Tim Harford's Blog, page 58

Will economists ever be as good at forecasting as meteorologists?

The UK’s national weather service, the Met Office, is to get a £1.2bn computer to help with its forecasting activities. That is a lot of silicon. My instinctive response was: when do we economists get one?

People may grumble about the weather forecast, but in many places we take its accuracy for granted. When we ask our phones about tomorrow’s weather, we act as though we are gazing through a window into the future. Nobody treats the latest forecasts from the Bank of England or the IMF as a window into anything.

That is partly because politics gets in the way. On the issue of Brexit, for example, extreme forecasts from partisans attracted attention, while independent mainstream forecasters have proved to be pretty much on the money. Few people stopped to praise the economic bean-counters.

Economists might also protest that nobody asks them to forecast economic activity tomorrow or even next week; they are asked to describe the prospects for the next year or so. True, some almanacs offer long-range weather forecasts based on methods that are secret, arcane, or both — but the professionals regard such attempts as laughable.

Enough excuses; economists deserve few prizes for prediction. Prakash Loungani of the IMF has conducted several reviews of mainstream forecasts, finding them dismally likely to miss recessions. Economists are not very good at seeing into the future — to the extent that most argue forecasting is simply none of their business. The weather forecasters are good, and getting better all the time. Could we economists do as well with a couple of billion dollars’ worth of kit, or is something else lacking?

The question seemed worth exploring to me, so I picked up Andrew Blum’s recent book, The Weather Machine, to understand what meteorologists actually do and how they do it. I realised quickly that a weather forecast is intimately connected to a map in a way that an economic forecast is not.

Without wishing to oversimplify the remarkable science of meteorology, one part of the game is straightforward: if it’s raining to the west of you and the wind is blowing from the west, you can expect rain soon. Weather forecasts begin with weather observations: the more observations, the better.

In the 1850s, the Smithsonian Institution in Washington DC used reports from telegraph operators to patch together local downpours into a national weather map. More than a century and a half later, economists still lack high-definition, high-frequency maps of the economic weather, although we are starting to see how they might be possible, tapping into data from satellites and digital payments. An example is an attempt — published in 2012 — by a large team of economists to build a simulation of the Washington DC housing market as a complex system. It seems a long way from a full understanding of the economy, but then the Smithsonian’s paper map was a long way from a proper weather forecast, too.

Weather forecasters could argue that they have a better theory of atmospheric conditions than economists have of the economy. It was all sketched out in 1904 by the Norwegian mathematician Vilhelm Bjerknes, who published “The problem of weather prediction”, an academic paper describing the circulation of masses of air. If you knew the density, pressure, temperature, humidity and the velocity of the air in three dimensions, and plugged the results into Bjerknes’s formulas, you would be on the way to a respectable weather forecast — if only you could solve those computationally-demanding equations. The processing power to do so was to arrive many decades later.

The missing pieces, then: much better, more detailed and more frequent data. Better theory too, perhaps — although it is striking that many critiques of the economic mainstream seem to have little interest in high-resolution, high frequency data. Instead, they propose replacing one broad theory with another broad theory: the latest one I have seen emphasises “the energy cost of energy”. I am not sure that is the path to progress.

The weather forecasters have another advantage: a habit of relentless improvement in the face of frequent feedback. Every morning’s forecast is a hypothesis to be tested. Every evening that hypothesis has been confirmed or refuted. If the economy offered similar daily lessons, economists might be quicker to learn. All these elements are linked. If we had more detailed data we might formulate more detailed theories, building an economic map from the bottom up rather than from the top down. And if we had more frequent feedback, we could test theories more often, making economics more empirical and less ideological.

And yet — does anyone really want to spend a billion pounds on an economic simulation that will accurately predict the economic weather next week? Perhaps the limitations of economic forecasting reflect the limitations of the economics profession. Or perhaps the problem really is intractable.

 

Written for and first published in the Financial Times on 21 February 2020.

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Book of the week 11: Uncharted by Margaret Heffernan

“The sagacious businessman is constantly forecasting,” said the great economist Irving Fisher, a man thoroughly convinced of the power of data to make the future legible. Fisher transformed economics and made millions as an entrepreneur, but died in penury. He is now best remembered as the tragic figure who, shortly before the cataclysmic Wall Street crash of 1929, informed the nation: “Stocks have reached what looks like a permanently high plateau.”

Poor Professor Fisher appears early on in Uncharted. Margaret Heffernan’s book is less a smackdown of failed forecasts than an engaging ramble across our attempts to predict, control, explore or embrace an uncertain future. Heffernan is admired for books that question the received wisdom of how management works; she is a business guru who brings the stern discipline of good sense to the business book genre. In this book, she turns her attention to a topic that absorbs most business leaders — and the rest of us too: how to think about what the future holds. Gazing into the future is not fruitless, she argues, but it is unnerving and hard work. Lazy and fearful, we are far too quick to reach for overblown gurus, or misleading data or other useless guides. Even a good tool, such as GPS, can dull our senses.

“What matters most isn’t the predictions themselves but how we respond to them, and whether we respond to them at all,” she writes. “The forecast that stupefies isn’t helpful, but the one that provides fresh thinking can be.”

And fresh thinking is what Heffernan wishes to provoke, mostly through storytelling, occasionally through rhetoric. Are we trapped by history? Only if we let our own narratives confine us. Can parents use an app to “predict life outcomes and . . . maximise the life-long potential of your child”? No. She finds the idea appalling.

Better, she suggests, to explore, empower, experiment. Whether you’re running a multinational, pondering a career change or being a parent, the same wisdom applies: sometimes things go wrong, or go right, and we don’t know why. Keep your eyes open. Stay engaged. Listen to others. Don’t be afraid to change course. Contribute to your community, and make connections before trouble strikes: “Don’t exchange business cards in a crisis.”

At times, Uncharted resembles a collection of secular sermons illustrated with a story. Heffernan stands in the pulpit quietly admonishing us to be a little wiser, reflect a little more, to do the things that deep down we already know we should be doing.

Moments of counterintuitive astonishment are scarce, but the book is probably better for that. And it largely avoids the usual suspects: Apple, Google, 3M, the US military. Instead, we find ourselves in the shoes of a disillusioned Catholic priest, realising he has fallen in love and getting no help from the Church. Or in a room with a diverse group of Mexicans, from mobsters to senators, as they try to explore the future with a scenario-planning exercise. Or with the management of Nokia, wondering if there is life after cell phones. These are subtle tales of struggle and compromise.

The storytelling is not without its flaws. Physicist Marzio Nessi morphs into a Mr Messi, who is surely a different kind of genius. A discussion of fresh ideas in healthcare required multiple re-readings to sort out who was doing what, where, and whether these were diverse experiments across the nation. More than once I checked the index because I assumed I’d missed something. These are small things, but in a book that tries to flow so freely across so many stories, they are barnacles that produce a drag.

That said, Heffernan is generally a deft storyteller and the book’s reliance on such stories is a strength. Bad “smart thinking” books offer 2×2 matrices and jargon; good ones offer theory and evidence. Heffernan steps outside the category entirely. She wants us to engage with the particularities of people, places and the problems they faced — to empathise with them, reflect on our own lives and our own careers, and to draw our own conclusions.

Uncharted is not a book to skim in the business class lounge. Heffernan’s approach is more like a music lover trying to broaden the appreciation of a patient friend. “Here’s an example; listen to this; here’s another. Compare, contrast. Now do you see what I’m getting at?” It is messy, and occasionally frustrating, but wise and appealingly human.

UK: Amazon – Blackwell’s

US: Amazon – Powell’s (Publishes Sep 2020)

Written for and first published in the Financial Times on 19 February 2020.

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Why moonshots matter

Tim Bradshaw, head of the Russell Group of leading UK universities, has a curious tale to tell about failure. A few years ago he visited the Cambridge office of an admired Japanese company to find them fretting about the success rate of their research and development. At 70 per cent, it was far too high: the research teams had been risk-averse, pursuing easy wins at the expense of more radical and risky long-shots.

The late Marty Sklar, a Disney veteran, once told me a similar tale — if his colleagues weren’t failing at half of their endeavours, they weren’t being brave or creative enough. My boss at the World Bank 15 years ago had the same worry that too many projects were succeeding.

When the same concern arises in such wildly different contexts, we may be worrying about a common problem: a systematic preference for marginal gains over long shots. It’s not hard to see why. It is much more pleasant to experience a steady trickle of small successes than a long drought while waiting for a flood that may never come.

While marginal gains add up, they need to be refreshed by the occasional long-shot breakthrough. Major innovations such as the electric motor, the photo­voltaic cell or the mobile phone open up new territories that the marginal-gains innovators can then explore.

With this in mind, it’s hard not to sympathise with the UK Conservative party’s promise to establish “a new agency for high-risk, high-pay-off research, at arm’s length from government” — a British version of the much-admired US Defense Advanced Projects Research Agency.

Originally known as Arpa, now Darpa, it is most famous for creating Arpanet, the precursor to the internet. It also supported early research into satellite navigation and the windows-and-mouse system for operating a computer. And it helped to catalyse interest in self-driving cars. With successes like that, nobody seems to mind that Arpa’s failure rate is often said to be around 85 per cent. High-risk, high-pay-off indeed.

A collection of essays published recently by the think-tank Policy Exchange concurs that we need an Arpa for the UK. I’ve long argued for the importance of long-shots — the subtitle of one of my books is “why success always starts with failure” — so I can’t help but agree. Yet if this was easy, the UK would have an Arpa already.

At the casino it is easy to double the rewards by doubling the risk, but in the world of research, the trade-off is not so straightforward. While a low failure rate may indeed signal a lack of originality and ambition, we cannot simply decide to fail more often in the hope that originality will follow.

Arpa itself has approached this problem by hiring high-quality scientists for short stints — often two or three years — and giving them control over a programme budget to commission research from any source they wish.

Meanwhile, the Howard Hughes Medical Institute, a foundation, deliberately looks for projects with an unusual or untried approach, but a large potential pay-off. One study suggested that HHMI gets what it pays for — more failures, but larger successes, compared with other grant-makers funding researchers of a similar calibre.

Another large obstacle looms: how long will politicians find failure to be a sign of boldness and originality? Eventually, they will simply call it failure. Now that Arpa has a 62-year record, it is easy to forget that the agency was initially written off by some critics.

A new UK agency will face pressure to deliver. That sits uneasily with the desire to support risk-taking. Consider Arpa’s younger sibling, Arpa-E, created in 2009 to fund new energy projects. As of this week, the section of the Wikipedia entry on Arpa-E entitled “Accomplishments” is empty. Ouch.

The problem is more acute for a UK Arpa, because it is likely to have less funding — perhaps £200m a year. Is that enough? When Arpa’s head Charles Herzfeld heard the initial pitch for the proto-internet, in 1965, he responded, “Great idea . . . Get it going. You’ve got a million dollars more in your budget right now. Go.”

That is $10m-$30m in today’s money — depending on how one adjusts for spending power. It is hard to imagine a modern-day Herzfeld blowing a tenth of the UK-Arpa’s budget after a 20-minute meeting. We are on the Triceratops-horns of a trilemma. Be cautious, or fund lots of risky but tiny projects, or fund a few big, risky projects from a modest budget and accept that every single one may flop.

Keeping this new agency “at arm’s-length from government” is essential. Indeed, Safi Bahcall — the author of Loonshots — persuasively argues that such agencies need to be at arm’s length not just from government but from everybody. Yet somehow they must focus on real, practical, front-line problems. Not too close, not too distant. Not too many successes, but not too many failures, either. It’s quite a balancing act. Still, I’d pay for a ticket to this circus. Let’s give it a try.

 

Written for and first published in the Financial Times on 14 February 2020.

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Book of the Week 10: The Rules of Contagion by Adam Kucharski

All authors need a little bit of luck, and Kucharski has it with his suddenly-topical book, The Rules of Contagion.

I enjoyed this one a lot (or, strictly, am enjoying it a lot, since I’ve not finished but I wanted my review to be as timely as the book). Kucharski is a young epidemiologist with first-hand experience of the Zika outbreak, as well as a summer working in finance in the middle of the financial crisis, so is well-placed to write a lively book about contagion both of biological illnesses and of other things such as ideas.

The book is well written, plenty of nerdy ideas (Erdos-Renyi networks, for example) leavened both with practical examples and with nice pen-portraits of the scientists involved, such as Robert May, Hilda Hudson, Paul Erdos and Ronald Ross.

I’m learning fast and having a good time. A welcome distraction from the excitable news.

UK: Amazon – Blackwell’s

US: Amazon

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The statistics behind the spread of ideas

Everyone loves a good idea. It’s even better when the idea becomes a tangible innovation, a better mousetrap that anyone can use and every mouse should fear. The awkward truth, however, is that even in a polished form, good ideas can be slow to spread.

Anaesthetic and antiseptic offer an instructive contrast. Both were developed in the mid-1800s. Anaesthetic spread faster than a hula-hooping craze. Atul Gawande explained in the New Yorker, “within seven years, virtually every hospital in America and Britain had adopted the new discovery”. Antiseptic, in contrast, took a generation to catch on.

“The puzzle is why,” noted Dr Gawande, before conceding that it is not a puzzle at all. Anaesthetic solves an immediate problem: a patient screaming and writhing in agony. Antiseptic is a defence against an invisible killer, infection, that acts only with a delay.

Unfortunately, many innovations are more like antiseptic than anaesthetic: they solve problems that can only be seen through a statistical lens. People are slow to embrace what they cannot see. A few years ago, researchers at the OECD looking at the diffusion of global productivity gains concluded that there was a growing gap between productive companies and the laggards. The gulf was huge — typically a fivefold productivity gap per worker, even after adjusting for differences in the equipment available.

Whether the innovation is a hardier variety of seed, a safer pharmaceutical compound or a more reliable manufacturing process, the benefits will rarely be as obvious as slumbering through surgery. Such ideas often spread all too slowly.

There are other barriers to the diffusion of innovation. If people feel they can’t adapt a new idea to their own purposes, or try it out on a small scale, they will resist. One major obstacle is social: evangelists for innovation are often rather different kinds of people from their audience. Agronomists are not farmers; pharmaceutical sales representatives are not general practice doctors; inventors are different from the rest of us. We will gladly imitate our peers, although that still raises the question of who will go first. One influential early study of hybrid corn in Iowa between 1926 and 1941 found that a few farmers would experiment with the new seed in small quantities to see how things worked out. Even the early adopters took things cautiously, while others watched. Farmers would then eventually copy their neighbours.

It is tempting to shrug and conclude that this is simply a tough problem. But there is no need to despair. Late last year, the British Medical Journal published a study that caught my attention, in part because of the cross-disciplinary team of authors: Alex Walker and Ben Goldacre (epidemiologists), Felix Pretis (an economist) and Anna Powell-Smith (a data scientist) — but also because those authors were looking at the diffusion of innovation in an innovative way.

The study examined how quickly National Health Service general practice clinics in England caught up with best practice in prescribing two types of drug. In one case, the birth-control pill Cerazette came off patent in 2012, at which point patients should generally have been prescribed cheaper generic versions of the drug, desogestrel. In the other, national guidelines were changed to recommend a different antibiotic for urinary tract infections.

NHS England publishes anonymised data, every month, describing the drugs being prescribed by GPs across 8,000 clinics. If you have time, you can noodle around on OpenPrescribing.net — a platform developed by Ms Powell-Smith and Dr Goldacre — looking for patterns.

And since that sounds like hard work, the BMJ study uses a statistical tool to spot whenever a clinic seems to have changed its clinical practice, and whether they did so promptly or gradually, or suddenly but after a delay, or not at all. The patterns are clear to the naked eye once pulled out of the mass of data: here’s a clinic that swiftly and sharply switched to the cheaper generic drug; here’s a clinic that never read the email. A follow-up study performs a similar analysis for statins.

What’s remarkable about all this is how unremarkable it really is. The diffusion of innovation could once only be studied in small settings and by taking considerable pains. But this is the 21st century: the NHS has made the data available to allow us to watch a good idea spreading across the nation, or not, almost in real time.

This is, of course, an atypical situation. It is unusual to be able to collect such a large set of high-quality data, showing who has or has not embraced a new idea. And it is unusual to have such sharply defined innovations: either the doctor prescribes the new drug to patient X or she does not. Still, being able to observe leaders and laggards in the NHS is no small thing. It should be straightforward to prod the laggards — and to ask the leaders how they do it. And Dr Goldacre’s group have published their statistical tools. Hopefully, it won’t take too long for the idea of using them to spread.

 

Written for and first published in the Financial Times on 7 February 2020.

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Book of the Week 9: Loonshots by Safi Bahcall

Loonshots is a book about “how to nurture the crazy ideas that win wars, cure diseases and transform industries” – and I should admit right off the bat that I haven’t had a chance to finish it yet, despite wanting to.

The book has a lot of strengths – some really nice accounts of the development of radar during the war, the creation of Arpa, Pixar, etc. These are case studies that you might have encountered before but the stories feel crisp and lively. Well worth reading for the potted histories alone, in fact.

I wish Bahcall had been less keen to coin new labels: P-type loonshots,  S-type loonshots, the “invisible axe” and the “Moses trap”. A few are fine, but as I skimmed ahead to the chapter about Arpa (which was excellent) I was surrounded by these new terms that I didn’t understand. By the way, P-type loonshots are bold product innovations. S-type loonshots are bold strategy innovations. Not sure why we don’t call them “product loonshots” and “strategy loonshots”.

Also still chewing over the effort to tie everything to phase transition (ice melting, water freezing). Bahcall is pointing to the fact that different organisations behave in different ways: a small start-up has a different culture to a large company; a military research outfit doesn’t act like an infantry regiment. But to get innovative ideas to work, you need both, and you need to manage the transfer of ideas between small and large, or blue-sky and front-line. As a metaphor, fine; but Bahcall seemed to feel it was more than a mere metaphor. Perhaps when I’ve had a chance to think about it some more, I’ll understand.

I wouldn’t be writing this review if I didn’t like the book, I should say. Despite the frustrations, there’s so much interesting material in it that I’m going to need to try again, cover to cover this time.

UK: Blackwell’s – Amazon

US: Powell’s – Amazon

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Why we need to disagree

A few days after Christmas in 1978, United Airlines Flight 173 ran into trouble on its descent into Portland, Oregon. The landing gear should have descended smoothly and an indicator light blinked on to indicate all was secure. Instead, there was a loud bang and no light.

While the crew tried to figure out whether the landing gear was in position or not, the plane circled and circled. The engineer mentioned that fuel was running low, but didn’t manage to muster enough forcefulness to convey the urgency to the captain, who was focused on the landing gear. Finally, when the first officer said “we’re going to lose an engine, buddy”, the captain asked, “why?”

The plane crashed shortly afterwards. Ten people died. The lesson: sometimes we can’t bring ourselves to speak up, even when lives are at stake.

It might seem strange, in this politically divided age, to call for people to speak out if they see things differently. But our current political discourse doesn’t quite qualify. (Abuse is not an argument, as any Monty Python fan knows.)

Useful dissent means serious engagement with people who see the world differently — or, perhaps, the courage to puncture the consensus of one’s own tribe. It is far more common to see people seeking out like-minded groups, while politicians are happy to deliver hellfire sermons to their own choirs.

That is a shame. Within a cohesive group, the mere demonstration that disagreement is possible can have liberating effects. Charlan Nemeth, a psychologist at the University of California, Berkeley, studies dissent. (Her recent book is titled, No!: The Power of Disagreement in a World that Wants to Get Along – or in the US, In Defense of Troublemakers; at least we can reliably expect transatlantic disagreement over titles.) When she arrived at the university she found her office a little too austere, and decided to put down a rug.

“These offices are all the same for a reason,” remonstrated a colleague. She kept the rug anyway — and before long, her colleagues started putting rugs in their offices, too. Apparently, few people had liked the austere offices but nobody was willing to admit that. It took Prof Nemeth’s low-level troublemaking to shatter the illusion of consensus.

Prof Nemeth has studied disagreement during brainstorming sessions. One rule of brainstorming is not to criticise the ideas of others. When she and colleagues ran their sessions, they found that groups produced more ideas if the “do not criticise” rule was reversed, encouraging participants to “debate and even criticise each other’s ideas”.

Dissent can free us to place rugs in our offices, or express our individuality in more important ways. It can also stimulate our ideas and creativity. And — as the case of Flight 173 suggests — if we hesitate forcefully to disrupt a group conversation, that can deny others a vital piece of information.

Matthew Syed, in his book Rebel Ideas (this one also has a different title in the US; there’s something in the air…) draws the same conclusion from a disastrous attempt on Everest in 1996. Mr Syed argues that junior members of the expedition had useful pieces of information about the weather and their equipment but tended to stay silent, deferring to the team leaders.

A similar dynamic is at play in lower-stakes environments. One study, conducted by Garold Stasser and William Titus, asked undergraduates to discuss hypothetical candidates for a student society president.

The researchers gave each participant a different fact sheet; some facts were given to everyone in the discussion, but others were disclosed to only one person. People rarely spoke up about their private information, and the conversation revolved — redundantly — around what the whole group knew already rather than trying to find out what wasn’t widely known. There was an opportunity for everyone to learn from everybody else, but it proved more comfortable to focus on knowledge that they all had in common.

The truth is that disagreement is hard. We find it unpleasant to be disagreed with, and it can be painful to be a dissenter. Prof Nemeth notes that when she hired actors to play the role of dissenters in experiments studying group dynamics, the actors found it distressing to be on the receiving end of hostility. Some even asked for “combat pay”.

Even in gentler settings, we underestimate the benefit of friction. One study of problem solving (conducted by Katherine Phillips, Katie Liljenquist and Margaret Neale) simply contrasted small groups of friends with those of three friends plus a stranger. The groups with an outsider did much better at solving the problems, even though the strangers had no special expertise: their mere presence raised everyone’s game.

Nevertheless, the groups of friends enjoyed themselves more and had more confidence in their answers — confidence that was, of course, badly misplaced.

We rarely appreciate it when someone is speaking out rather than fitting in. But whether it is as trivial as a rug, or as vital as a fuel gauge in a circling aircraft, we need people who see things that we don’t. We need them to speak up. And we also need to listen when they do.

 

Written for and first published in the Financial Times on 31 January 2020.

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Book of the Week 8: Deep Thinking by Garry Kasparov

Garry Kasparov’s Deep Thinking (UK) (US) is subtitled “Where Machine Intelligence Ends and Human Creativity Begins”, although on that particular point it is not especially profound. Nevertheless I’ve found it well worth a second read.

The book has two particular strengths. First, the account of account of Kasparov’s battles with IBM’s Deep Blue, which reads like a thriller. Kasparov is clearly very sore about how IBM behaved, although he has rowed back from outright claims of cheating. What he does believe is that IBM made a big song and dance about how Deep Blue was going to advance the state of artificial intelligence – while all IBM really wanted was the PR coup of victory. Victory, it turns out, was a scientific dead end. He quotes the late computer scientist Alan Perlis: “Optimization hinders evolution”. In the case of computer chess, Perlis’s maxim describes researchers who chose pragmatic short-cuts for quick results. Deeper, riskier research was neglected.

This leads me to the second strength: it really is a wonderful history of computers in chess – although my hardback edition is from 2017 so Kasparov has nothing much to say about AlphaZero. I enjoyed it a lot, even though my chess knowledge is pretty ropey.

UK: Blackwell’s – Amazon

US: Powell’s – Amazon

 

 

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The prisoner’s dilemma at 70 – at what we get wrong about it

Once upon a time, a pianist was arrested by the secret police and accused of spying. He was carrying sheets of paper covered with a mysterious code. Despite protesting that it was merely the sheet music for Beethoven’s Moonlight sonata, the poor man was marched to the cells. A couple of hours later, a sinister interrogator walked in. “You’d better tell us everything, comrade,” he announced with a thin smile. “We have caught your friend Beethoven. He is already talking.”

This sets up the most famous problem in game theory: the prisoner’s dilemma. The interrogator explains that if one man confesses and the other does not, the talkative prisoner will go free and the other will do 25 years in a gulag. If they both remain silent, they will each spend five years in prison. If they both confess, 20 years each. The dilemma is clear enough: each would do better to confess, regardless of what the other does; yet collectively they could profit by sticking together.

The dilemma is now 70 years old — it was developed in a simple mathematical form in 1950 by mathematicians Merrill Flood and Melvin Dresher and wrapped in a story by Albert Tucker. (My own retelling owes a debt to economists Avinash Dixit and Barry Nalebuff.)

Dresher, Flood and Tucker worked at the Rand think-tank. The prisoner’s dilemma distilled the tension between selfishness and co-operation into a potent form, making it emblematic of the risk of nuclear destruction and much more besides. The dilemma received a second burst of attention in 1981, after the publication of “The Evolution of Cooperation” by political scientist Robert Axelrod and evolutionary biologist William Hamilton. Their article is not only the most cited in political science, but as popular as the next three works put together.

I hope readers will forgive my dredging up such a venerable idea, because it remains relevant, instructive, and widely misunderstood. One common misunderstanding is that the problem is one of communication: if only the pianist and Beethoven could get together and agree a strategy, they’d figure out that they should stick together. Not so. Communication doesn’t solve anything. The attraction of teaming up is obvious; so is the temptation to betray. Those who believe talking helps much should watch Golden Balls, a game show based on a modified prisoner’s dilemma. What makes the show fun to watch is the emptiness of the promises contestants make to each other.

More problematic is the mistaken belief that the prisoner’s dilemma means we are doomed to selfish self-destruction. Moral philosophers have tied themselves in knots trying to refute it, to show that it is somehow rational to collaborate in a one-shot prisoner’s dilemma. It isn’t. Fortunately, most human interaction is not a one-shot prisoner’s dilemma. The 1981 paper — and subsequent book — may have pushed the pendulum too far in an optimistic direction. Prof Axelrod ran tournaments in which computer programs competed against each other, playing the prisoner’s dilemma hundreds of times. Repeating the game allows co-operation to be enforced through the threat of punishment — something game theorists had known since the 1950s. When Prof Axelrod enshrined that idea in a simple program called “Tit for Tat”, it routinely triumphed.

Tit for Tat responds to co-operation with co-operation, and betrayal with betrayal. Whatever you do to it, it does right back. Prof Axelrod highlighted the fact that although the program was tough, it was “nice” — it tried co-operation first. And he drew broader parallels, arguing that the success of the strategy explains why soldiers in the trenches of the first world war were able to agree informal ceasefires. His inspiring message was that in the worst possible circumstances, nice guys finish first — provided they have an inner steel.

But that goes too far. A simpler explanation of “live and let live” in the trenches is that popping up to shoot at the enemy is nothing like ratting out Beethoven. It is dangerous. One needs no game theory to explain why soldiers might prefer to lie low.

Prof Axelrod also set far too much store by Tit for Tat’s “niceness”. Other strategies prosper in prisoner’s dilemma tournaments, depending on details of the rules. Among them is “Pavlov”, a strategy that tries to exploit suckers and changes tactics when it encounters a punishing response. It can be co-operative, sure — but it is hardly “nice”.

Prisoner’s dilemmas do exist. The most pressing example today is climate change. Every nation and every individual benefits if others restrain their pollution, but we all prefer not to have to restrain our own. It would be foolish to hope that Tit for Tat will save the day here — and we don’t have to. We have tools available to us: domestically, taxes and regulations; internationally, treaties and alliances. Such tools change the incentives. We could and should be using them more. The pianist and his suspected accomplice were trapped. We are not. Unlike them, we can change the game.

Written for and first published in the Financial Times on 24 January 2020.

My book “Fifty Things That Made the Modern Economy” (UK) / “Fifty Inventions That Shaped The Modern Economy” (US) is out now in paperback – feel free to order online or through your local bookshop.

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Book of the Week 7: To Engineer Is Human by Henry Petroski

Henry Petroski is a fascinatingly eclectic writer – a nerd with the soul of a poet. I relied upon his book The Pencil: A History in writing the opening chapter of the forthcoming The Next Fifty Things That Made The Modern Economy (coming in May), and turned to Success Through Failure while writing Adapt.

I was delighted to receive To Engineer Is Human as a Christmas present – one of those rare surprise presents that actually works out… It’s a wide-ranging collection of essays and musings. Topics range from the experience of being a toddler in a world of adults, through the distinctive pattern of fatigue in a “Speak & Spell”, to the catastrophic collapse of walkways in the lobby of a Kansas City hotel in 1981.

One provocative idea in Petroski’s work is the idea that engineers learn through trial and error more than one might expect. Yes, there are the laws of physics and in principle one can calculate the load-bearing strength of any structure – but in practice, when we try to do something new we will sometimes run into the unexpected.

Not every essay hits the mark – I didn’t feel moved or improved by the analysis of the Oliver Wendell Holmes poem “The Deacon’s Masterpiece” – but like a collection of poems or short stories, if you don’t enjoy one you can skip to the next. Overall I felt I was learning things from Petroski that I wouldn’t learn from anybody else.

Some overlap with the more recent book Success Through Failure, but lots to intrigue.

US: Powell’s / Amazon   UK: Blackwells / Amazon

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