport secretary Philip Hammond himself, who just a fortnight later is already being forced to eat humble pie… If you want a laugh I recommend reading the Resilience Of England’s Transport Systems In Winter, an interim report by the DfT published last July. It is shockingly complacent. Rather than look for solutions to snow-induced gridlock the authors seem intent on avoiding the issue. The Met Office assured them “the effect of climate change is to gradually but steadily reduce the probability of severe winters in the UK”.

Met Office 2010 Forecast: Winter To Be Mild Predicts Met Office

Daily Express, 28 October 2010: IT’S a prediction that means this may be time to dig out the snow chains and thermal underwear. The Met Office, using data generated by a £33million supercomputer, claims Britain can stop worrying about a big freeze this year because we could be in for a milder winter than in past years… The new figures, which show a 60 per cent to 80 per cent chance of warmer-than-average temperatures this winter, were ridiculed last night by independent forecasters. The latest data comes in the form of a December to February temperature map on the Met Office’s website.

Reality Check: December 2010 “Almost Certain” To Be Coldest Since Records Began

The Independent, 18 December 2010: December 2010 is “almost certain” to be the coldest since records began in 1910, according to the Met Office.

Met Office Predicted A Warm Winter. Cheers Guys

John Walsh, The Independent, 19 January 2010: Some climatologists hint that the Office’s problem is political; its computer model of future weather behaviour habitually feeds in government-backed assumptions about climate change that aren’t borne out by the facts. To the Met Office, the weather’s always warmer than it really is, because it’s expecting it to be, because it expects climate change to wreak its stealthy havoc. If it really has had its thumb on the scales for the last decade, I’m afraid it deserves to be shown the door.

A Frozen Britain Turns The Heat Up On The Met Office

Paul Hudson, BBC Weather, 9 January 2010: Which begs other, rather important questions. Could the model, seemingly with an inability to predict colder seasons, have developed a warm bias, after such a long period of milder than average years? Experts I have spoken to tell me that this certainly is possible with such computer models. And if this is the case, what are the implications for the Hadley centre’s predictions for future global temperatures? Could they be affected by such a warm bias? If global temperatures were to fall in years to come would the computer model be capable of forecasting this?

A Period Of Humility And Silence Would Be Best For Met Office

Dominic Lawson, The Sunday Times, 10 January 2010: A period of humility and even silence would be particularly welcome from the Met Office, our leading institutional advocate of the perils of man-made global warming, which had promised a “barbecue summer” in 2009 and one of the “warmest winters on record”. In fact, the Met still asserts we are in the midst of an unusually warm winter — as one of its staffers sniffily protested in an internet posting to a newspaper last week: “This will be the warmest winter in living memory, the data has already been recorded. For your information, we take the highest 15 readings between November and March and then produce an average. As November was a very seasonally warm month, then all the data will come from those readings.”

You would think with that much egg on their fact the UK Met office would throw in the towel. But no, true believers don't give up. They just issue another forecast based on another run of the model!

Stephen Baker's "The Numerati"

This book is a fun read. It discusses the trend toward data collection and data mining to understand humans. The author gives examples of this technology applied to the workplace, to shopping, to politics, terrorist hunting, medicine, and using a online dating service. It will acquaint you with the technology, its possibilities, and the dangers. It won't give you enough information to understand how the technology works or to really appreciate where, how, and to what extent this technology can be applied.

The writers style is breezy. He intrudes his own persona into the narrative. I especially loved the bit about how he cajoled his wife to sign up with him for a dating service to see if that service could spot them as "potential mates". He sheepishly had to admit it didn't because he put his preference down for a younger woman. Only after he correct this did his wife show up in the list of candidates. Whoa! I'm a little shocked that he would admit to this. I can only imagine how much boxing around the ears he got from his wife. Especially when she discovers that the whole world now knows this about him.

The term "numerati" is used by him to cover those who collect and analyze data, build models, and predict human behaviour. Here's a bit from the book:

... today's Numerati are plowing forward, with an eye on us. They're already stitching bits of our data into predictive models, and they're just getting warmed up. In the coming decade, each of us will spawn, often unwittingly, models of ourselves in nearly every walk of life. We'll be modeled as workers, patients, soldiers, lovers, shoppers, and voters. In these early days, many of the models are still primitive, making us look like stick figures. The ultimate goal though, is to build versions of humans that are just as complex as we are -- each one unique.

The book builds the story from chapter to chapter of how we are being mapped, reduced to numbers, and turned predictable. But almost as a throwaway line at the very end of the book emerges an alternative view. One that I endorse from my experience in computer modeling. Here is a bit of a conversation he had with a friend with a doctorate in computer science on this vision of the Numerati:

...he explains that once he too dreamed of modeling the world but has since concluded that math, while powerful, is flawed.

"Why?"

"Ever heard of garbage in, garbage out?" His point is that mathematicians model misunderstandings of our world, often using the data at hand instead of chasing down the hidden facts.

There is a nugget of truth in this statement, but it is mangled. The data isn't garbage. It us simply unstructured, unqualified, and never completely understood. The "interpretation" that the Numerati are taking is purely statistical. So they will never be able to filter out the misleading and untrue. They simply hope that with large enough piles of data their analysis will approximate ever more closely the real underlying person. But people are maddenly unreliable. Humans learn. Once they know they are being "inspected" they change behaviour. Fads are a good example. Once the trendsetters realize that the "trend" is becoming too popular, they abandon it and start a new one. The data is not "static" because people change. So the data is unreliable, ambiguous, misleading, changeable, and sometimes just wrong. At best you get a crude approximation from this.

The techniques of data analysis, data mining, etc. work best for things that are dumb and static. They will be very useful in medicine, e.g. looking at diseases and genetics, but they will never be definitive in creating a model of a "shopper" or a "voter" or anybody else who can change their mind. The techniques will be useful, but they won't be definitive. You just can't pin people down.

I do recommend that you read the book. It is enjoyable. It will teach you some things. But take it with a grain of salt.

Climate Models

Here is a fairly boring academic talk by Mike Hulme on climate models. It gives 4 measures of reliability and discusses the current climate models. From my perspective, it should give people some caution about swallowing "modeling results" holus bolus and without some skepticism.

Watch the video here.

Skip the first 18:00 minutes which include an introduction and some introductory remarks.

Having built computer models in my previous life, I watch this and chuckle at the careful terminology and tepid characterization of the climate modeling community's efforts. It is obvious that Hulme is highly constrained by a desire to keep his "academic standing" so his remarks end up being carefully hedged and qualified to ensure no academic reputations are threatened.

One oddity of this talk: why spend an hour talking about the need for reliability (on four different fronts) if there isn't an issue of reliability. You will notice that he never admits to any problems with model reliability. But he does give broad hints that this is badly needed. He sounds like a politician and not a scientist.

His only clear words are in the introduction where he talks about the origins of science and the need for experimental verification. This of course is completely impossible for "science" based on model predictions. Reading the tea leaves, it sounds like he is most keen on moving the modeling from the current "private" models jiggered in the back room to open platforms using open software standards where the modeling is released along with the model results to ensure that reliability can be evaluated by a wider public. This makes sense only if the current secretive modeling is in fact questionable (which it is). But he never clearly says "there is a problem which can be seen from this, and this, and this". Instead it is all airy fairy "we need reliable models and here are four directions in which you make models more reliable".

He mentions the UEA CRU e-mails but gives no indication of their relevance to a need to improve model reliability or indicate why the stench of scandal hangs over them. He admits that over the last "few years" there has been a decline in public acceptance of climate modeling "results". But he doesn't connect the dots.

Models & the IPCC

Here is an excellent post by Roger Pielke Sr. on his blog Climate Science:

I am reading the book The Grand Design by Stephen Hawking and Leonard Mlodinow. While the book involves a non-mathematical discussion of quantum physics and general relatively, among other topics, there is a concise summary on page 51 as to what is a “good model”.

They write

A model is a good model if it:

1. Is elegant


2. Contains few arbitrary or adjustable elements


3. Agrees with and explains all existing observations


4. Makes detailed predictions about future observations that can disprove or falsify the model if they are not borne out.

With respect to the mult-decadal global climate models, it is clear they fail these requirements to be a “good model”. As candidly summarized, for example, by Kevin Trenberth in 2007 [an IPCC WG1 author] [highlighting added]

“…there are no predictions by IPCC at all. And there never have been. The IPCC instead proffers “what if” projections of future climate that correspond to certain emissions scenarios. There are a number of assumptions that go into these emissions scenarios. They are intended to cover a range of possible self consistent “story lines” that then provide decision makers with information about which paths might be more desirable. But they do not consider many things like the recovery of the ozone layer, for instance, or observed trends in forcing agents. There is no estimate, even probabilistically, as to the likelihood of any emissions scenario and no best guess.Even if there were, the projections are based on model results that provide differences of the future climate relative to that today. None of the models used by IPCC are initialized to the observed state and none of the climate states in the models correspond even remotely to the current observed climate. In particular, the state of the oceans, sea ice, and soil moisture has no relationship to the observed state at any recent time in any of the IPCC models. There is neither an El Niño sequence nor any Pacific Decadal Oscillation that replicates the recent past; yet these are critical modes of variability that affect Pacific rim countries and beyond. The Atlantic Multidecadal Oscillation, that may depend on the thermohaline circulation and thus ocean currents in the Atlantic, is not set up to match today’s state, but it is a critical component of the Atlantic hurricanes and it undoubtedly affects forecasts for the next decade from Brazil to Europe. Moreover, the starting climate state in several of the models may depart significantly from the real climate owing to model errors. I postulate that regional climate change is impossible to deal with properly unless the models are initialized.

The current projection method works to the extent it does because it utilizes differences from one time to another and the main model bias and systematic errors are thereby subtracted out. This assumes linearity. It works for global forced variations, but it can not work for many aspects of climate, especially those related to the water cycle. For instance, if the current state is one of drought then it is unlikely to get drier, but unrealistic model states and model biases can easily violate such constraints and project drier conditions. Of course one can initialize a climate model, but a biased model will immediately drift back to the model climate and the predicted trends will then be wrong. Therefore the problem of overcoming this shortcoming, and facing up to initializing climate models means not only obtaining sufficient reliable observations of all aspects of the climate system, but also overcoming model biases. So this is a major challenge.”

The obvious answer to the questions posed regarding a “good model” in the Hawking and Mlodinow 2010 book is that the models used in the 2007 IPCC report are not “good models” as they fail all four of the requirements.

This failure does not mean we should not be concerned about the human addition of greenhouse gases (or other human and natural climate forcings), but it should cause policymakers and funders of climate model researchers to realize that they have been oversold on the scientific rigor of the IPCC models. The funding of model predictions decades into the future using these tools is not money well spent.

Climate Change Models

Here is an excellent post by Judith Curry, an American climatologist and chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology, who is willing to admit that the climate models which supposedly justify panic about global warming may not be of much real use. The key bit is where she says "A seminal event in the evolution of my thinking on this subject was a challenge I received at Climate Audit to host a thread related to climate models, which increased my understanding of why scientists and engineers from other fields find climate models unconvincing.":

What can we learn from climate models?

Posted on October 3, 2010
by Judith Curry

Short answer: I’m not sure.

I spent the 1990’s attempting to exorcise the climate model uncertainty monster: I thought the answer to improving climate models lay in improving parameterizations of physical processes such as clouds and sea ice (following Randall and Wielicki), combined with increasing model resolution. Circa 2002, my thinking became heavily influenced by Leonard Smith, who introduced me to the complexity and inadequacies of climate models and also ways of extracting useful information from weather and climate model simulations. I began thinking about climate model uncertainty and how it was (or rather, wasn’t) characterized and accounted for in assessments such as the IPCC. A seminal event in the evolution of my thinking on this subject was a challenge I received at Climate Audit to host a thread related to climate models, which increased my understanding of why scientists and engineers from other fields find climate models unconvincing. The Royal Society Workshop on Handling Uncertainty in Science motivated me to become a serious monster detective on the topic of climate models. So far, it seems that the biggest climate model uncertainty monsters are spawned by the complexity monster.

This post provides my perspective on some of the challenges and uncertainties associated with climate models and their applications. I am by no means a major player in the climate modeling community; my expertise and experience is on the topic of physical process parameterization, challenging climate models with observations, and extracting useful information from climate model simulations. My perspective is not in the mainstream among the climate community (see this assessment). But I think there are some deep and important issues that aren’t receiving sufficient discussion and investigation, particularly given the high levels of confidence that the IPCC gives to conclusions derived from climate models regarding the attribution of 20th century climate change and climate sensitivity.

I don’t think we can answer the question of what we can learn from climate models without deep consideration of the subject by experts in dynamical systems and nonlinear dynamics, artificial intelligence, mechanical engineers, philosophy of science, and probably others. I look forward to such perspectives from the Climate Etc. community.

There's a great deal more in her post. Go read the whole thing.

The issue of model verification and validation (V&V) is well known in the modelling community. (Here's a fairly standard presentation on it.) But apparently V&V isn't well known or well understood in the climate modelling community. Consequently they have set the world off on a many billion dollar (and soon-to-be trillion dollar) fiasco. They have disrupted economic growth (and force the starving poor to die) while these fanatics strive to "out green" each other in their zealotry to shut down economic growth to "save Mother Earth" from a (most likely) non-existent problem. This won't be the first time in human history when zealots have disrupted a society and imposed their fanatic views on others. But as the world has become globalized, the danger from fanatics like the "global warming" crowd or the Al Qaeda religious fundamentalists are becoming overwhelming. Fanatics can derail societies.

Consciousness Science

Carl Zimmer has an interesting article on consciousness in the NY Times. Here is a bit to give you a taste:

For Dr. Tononi, sleep is a daily reminder of how mysterious consciousness is. Each night we lose it, and each morning it comes back. In recent decades, neuroscientists have built models that describe how consciousness emerges from the brain. Some researchers have proposed that consciousness is caused by the synchronization of neurons across the brain. That harmony allows the brain to bring together different perceptions into a single conscious experience.

Dr. Tononi sees serious problems in these models. When people lose consciousness from epileptic seizures, for instance, their brain waves become more synchronized. If synchronization were the key to consciousness, you would expect the seizures to make people hyperconscious instead of unconscious, he said.

While in medical school, Dr. Tononi began to think of consciousness in a different way, as a particularly rich form of information. He took his inspiration from the American engineer Claude Shannon, who built a scientific theory of information in the mid-1900s. Mr. Shannon measured information in a signal by how much uncertainty it reduced.

...

Consciousness is not simply about quantity of information, he says. Simply combining a lot of photodiodes is not enough to create human consciousness. In our brains, neurons talk to one another, merging information into a unified whole. A grid made up of a million photodiodes in a camera can take a picture, but the information in each diode is independent from all the others. You could cut the grid into two pieces and they would still take the same picture.

Consciousness, Dr. Tononi says, is nothing more than integrated information. Information theorists measure the amount of information in a computer file or a cellphone call in bits, and Dr. Tononi argues that we could, in theory, measure consciousness in bits as well. When we are wide awake, our consciousness contains more bits than when we are asleep.

...

Networks gain the highest phi possible if their parts are organized into separate clusters, which are then joined. “What you need are specialists who talk to each other, so they can behave as a whole,” Dr. Tononi said. He does not think it is a coincidence that the brain’s organization obeys this phi-raising principle.

Dr. Tononi argues that his Integrated Information Theory sidesteps a lot of the problems that previous models of consciousness have faced. It neatly explains, for example, why epileptic seizures cause unconsciousness. A seizure forces many neurons to turn on and off together. Their synchrony reduces the number of possible states the brain can be in, lowering its phi.

Personally I don't this research is on the right track. Information theory is great for treating signals, coding, and noise, but I don't see it as particularly useful for measuring "consciousness". But it is intersting to put another contender in the ring. Maybe it will jog somebody into coming up with a better theory.

It is obvious that integration is an essential element of consciousness, but to reduce it to the ability to track "pinging" or a simulus through centres in the brain strikes me as simplistic. I'm in agreement with David Chalmers who is quoted at the end of the article:

Other researchers view Dr. Tononi’s theory with a respectful skepticism.

“It’s the sort of proposal that I think people should be generating at this point: a simple and powerful hypothesis about the relationship between brain processing and conscious experience,” said David Chalmers, a philosopher at Australian National University. “As with most simple and powerful hypotheses, reality will probably turn out to be more complicated, but we’ll learn something from the attempt. I’d say that it doesn’t solve the problem of consciousness, but it’s a useful starting point.”

Climate Sciene: The State of the Art

Here is an interview with Brian Hoskins, a climatologist with the Imperial College, London, interviewed by The Economist:



This is interesting because he does take a step back from the "science is settled" crowd and does admit to the "group think" going on in climate science. Notice that he says that climate models are "pretty lousy" and he talks about how models as they were made higher and higher resolution got better and then got worse which showed that they didn't understand something fundamental. When asked if that has been fixed, he evades giving a straight answer. In short, they haven't fixed it.

Nassim Nicholas Taleb on White Swans

Here is Nassim Nicholas Taleb, the author of the book The Black Swan talking about the failure of risk modeling and the role it played in the 2008 financial crisis:



The discussion of The Great Moderation is interesting. His thesis is that there was an accumulation of risk "only in the tails". With hindsight, this is correct. But it isn't clear to me that this claim is rock solid. The bit I agree with is that the really big risks always comes out of the blue and are unaccounted for. Where I begrudge Taleb is his calm assurance that this was all knowable in advance. It wasn't. The real and growing risk of 2008 wasn't a "fat tail" or "an accumulation of risk". These are empty words. The real risk was the confluence of risks documented in Michael Lewis's book The Big Short: the corruption of Wall Street mortgage securitization, the fradulent mortgage brokers with this NINJA loans, and the connivance of the rating agencies which had been captured by Wall Street and gave AAA ratings that lured big and supposedly "knowledgeable" investors to their doom, i.e. the pension funds, the municipalities that parked money is supposedly "safe" AAA securities.

Taleb is a salesman. He dances in abstractions and sounds very knowledgeable. But his words are empty. Real knowledge rests on facts. He has no facts. He is a theoretician living only in the clouds with after-the-fact "truisms".

Don't get me wrong. I enjoy listening to him. I like a lot of what he says, but I get frustrated because it is too theoretical and not enough factual.

I get really frustrated when he makes ridiculous statements like:

What happened to all that collected wisdom of 3000 years, the Bible, the Koran, early Christianity, the Romans, everyone learned the perils of debt. Now what happened to that wisdom in the business world. If you are facing uncertainty it is a bad idea to have private debt. I think it is criminal to transform private debt into public debt because you are taxing the unborn.

This is absolutely idiotic. This claim of "3000 years of wisdom" is a joke. There is no such thing. The claim that when you "face uncertainty" it is a bad idea to have private debt is a very bad joke. Life is always full of uncertainty. Is Taleb saying "never have any private debts"? That is nutty. And the idea that public debt is somehow worse than private debt is sheer nonsense. A debt is a debt is a debt. For some things private debts are effective, for others you need public debt because no private person could handle the debt. The invention of the stock market was to beef up the size of private debts, but even with the huge private firms of today, there are still some undertakings for which no private consortium is large enough to fund it. Taleb reminds me of so many academics I've known who fall in love with their own patter and abstractions. What he is saying is ridiculous.

What bugs me is that Taleb has been seduced by his notariety. He now is out selling half-baked ideas, selling himself as an instant expert on areas where he has no expertise. He has prostituted himself to fame.

The blather he goes on about public debt is dangerous and bad. Right now the world needs a Keynesian stimulus. His "warnings" about debt are part of the problem because they are stopping governments from doing what is essential: provide the missing demand until the private sector recovers. He is presenting himself in the camp of Hoover's Secretary of the Treasury, Andrew Mellon, with his idiotic "liquidate labor, liquidate stocks, liquidate farmers, liquidate real estate… it will purge the rottenness out of the system. High costs of living and high living will come down. People will work harder, live a more moral life. Values will be adjusted, and enterprising people will pick up from less competent people". Taleb is calling for "very severe austerity measures". This is nutty. This is a moralistic view that debt needs to be atoned for by blood, sweat, and tears. Keynes showed this is not true, but Taleb is a fool and hasn't read Keynes and hasn't studied history. He is presenting himself a Andrew Mellon redux.

One thing that really bugs me about Taleb: He shows no awareness of the suffering of average people. He lives in the abstrations of the financial markets. Bankers find it very easy to tell others to "tighten their belts" because they have never suffered poverty and starvation. In the real world, a Great Recession means 15 million are unemployed and suffering. Keynes focused on that suffering and wanted the society to get those resources back to work so there would be more to share. The poor are keenly aware when production falls below the frontier of possible production because the missing goods are exactly what is missing from their tables. The rich never miss this because their tables are always full. It is very easy for a banker, for a rich person, to prescribe "belt tightening" to others.

I have to make a mental not to refuse to listen to Taleb again. He has gone over to the dark side.

Crime: The Big Picture

Here's a nice visualization of crime in 2009 in San Francisco from Doug McCune:


Go to the site to see more. I like this visualization because it shows certain kinds of crime (prostitution, narcotics, and robbery) are highly localized. Others (vehicle theft, vandalism, and larceny) are generalized over the whole region. The message: if you know your town, you know which areas to avoid for certain types of crime.