Episode 143, Recorded on April 3, 1969
Guest: Noam Chomsky
Jim Rickards explains why there’s a financial crisis coming, and in so doing, reviews the unusual origins of his predictive analytics tool. He also explores complexity theory and Bayesian statistics. Jim Rickards is a renowned author and the chief global strategist at Meraglim. Filmed on July 12, 2018 in New York.
This has roots that go back to 9/11.12:24Tragic day, September 11, 2001, when the 9/11 attack took place.12:31And what happened then– there was insider trading in advance of 9/11.12:37In the two trading days prior to the attack, average daily volume and puts, which is short12:43position, put option buying on American Airlines and United Airlines, was 286 times the average12:50daily volume.12:51Now you don’t have to be an option trader, and I order a cheeseburger for lunch every12:55day, and one day, I order 286 cheeseburgers, something’s up.12:59There’s a crowd here.13:00I was tapped by the CIA, along with others, to take that fact and take it forward.13:06The CIA is not a criminal investigative agency.13:10Leave that to the FBI and the SEC.13:11But what the CIA said was, OK, if there was insider trading ahead of 9/11, if there were13:17going to be another spectacular terrorist attack, something of that magnitude, would13:22there be insider trading again?13:24Could you detect it?13:26Could you trace it to the source, get a FISA warrant, break down the door, stop the attack,13:30and save lives?13:31That was the mission.13:32We call this Project Prophecy.13:34I was the co-project director, along with a couple of other people at the CIA.13:39Worked on this for five years from 2002 to 2007.13:43When I got to the CIA, you ran into some old timers.13:47They would say something like, well, Al-Qaeda or any terrorist group, they would never compromise13:53operational security by doing insider trading in a way that you might be able to find.13:59And I had a two word answer for that, which is, Martha Stewart.14:03Martha Stewart was a legitimate billionaire.14:05She made a billion dollars through creativity and her own company.14:08She ended up behind bars because of a $100,000 trade.14:11My point is, there’s something in human nature that cannot resist betting on a sure thing.14:15And I said, nobody thinks that Mohamed Atta, on his way to Logan Airport, to hijack a plane,14:21stopped at Charles Schwab and bought some options.14:23Nobody thinks that.14:24But even terrorists exist in the social network.14:26There’s a mother, father, sister, brother safe house operator, car driver, cook.14:32Somebody in that social network who knows enough about the attack and they’re like,14:36if I had $5,000, I could make 50, just buy a put option.14:40The crooks and terrorists, they always go to options because they have the most leverage,14:44and the SEC knows where to look.14:47So that’s how it happens.14:49And then the question was, could you detect it.14:52So we started out.14:53There are about 6,000 tickers on the New York Stock Exchange and the NASDAQ.14:57And we’re talking about second by second data for years on 6,000 tickers.15:03That’s an enormous, almost unmanageable amount of data.15:06So what we did is we reduced the targets.15:08We said, well, look, there’s not going to be any impact on Ben and Jerry’s ice cream15:12if there’s a terrorist attack.15:14You’re looking at cruise ships, amusement parks, hotels, landmark buildings.15:18there’s a set of stocks that would be most effective.15:22So we’re able to narrow it down to about 400 tickers, which is much more manageable.15:26Second thing you do, you establish a baseline.15:28Say, what’s the normal volatility, the normal average daily volume, normal correlation in15:35the stock market.15:36So-called beta and so forth.15:37And then you look for abnormalities.15:39So the stock market’s up.15:42The transportation sector is up.15:43Airlines are up, but one airline is down.15:46What’s up with that?15:47So that’s the anomaly you look for.15:48And then the third thing you do.15:49You look for news.15:50Well, OK, the CEO just resigned because of some scandal.15:54OK, got it, that would explain why the stock is down.15:57But when you see the anomalous behavior, and there’s no news, your reference is, somebody16:03knows something I don’t.16:04People aren’t stupid, they’re not crazy.16:06There’s a reason for that, just not public.16:08That’s the red flag.16:09And then you start to, OK, we’re in the target zone.16:12We’re in these 400 stocks most affected.16:15We see this anomalous behavior.16:17Somebody is taking a short position while the market is up and there’s no news.16:21That gets you a red light.16:23And then you drill down.16:24You use what in intelligence work we call all source fusion, and say, well, gee, is16:28there some pocket litter from a prisoner picked up in Pakistan that says cruise ships or something16:34along– you sort of get intelligence from all sources at that point drilled down So16:38that was the project.16:40We built a working model.16:41It worked fine.16:42It actually worked better than we expected.16:44I told the agency, I said, well, we’ll build you a go-kart, but if you want a Rolls Royce,16:48that’s going to be a little more expensive.16:50The go-kart actually worked like a Rolls Royce.16:52Got a direct hit in August 2006.16:55We were getting a flashing red signal on American Airlines three days before MI5 and New Scotland17:04Yard took down that liquid bomb attack that were going to blow up 10 planes in midair17:09with mostly Americans aboard.17:11So it probably would have killed 3,000 Americans on American Airlines and Delta and other flights17:16flying from Heathrow to New York.17:18That plot was taken down.17:20But again, we had that signal based on– and they made hundreds of arrests in this neighborhood17:26in London.17:27So this worked perfectly.17:30Unfortunately, the agency had their own reasons for not taking it forward.17:37They were worried about headline risk, they were worried about political risk.17:41You say, well, we were using all open source information.17:45You can pay the Chicago Mercantile Exchange for data feed to the New York Stock Exchange.17:48This is stuff that anybody can get.17:49You might to pay for it, but you can get it.17:52But the agency was afraid of the New York Times headline, CIA trolls through 401(k)17:58accounts, which we were not doing.18:00It was during the time of waterboarding and all that, and they decided not to pursue the18:06project.18:07So I let it go, there were plenty of other things to do.18:09And then as time went on, a few years later, I ended up in Bahrain at a wargame– financial18:14war game– with a lot of thinkers and subject matter experts from around the world.18:20Ran into a great guy named Kevin Massengill, a former Army Ranger retired Major in the18:27US army, who was working for Raytheon in the area at the time was part of this war game.18:32We were sort of the two American, little more out of the box thinkers, if you want to put18:36it that way.18:38We hit it off and I took talked him through this project I just described.18:42And we said, well look, if the government doesn’t want to do it, why don’t we do it18:45privately?18:46Why don’t we start a company to do this?18:47And that’s exactly what we did.18:49Our company is, as I mentioned, Meraglim.18:51Our website, Meraglim.com, and our product is Raven.18:55So the question is, OK, you had a successful pilot project with the CIA.19:01It worked.19:02By the way, this is a new branch of intelligence in the intelligence.19:06I-N-T, INT, is short for intelligence.19:08And depending on the source, you have SIGINT, which is signal intelligence, you have HUMINT19:14which is human intelligence, and a number of others.19:17We created a new field called MARKINT, which is market intelligence.19:20How can you use market data to predict things that are happening.19:24So this was the origin of it.19:26We privatized it, got some great scientists on board.19:30We’re building this out ourselves.19:31Who partnered with IBM, and IBM’s Watson, which is the greatest, most powerful plain19:38language processor.19:40Watson can read literally millions of pages of documents– 10-Ks, 10-Qs, AKs, speeches,19:47press releases, news reports.19:51More than a million analysts could read on their own, let alone any individual, and process19:57that in plain language.19:58And that’s one of our important technology partners in this.20:02And we have others.20:04What do we actually do?20:07What’s the science behind this.20:09First of all, just spend a minute on what Wall Street does and what most analysts do,20:13because it’s badly flawed.20:15It’s no surprise that– every year, the Fed does a one year forward forecast.20:22So in 2009, they predict 2010.20:24In 2010, they predict 2011.20:27So on.20:28Same thing for the IMF, same thing for Wall Street.20:30They are off by orders of magnitude year after year.20:34I mean, how can you be wrong by a lot eight years in a row, and then have any credibility?20:38And again, the same thing with Wall Street.20:41You see these charts.20:43And the charts show the actual path of interest rates or the actual path of growth.20:48And then along the timeline, which is the x-axis, they’ll show what people were predicting20:52at various times.20:54The predictions are always way off the actual path.20:57There’s actually good social science research that shows that economists do worse than trained21:02monkeys on terms of forecasting.21:04And I don’t say that in a disparaging way– here’s the science.21:07A monkey knows nothing.21:08So if you have a binary outcome– up, down, high, low, growth, recession– and you ask21:17a monkey, they’re going to be right half the time and wrong half the time, because they21:20don’t know what they’re doing.21:21So you’re to get a random outcome.21:24Economists are actually wrong more than half the time for two reasons.21:28One, their models are flawed.21:29Number two, what’s called herding or group behavior.21:32An economist would rather be wrong in the pack than go out on a limb and maybe be right,21:37but if it turns out you’re not right, you’re exposed.21:40But there are institutional constraints.21:42People want to protect their jobs.21:44They’re worried about other things than getting it right.21:47So the forecasting market is pretty bad.21:48The reasons for that– they use equilibrium models.21:52The capital markets are not in equilibrium system, so forget your equal equilibrium model.21:57They use the efficient market hypothesis, which is all the information is out there,22:01you can’t beat the market.22:02Markets are not efficient, we know that.22:05They use stress tests, which are flawed, because they’re based on the past, but we’re outside22:12the past.22:13The future could be extremely different.22:16They look at 9/11, they look at long term capital management, they look at the tequila22:20crisis.22:21Fine, but if the next crisis is worse, there’s nothing in that history that’s going to tell22:25you how bad it can get.22:27And so they assume prices move continuously and smoothly.22:30So price can go from here to here or from here to here.22:34But as a trader, you can get out anywhere in between, and that’s for all these portfolio22:38insurance models and stop losses come from.22:41That’s not how markets behave.22:42That go like this– they just gap up.22:44They don’t hit those in between points.22:45Or they gap down.22:46You’re way underwater, or you missed a profit opportunity before you even knew it.22:51So in other words, the actual behavior of markets is completely at odds with all the22:56models that they use.22:57So it’s no surprise the forecasting is wrong.23:00So what are the good models?23:01What are the models that do work?23:03What is the good science?23:04The first thing is complexity theory.23:07Complexity theory has a long pedigree in physics, meteorology, seismology, forest fire management,23:13traffic, lots of fields where it’s been applied with a lot of success.23:18Capital markets are complex systems.23:20The four hallmarks of a complex system.23:24One is their diversity of actors, sure.23:26Two is their interaction– are the actors talking to each other or are they all sort23:30of in their separate cages.23:31Well, there’s plenty of interaction.23:33Is there communication and is there adaptive behavior?23:37So yeah, there are diverse actors, there’s communication.23:40They’re interacting.23:42And if you’re losing money, you better change your behavior quickly.23:45That’s an example of adaptive behavior.23:47So capital markets are four for four in terms of what makes a complex system.23:51So why not just take complexity science and bring it over to capital markets?23:55That’s what we’ve done, and we’re getting fantastic results.23:57So that’s the first thing.23:58The second thing we use is something called Bayesian statistics.24:03It’s basically a mathematical model that you use when you don’t have enough data.24:08So for example, if I’ve got a million bits of data, yeah, do your correlations and regressions,24:14that’s fine.24:15And I learned this at the CIA, this is the problem we confronted after 9/11.24:19We had one data point– 9/11.24:20Janet Yellen would say, wait for 10 more attacks, and 30,000 dead, and then we’ll have a time24:26series and we can figure this out.24:28No.24:29To paraphrase Don Rumsfeld, you go to war with the data you have.24:33And so what you use is this kind of inferential method.24:37And the reason statisticians dislike it is because you start with a guess.24:41But it could be a smart guess, it could be an informed guess.24:44The data may be scarce.24:45You make the best guess you can.24:47And if you have no information at all, just make it 50/50.24:50Maybe Fed is going to raise rates, maybe they’re not.24:53I think we do better than that on the Fed.24:55But if you didn’t have any information, you just do 50/50.24:58But then what you do is you observe phenomena after the initial hypothesis, and then you25:05update the original hypothesis based on the subsequent data.25:07You ask yourself, OK this thing happened later.25:10What is the conditional correlation that the second thing would happen if the first thing25:14were true or not?25:16And then based on that, you’d go back, and you either increase the probability of the25:19hypothesis being correct, or you decrease it.25:21It gets low enough, you abandon it, try something else.25:24If it gets high enough, now you can be a lot more confident in your prediction.25:27So that’s Bayesian statistic.25:29You use it to find missing aircraft, hunt submarines.25:32It’s used for a lot of things, but you can use it in capital markets.25:36Third thing, behavioral psychology.25:38This has been pretty well vetted.25:40I think most economists are familiar with it, even though they don’t use it very much.25:43But humans turn out to be a bundle of biases.25:48We have anchoring bias, we get an idea in our heads, and we can’t change it.25:52We have recency bias.25:54We tend to be influenced by the last thing we heard.25:57And anchoring bias is the opposite, we tend to be influenced by something we heard a long26:01time ago.26:03Recency bias and anchoring bias are completely different, but they’re both true.26:07This is how you have to get your mind around all these contradictions.26:11But when you work through that, people make mistakes or exhibit bias, it turns out, in26:16very predictable ways.26:18So factor that in.26:19And then the fourth thing we use, and economists really hate this, is history.26:23But history is a very valuable teacher.26:26So those four areas, complexity theory, Bayesian statistics, behavioral psychology, and history26:33are the branches of science that we use.26:35Now what do we do with it?26:37Well, we take it and we put it into something that would look like a pretty normal neural26:41network.26:42You have nodes and edges and some influence in this direction, some have a feedback loop,26:47some influence in another direction, some are influenced by others, et cetera.26:51So for Fed policy for example, you’d set these nodes, and it would include the things I mentioned26:55earlier– inflation, deflation, job creation, economic growth, capacity, what’s going on27:02in Europe, et cetera.27:03Those will be nodes and there will be influences.27:05But then inside the node, that’s the secret sauce.27:08That’s where we have the mathematics, including some of the things I mentioned.27:12But then you say, OK, well, how do you populate these nodes?27:15You’ve got math in there, you’ve got equations, but where’s the news come from?27:19That’s where Watson comes in.27:20Watson’s reading all these records, feeding the nodes, they’re pulsing, they’re putting27:24input.27:25And then we have these actionable cells.27:26So the euro-dollar cross rate, the Yuandollar cross rate, yen, major benchmark, bonds, yields27:36on 10 year treasury notes, bunds, JGBs, et cetera.27:41These are sort of macro indicators, but the major benchmark bond indices, the major currency27:46across rates, the major policy rates, which are the short term central bank rates.27:50And a basket of commodities– oil, gold, and a few others– they are the things we watch.27:55We use these neural networks I described, but they’re not just kind of linear or conventional28:06equilibrium models.28:07They’re based on the science I describe.28:09So all that good science, bringing it to a new field, which is capital markets, using28:13what’s called fuzzy cognition, neural networks, populating with Watson, this is what we do.28:19We’re very excited about it, getting great results.28:21And this is what I use.28:23When I give a speech or write a book or write an article, and I’m making forecast.28:28This is what’s behind it.28:32So we talked earlier about business cycles, recessions, depressions.28:37And that’s conventional economic analysis.28:40My definition of depression is not exactly conventional, but that’s really thinking in28:44terms of growth, trend growth, below trend growth, business cycles, et cetera.28:50Collapse or financial panic is something different.28:52A financial panic is not the same as a recession or a turn in the business cycle.28:57They can go together, but they don’t have to.28:59So let’s talk about financial panics as a separate category away from the business cycle29:04and growth, which we talked about earlier.29:06Our science, the science I use, the science that we use with Raven, at our company, Meraglim,29:12involves complexity theory.29:14Well, complexity theory shows that the worst thing that can happen in a system is an exponential29:21function of scale.29:23Scale is just how big is it.29:24Now you have to talk about your scaling metrics.29:27We’re talking about the gross notional value derivatives.29:28We’re talking about average daily volume on the stock market.29:31We’re talking about debt.29:33We could be talking about all of those things.29:35This is new science, so I think it will be years of empirics to make this more precise.29:39But the theory is good, and you can apply it in a sort of rough and ready way.29:43So you go to Jamie Dimon, and you say, OK, Jamie, you’ve tripled your gross notional29:50value derivatives.29:51You’ve tripled your derivatives book.29:53How much did the risk go up?29:54Well, he would say, not at all, because yeah, gross national value is triple, but who cares?29:59It’s long, short, long, short, long, short, long, short.30:01You net it all down.30:02It’s just a little bit of risk.30:04Risk didn’t go up at all.30:06If you ask my 87-year-old mother, who is not an economist, but she’s a very smart lady,30:10say, hey mom, I tripled the system, how much did the risk go up?30:14She would probably use intuition and say, well, probably triple.30:17Jamie Dimon is wrong, my mother is wrong.30:21It’s not the net, it’s the gross.30:22And it’s not linear, it’s exponential.30:24In other words, if you triple the system, the growth went up by a factor of 10, 50,30:28et cetera.30:29There’s some exponential function associated with that.30:32So people think, well gee, in 2008, we learned our lesson.30:36We’ve got debt under control, we’ve got derivatives under control.30:39No.30:40Debt is much higher.30:41Debt to GDP ratios are much worse.30:44Total notional value, gross notional values of derivatives is much higher.30:47Now people look at the BIS statistics and say, well, the banks, actually, gross national30:52value derivatives has been going down, which it has, but that’s misleading because they’re30:57taking a lot of that, moving it over to clearing houses.30:59So it’s never been on the balance sheet, it’s always been off balance sheet.31:02But even if you use the footnotes, that number has gone down for banks, but that’s only because31:07they’re putting it over clearing houses.31:09Who’s guaranteeing the clearing house?31:10The risk hasn’t gone away, it’s just been moved around.31:12So given those metrics– debt, derivatives, and other indices, concentration, the fact31:21that the five largest banks in America have a higher percentage of total banking assets31:26than they did in 2008, there’s more concentration– that’s another risk factor.31:31Taking that all into account, you can say that the next crisis will be exponentially31:37worse than the last one.31:38That’s an objective statement based on complexity theory.31:41So you either have to believe that we’re never going to have a crisis.31:44Well, you had one in 1987, you had one in 1994, you had one in 1998.31:49You had the dotcom crash in 2000, mortgage crash in 2007, Lehman in 2008.31:55Don’t tell me these things don’t happen.31:56They happen every five, six, seven years.31:59It’s been 10 years since the last one.32:02Doesn’t mean it happens tomorrow, but nobody should be surprised if it does.32:05So the point is this crisis is coming because they always come, and it will be exponentially32:11worse because of the scaling metrics I mentioned.32:14Who’s ready for that?32:15Well, the central banks aren’t ready.32:17In 1998, Wall Street bailed out a hedge fund long term capital.32:23In 2008, the central banks bailed out Wall Street.32:25Lehman– but Morgan Stanley was ready to fail, Goldman was ready to fail, et cetera.32:31In 2018, 2019, sooner than later, who’s going to bail out the central banks?32:35And notice, the problem has never gone away.32:37We just get bigger bailouts at a higher level.32:40What’s bigger than the central banks?32:42Who can bail out the central banks?32:43There’s only one institution, one balance sheet in the world they can do that, which32:46is the IMF.32:48The IMF actually prints their own money.32:51The SDR, special drawing right, SDR is not the out strawberry daiquiri on the rocks,32:55it’s a special drawing right.32:56It’s world money, that’s the easiest way to think about it.32:58They do have a printing press.33:00And so that will be the only source of liquidity in the next crisis, because the central banks,33:07if they don’t normalize before the crisis– and it looks like they won’t be able to, they’re33:11going to run out of runway, and they can expand the balance sheet beyond the small amount33:17because they’ll destroy confidence, where does the liquidity come from?33:20The answer, it comes from the IMF.33:23So that’s the kind of global monetary reset, the GMR, global monetary resety.33:28You hear that expression.33:31There’s something very new that’s just been called to my attention recently, and I’ve33:36done some independent research on it, and it holds up.33:39So let’s see how it goes.33:42But it looks as if the Chinese have pegged gold to the SDR at a rate of 900 SDRs per33:51ounce of gold.33:52This is not the IMF.33:53The IMF is not doing this.33:55The Federal Reserve, the Treasury is not doing it.33:58The ECB is not doing it.33:59If they were, you’d see it.34:00It would show up in the gold holdings.34:02You have to conduct open market operations in gold to do this.34:05But the Chinese appear to be doing it, and it starts October 1, 2016.34:11That was the day the Chinese Yuan joined the SDR.34:15The IMF admitted the Yuan to the group was four, now five currencies that make up the34:21SDR.34:22So almost to the day, when the Yuan got in the SDR, you see this a horizontal trend where34:29first, gold per ounce is trading between 850 and 950 SDRs.34:37And then it gets tighter.34:38Right now, the range is 875 to 925.34:41Again, a lot of good data behind this.34:44So it’s a very good, it’s another predictive indicator.34:47If you see gold around 870 SDRs per ounce, that’s a strong SDR, weak gold.34:54Great time to buy gold, because the Chinese are going to move back up to 900.34:58So that’s an example of science, observation, base and statistics, inference, all the things35:04we talked about that can be used today in a predictive analytic way.35:08A crisis is coming, because they always do.35:10I don’t have a crystal ball, this is plenty of history to back it up.35:13It’ll be exponentially worse.35:15That’s what the science tells us.35:16The central banks will not be prepared, because they haven’t normalized from the last one.35:20You’re going to have to turn to the IMF, and who’s waiting there but China with a big pile35:24of gold.
The New York Times columnist broke down what the Iraq was really about for Charlie Rose on May 29, 2003.
At the end of May 2003, America was on the verge of one of its longest-running, most expensive wars in Iraq. Yet Iraq war boosters were feeling vindicated by the swift march on Baghdad, which had fallen within weeks, and the swift collapse of the regime.
New York Times columnist Thomas Friedman, a fan of the Iraq war, appeared on Charlie Rose to crow about this rousing success on May 29 2003. The brief clip below from that interview (the full interview can be found here) is a fascinating glimpse into the id of Washington insiders like Friedman before the invasion in March of that year and for the first few months, at least, of what was to prove a long occupation.
He appears to still think it was the right choice. He wrote last June, in a column on Syria, that: “You can’t go from Saddam to Switzerland without getting stuck in Hobbes — a war of all against all — unless you have a well-armed external midwife, whom everyone on the ground both fears and trusts to manage the transition. In Iraq, that was America” and “the only reason Iraq has any chance for a decent outcome today is because America was on the ground with tens of thousands of troops to act as that well-armed midwife, reasonably trusted and certainly feared by all sides, to manage Iraq’s transition to more consensual politics.”
I don’t ever remember a time in my five years in Iraq where the US was generally seen as a trusted “midwife” by a majority, or even a large minority, of people. Whether or not Iraq might have a found a better, less bloody way out from the shadow of Saddam Hussein without an invasion and occupation, is now something forever unknowable.
(I just made the below transcript from the above clip. I’ve omitted most “uhms” and the like, and may have made one or two errors since the audio is a bit compromised):
Rose: “Now that the war is over and there’s some difficulty with the peace, was it worth doing?”
Friedman: “I think it was unquestionably worth doing Charlie, and I think that looking back that I now certainly feel I understand what the war was about and it’s interesting to talk about it here in silicon valley because I think looking back at the 1990s I can identify there are actually three bubbles of the 1990s, there was the Nasdaq bubble, there was the corporate governance bubble, and lastly there was what I would call the terrorism bubble, and the first two were based on creative accounting and the last two were based on moral creative accounting. The terrorism bubble that built up over the 1990s said flying airplanes into the World Trade Center, that’s Ok. Wrapping yourself with dynamite and blowing up Israelis in the pizza parlour, that’s Ok. Because we’re weak and they’re strong and the weak have a different morality. Having your preachers say that’s Ok? That’s Ok. Having your charities raise money for people who do these kinds of things? That’s Ok. And having your press call people who do these kind of things martyrs? That’s Ok. And that build up as a bubble, Charlie. And 9/11 to me was the peak of that bubble. And what we learned on 9/11 in a gut way was that bubble was a fundamental threat to our society because there is no wall high enough no INS agent smart enough no metal detector efficient enough to protect an open society from people motivated by that bubble. And what we needed to do was to go over to that part of the world and burst that bubble. We needed to go over there basically uhm, and, uh, uhm take out a very big stick, right in the heart of that world and burst that bubble. And there was only one way to do it because part of that bubble said ‘we’ve got you’ this bubble is actually going to level the balance of power between us and you because we don’t care about life, we’re ready to sacrifice and all you care about is your stock options and your hummers. And what they needed to see was American boys and girls going house to house from Basra to Baghdad uhm, and basically saying which part of this sentence don’t you understand. You don’t think we care about our open society, you think this bubble fantasy we’re going to just let it go, well suck on this. Ok. That, Charlie, was what this war was about. We could have hit Saudi Arabia. It was part of that bubble. We could have hit Pakistan, We hit Iraq, because we could. And that’s the real truth. “
What’s maybe most interesting about this bizarre set of views was that they were so commonplace back then. Al Qaeda has hit the United States, so we must hit back at them. Not just at Al Qaeda, or the people who might have directly assisted them, but a much bigger “them:” A whole civilization who had started to loom in the sight of people like Thomas Friedman as an existential threat to America.
Saddam Hussein had nothing to do with 9/11. The Iraqi people had had nothing to do with 9/11. Were there people there who were delighted to see the US get a bloody nose from Osama bin Laden? Yes. The previous decade had seen a US-backed sanctions effort targeting Saddam Hussein that crippled the country. Never mind that Saddam brought that upon his people with the invasion of Kuwait. Average people were the ones who suffered the most. In 1999 UNICEF estimated that the mortality rate for children under the age of five had doubled in central and southern Iraq since sanctions were imposed, from 56 dead children per 1,000 between 1984-1989 to 131 per 1,000 between 1994-1999.
I don’t begrudge them their anger, not least because they weren’t doing anything to harm people here in the US. I never understood the terror that seemed to grip so many Americans after 9/11, perhaps because by that point I’d covered small wars and grasping poverty we haven’t seen the likes of in the US for generations across Southeast Asia. A few years prior, I covered the independence of East Timor. The murder of Monitor stringer Sander Thoenes there was what led me to getting picked up by the paper — and he was just one of over 100,000 excess deaths in the tiny country during Indonesia’s 24-year occupation. For comparison, that was one in seven people in East Timor. One in seven Americans dying as the result of war and occupation would be 44 million people.
I had schoolmates who died in the towers, one dear friend who departed from the heights of Tower Two just minutes before it would have been too late, and who struggled with survivor’s guilt about the colleagues who stayed at their desks, for years after (most reckoned the plane that had crashed into the first tower was an accident, not a terrorist attack). It effected me, as it effected almost all Americans.
But it didn’t seem that hard to keep some perspective. And having lived in Muslim majority Indonesia since 1993 and spending the years after 9/11 covering Al Qaeda and aligned militant groups in the region, I’d learned enough to know that a war that could be painted as against Muslims in general would suit Al Qaeda right down to the ground – such a reaction is what they wanted, since they reckoned that would yield them a bonanza of new recruits.
Mr. Friedman has gone from strength to strength in the years since, with handsome speakers fees for him to explain his theories about how the world is changing and evolving. But that brief clip above shows a man whose analysis is easily swayed by emotion, by sentiment.
“What they needed to see was American boys and girls going house to house from Basra to Baghdad and basically saying which part of this sentence don’t you understand. You don’t think we care about our open society, you think this bubble fantasy we’re going to just let it go, well suck on this” is not the sort of comment that comes from dispassionate, reasoned analysis. It comes from fear.
We learned in a “gut way (that) bubble was a fundamental threat to our society?” That’s not really learning. As horrible as that attack on us was, there was no fundamental threat to our society. We have done a good job in the years since increasing security (to the point that, in some views, we have actually threatened our own open society ourselves) and preventing any further major attacks on our soil. Did the invasion of Iraq and taking out “a very big stick” accomplish that? No.
Finally, even the notion of a “terrorism bubble” in the 1990s was a bit of a myth. The decade that the 9/11 attacks began so horrifically was among the safest ones when terrorism in the skies is considered ever (since supplanted by the last decade). There were 469 fatalities for passengers, crews and passengers for commercial fliers in the 2000s, 256 of those on 9/11. In the 1990s, there were just under 400 fatalities. In the 1980s, there were about 1,400 and in the 1970s, there were just over 800 killed. When total number of commercial flights are included to make apples to apples comparisons, the most dangerous decade was the 1930s, with 616 fatalities per billion passenger flights. The 2000s had 22 per billion flights taken.
If there has been a “terrorism” bubble it appeared to have burst around 1991, judging by this graph at the Global Terrorism Database maintained at the University of Maryland with funding from the Department of Homeland Security. Terrorism, though, surged again after 2003, largely with a rise in terrorist incidents in Afghanistan and Iraq associated with the wars being fought in those lands.
At this time of looking back, let’s try to remember the track records and quality of argument presented by people whose views and advice are sought before the wars of our future.
Hurricanes, floods, and wildfires aside, climate change is delivering another threat: a remaking of geopolitics that stands to empower some of America’s adversaries and rivals.
As Arctic ice melts, Russia stands to gain access to oil and gas fields historically locked beneath northern ice — and is building up capability to launch cruise missiles from newly navigable waters to threaten America’s coastlines.
As polar seaways open up, China is eyeing a new “Polar Silk Road” — shorter shipping routes that could cut weeks off of shipping times from Asia to Europe.
And as drought drives more farmers and herders off their lands, extremist groups in Africa and the Middle East are finding fresh recruits.
These are just some of the ways climate change stands to reshape the power dynamics between nations that emerged from interviews for POLITICO’s Global Translations podcast.
Climate change is “making all of our challenges — whether it’s
- weapons of mass destruction,
- violent extremism or
- great power competition between China and Russia —
that much more challenging,” said Sherri Goodman, a former deputy undersecretary of defense who led studies of climate impacts on national security for the Center for Naval Analyses.
Some of the biggest power shifts are around the Arctic, which Goodman called “ground zero for the nexus of national security and climate change. In our lifetime, a whole new ocean has opened up because with climate change the sea ice is retreating, the oceans are warming and the permafrost is collapsing.”
A global quest for resources is already underway in the Arctic, said Goodman, now a senior fellow at the Woodrow Wilson Center Polar Institute. “There are thought to be vast stores of fossil fuels, oil and gas and minerals across the Arctic that have not yet been tapped. Russia is doing so today across its vast Arctic coastline with the help of China,” she said.
Russia is vying for control of Arctic seaways and has built some 40 icebreakers — ships that can channel through ice. “Russia envisions under Putin a northern sea route that is essentially a toll road that requires Russian Arctic escorts in the form of icebreakers or other patrol boats, escorting not only the Chinese but others who want to ship across the Arctic,” she said. By contrast, the U.S. has only two icebreakers, she said.
Meanwhile, China, which is not a polar country, has launched aggressive Arctic diplomacy and gained non-voting observer status for itself at the Arctic Council, the international forum that addresses policy in the Arctic. Last year, China issued its first arctic policy.
“It envisions a Polar Silk Road that stretches from Shanghai across potentially to Hamburg and Reykjavik and parts of Europe across Russia’s vast northern sea route hugging the Russian coastline and both exploiting the energy resources there, potential transport opportunities, shipping, research,” Goodman said.
President Donald Trump’s interest in buying Greenland was driven in part by resources newly available because of melting ice. The Danish government quickly rebuffed the idea, but the incident could be seen as an acknowledgment of climate change from a leader who has derided global warming as a hoax.
Climate change poses additional security consequences. U.S. military bases at home and abroad have already been strained by destructive hurricanes and flooding that have cost billions of dollars to repair — and extreme weather has stretched thin the disaster response capabilities of the military. When hurricanes hit Florida and Puerto Rico and the East Coast of the United States in 2017 and 2018, the military had to slow the flow of forces to Afghanistan in order to be able to provide relief at home. Meanwhile, troops have to operate in higher temperatures across Asia and the Middle East, where temperatures now regularly are over 100 degrees and face a broader array of infectious diseases.
Florida’s Tyndall Air Force Base incurred billions of dollars in damage from Hurricane Michael in 2018 when winds tore through the roofs of hangars and destroyed buildings. Congress has in recent years directed the Department of Defense to address the climate resilience of military bases and climate risks to operating forces.
“The Department of Defense is beginning to integrate these risks into its strategy plans and plans,” Goodman said.
Another geopolitical threat is migration — whether from low-lying island states that stand to lose fresh water drinking supply or coastal areas susceptible to typhoons. Prolonged drought is believed to contribute to conflicts in the Middle East.
“We know that in Syria the prolonged drought that preceded the civil unrest there was a contributing factor to that unrest, which became instability, which led to the violent extremism, which has become the deadliest civil war in modern times,” she said.
Elsewhere, drought-prone countries are buying up land to grow water-intensive crops in what is called the “virtual water” trade. For example, China has been buying agricultural land in the U.S. and Europe to harvest water-intensive crops such as alfalfa.
Simon Dalby, a professor of geography and environmental studies at Wilfrid Laurier University, told the podcast that the geopolitical consequences can be difficult to predict. He cited the impacts of a 2010 drought in Russia which led the Kremlin to limit wheat exports, setting off a chain reaction.
“International markets panicked. The price went up quickly — and it is indeed suggested that in fact part of the Arab Spring was partly a response to those price fluctuations. So political disturbances across the Middle East might indeed have been related to the drought in Russia, which was probably at least partly caused by climate fluctuations. So this is where we see how dramatically the global economy and the ecology is interconnected,” he said.
The world will need emergency stockpiles of food and disaster relief aid, he said.
And, he noted, while warming may open up certain regions to new agriculture, unpredictable rainfall and flooding can wreak havoc on crops. “This is much trickier than simply saying, ‘Oh because it’s warmer, Russia will do better.’ It’s not that simple,” he said.
Climate change is transforming agriculture itself.
Increased concentration of carbon dioxide in the atmosphere ramps up photosynthesis and makes crops grow more quickly. But the phenomenon has been shown to reduce nutrient density in some crops, like rice. Researchers have begun studying how many people might be at risk for iron or zinc deficiency as a result.
Like governments, businesses are studying how to address long-term risks to their business models, said Gary Litman, vice president for global initiatives at the U.S. Chamber of Commerce.
“We definitely need to prepare, to adjust, to adapt to climate change to mitigate the impact of the industry on climate,” he said. But he added that it’s part of a broader pressure on companies to address long-term environmental sustainability and compete for increasingly scarce resources. “We’re dealing with finite resources. There’s not going to be more cobalt on this planet. There is not going to be new soil on this planet. There is not going to be a new oxygen on this planet,” he said.
He noted that advanced technologies, such as batteries, require rare metals. “You cannot address the climate issue — you cannot prepare, for example, for the rise of the oceans — if you don’t invest in new construction materials. How do you build the dam? If you use the current resources, you’ll run out of gravel before you build anything. If you don’t have access to reliable supply of cobalt, you won’t be able to switch to e-mobility,” he said.