Tim Harford The Undercover Economist

Articles published in December, 2017

Help with your New Year’s Resolutions is at hand!

If your resolution is to get more done, I recommend Cal Newport’s remarkable book Deep Work. (US) (UK) Newport argues that success in the world of work is dependent on the amount of time we can devote to serious, deep thinking.

An observation that hit home for me is that for many of us, the productivity-sink isn’t YouTube or Snapchat, but serious stuff like emails and meetings. Email is a severe temptation for me: swift, decisive email etiquette feels professional – but all too often it’s just an excuse for avoiding the real work.

There’s also David Allen’s Getting Things Done. (US) (UK) The central ideas of GTD are: take vague incoming issues (a phone message, an email, a meeting, an idea that pops into your head) and turn then into some specific next action, then write the next action down somewhere where you’re confident you’ll see it when you need it. This stops your subconscious constantly churning over the issue.

That makes GTD sound simple and in many ways it is. But in the messy reality of modern work it’s often easier to appreciate the principle than to make it work in practice. I don’t follow every piece of David Allen’s advice but I follow a lot, because it’s smart, practical and useful stuff.

In a recent podcast, David Allen’s own New Year advice: don’t get carried away making resolutions, but think about your projects in the year just gone and the year to come. Also: tidy something up. (Your shed; your desk; your glove-compartment.) Not only is the tidying satisfying but it will spark all sorts of intriguing thoughts.

 

Now, if your resolution is to try new things, may I suggest Robert Twigger’s wonderful little book Micromastery. (US) (UK) Twigger – among other things an explorer, prize-winning poet, and Aikido master – makes the case for mastering many deep-but-narrow skills. Learn how to do an Eskimo roll, or a racing turn, or how to draw a smooth circle by hand. Don’t aim to become a brilliant cook; start instead by mastering the omelette. A really fun book – and a wise idea explained well.

 

And if you fancy dipping into some behavioural economics to help you master life’s challenges, Cass Sunstein and Reid Hastie’s Wiser (UK) (US) is the best book I know about group decision-making and how to overcoming polarisation and groupthink, while Think Small (UK) (US) by Halpern’s colleagues Owain Service and Rory Gallagher, or How To Have A Good Day (UK) (US) by Caroline Webb, are both practical applications of behavioural science to lose weight, acquire better habits, or deal productively with awful meetings.

 

My own resolution for 2018 is: One Thing At A Time.

Happy New Year!

 

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31st of December, 2017MarginaliaComments off

Could we run the economy with an app?

The control room is hexagonal, containing a circle of white fibreglass swivel-chairs with red-brown cushions and inbuilt push-button panels. The room is reminiscent of Star Trek, but it is no film set. Project Cybersyn was an attempt in the early 1970s to algorithmically manage the Chilean economy in accordance with democratic socialist principles under President Salvador Allende.
The idea was not entirely a new one. Between the wars, economists debated the “socialist calculation” problem: could a benevolent central planner somehow coordinate all the production and consumption necessary to run a modern economy, bypassing the greed and waste of the market with a more rational system?
The answer was not obvious to economists – at least, not then. The uncompromising Ludwig von Mises argued that it was logically impossible, others that it was merely impractical. But Oskar Lange argued that it could be done: if an economy could be described as a series of simultaneous equations for supply and demand, then the central planner could solve those equations, if only by trial and error.
This proved easier said than done. Nobel laureate Leonid Kantorovich spent six years gathering the data and performing the calculations necessary to optimise Soviet steel production in the 1960s, far too slow to be useful in an ever-changing economy.
Computers promised more. In an essay published after his death in 1965, Lange wrote, “Let us put the simultaneous equations on an electronic computer and we shall obtain the solution in less than a second. The market process… appears old-fashioned.”
That was typical of the awe with which we continue to view these silicon brains. But it was still premature: the computers of five decades ago weren’t fast enough. One credible estimate is that the Soviet Union produced 12 million types of product at its zenith, a mathematical knot that would have taken decades for a vintage computer to unpick. A modern economy produces perhaps 10 billion.
Chile’s Project Cybersyn never had much chance to prove its worth: like Allende himself, it died when the murderous Augusto Pinochet seized power in Chile in 1973.
It was probably doomed from the start. As described in Eden Medina’s book Cybernetic Revolutionaries (UK) (US), the sleek control room masked the fact that Allende’s government only owned four computers. One of them was a Burroughs 3500, which by coincidence is a type of machine that my own father used to install, keeping himself trim by lugging around hard drives the size of tumble-dryers. It was still too soon to try to replace the marketplace with a computer network.
But the project’s ambitions no longer seem quite so unfeasible. We shouldn’t underestimate the task: Chile’s GDP in 1970 was about $50bn – perhaps $300bn at current prices. Even now, Amazon’s revenue, $135bn in 2016, is less than that.
But the power of computers is growing far more quickly than economic output. Could we build an app to run an economy, to not only replace Steve Mnuchin and Janet Yellen, Jeff Bezos and Tim Cook, but to oversee the fine details of production and consumption everywhere, eliminating waste, recessions, and inequality?
The idea has resurfaced in the writings of two Chinese economists, Binbin Wang and Xiaoyan Li. Wang and Li argue that modern computers and cheap sensors make it possible to optimise production in real time, personalised to the needs of citizens.
In some ways this has already happened. Advertisements on Google and Facebook are handled by vast algorithmic markets. If you work for Uber or Deliveroo, your boss is an algorithm. But firms have always been islands of planning in a sea of market forces; an economy in which the government controls all the platforms is something quite different.
One enduring obstacle is tacit knowledge. A textbook economy of supply and demand curves is, in principle, the kind of system that can be understood mathematically. But as Friedrich Hayek argued in 1945 there is a great deal going on in any economy that cannot be counted or even described.
Decisions to produce, to consume, and to take a risk trying to create something new, are all taken with the knowledge of “particular circumstances of time and place”. Wang and Li believe that big data make this once-tacit knowledge explicit; I am not convinced.
Then there is the issue of power. Facebook and Google already have too much. What would Stalin have done with such information? Or Pinochet? China is already using the data exhaust collected by Alibaba and TenCent to exert social control.
Hayek himself twice visited Pinochet’s Chile without speaking out about the regime’s abuses; that is indefensible.
But Hayek was right about the power of market prices to coordinate a complex economy steeped in tacit knowledge. Market forces remain a more powerful computer than anything made of silicon. We can shape its inputs and outputs with taxes that penalise pollution, redistribute income, or encourage social goods. But replacing the market with state-run algorithms is an idea that should stay in the realms of science fiction.
Written for and first published in the Financial Times on 1 Dec 2017.

My new book is “Fifty Inventions That Shaped The Modern Economy”. Grab yourself a copy in the US or in the UK (slightly different title) or through your local bookshop.

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Economicky words are just plain icky

Why can’t economists just speak plainly and clearly? The dismal science has had an image problem for a long time — long enough for most people to forget that the “dismal science” insult was hurled by the despicably eloquent racist Thomas Carlyle, in an argument over whether black plantation workers should be paid for their work or motivated with the “beneficent whip”.

If you’re arguing with an apologist for racism and he has better lines than you, you’re doing something wrong. True in 1849, true today.

Yet the problem seems to have intensified in the past few years; gone are the glory days of Freakonomics, when every economist seemed an investigator with the cachet of Sherlock Holmes. Now we economists are painted as jargon-spouting spreadsheet jockeys, malevolent string-pulling ideologues, or worst of all, “experts”. What went wrong and what are we going to do about it?

Language is part of our problem. Even in a medium that demands brevity and clarity — Twitter — we seem to be drawn to polysyllabic obfuscations like wasps to jam. Marina Della Giusta and colleagues at the University of Reading recently conducted a linguistic analysis of the tweets of the top 25 academic economists and the top 25 scientists on Twitter. (The top 3 economists: Paul Krugman, Joseph Stiglitz and Erik Brynjolfsson; the top 3 scientists: Neil deGrasse Tyson, Brian Cox, and Richard Dawkins.)

Ms Della Giusta and her colleagues found that the economists tweeted less and had fewer Twitter conversations with strangers. I sympathise, but nevertheless the scientists managed it and the economists did not. The economists also used less accessible language with more complex words and more abbreviations. Both their language and their behaviour was less chatty.

This is true in more formal settings, too. Last year on Bank Underground, a blog for Bank of England staff, analyst Jonathan Fullwood compared the bank’s reports to the writings of Dr Seuss. Long words, long sentences or long paragraphs make for difficult prose. The Cat In The Hat stands at one end of the scale; bank reports at the other.

The World Bank is another culprit: this summer its chief economist Paul Romer made few friends when he berated his colleagues over their feel-good bureaucratese in which projects “are emerging” while “players” are “partnering”, all the while advising “corporate governance and competition policies and reform and privatise state-owned enterprises and labour market/social protection reform”. It is surprisingly easy to write like this when you don’t know what you think, or cannot agree, or dare not say. The result occupies the overlap on a Venn diagram between unobjectionable and incomprehensible.

According to Stanford’s Literary Lab, World Bank reports were not always like this: they once described specific facts (“Congo’s present transport system is geared mainly to the export trade”) and what the World Bank had done to improve them.

We should do better, whether writing a tweet or a report. But there is a reason that this stuff is hard: politics. In most spheres of life people are happy to trust doctors, engineers and scientists to get on with whatever it is they do. Politics changes that: when scientists must communicate ideas about climate change, vaccines, or genetic engineering, they suddenly find themselves dragged into political fights for which they have neither the stomach nor weapons. Scientific literacy is no cure: on contentious topics such as climate change, political polarisation actually increases with education.

Economists, of course, cannot boast the same regard as doctors, engineers and scientists — but they are on contested territory more often. Economics discusses public spending, inequality, regulation, taxes and other topics in the no-man’s-land of a political war. No wonder we hesitate to engage on Twitter; no wonder we write reports that try to please everyone by saying nothing much. We then seem evasive and tedious, so nobody trusts us. But when we set out a position clearly and plainly, we risk being dragged into poisonous squabbles — something that has happened repeatedly during and since the Brexit referendum.

There are no easy answers — although emerging evidence from political scientist Dan Kahan’s research group at Yale University suggests that we might do well by trying to engage people’s sense of curiosity. It is not enough to write with clarity; the great science communicators, from Carl Sagan to David Attenborough, inspire a sense of wonder. If we use a surprising fact as an ambush, that will provoke a defensive response; far better to present an intriguing puzzle. But if we cannot inspire awe, we should at least write clearly — a habit that helps us think clearly, too.

Simplicity alone, of course, is not enough. “We’re going to build a big, beautiful wall and Mexico is going to pay for it,” has the same simple tone as Dr Seuss, although it lacks his compassion. Does it reflect clear, trustworthy thinking? I do not think so, Sam-I-Am.

Written for and first published in the Financial Times on 24 November 2017.

My new book is “Fifty Inventions That Shaped The Modern Economy”. Grab yourself a copy in the US or in the UK (slightly different title) or through your local bookshop.

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Why the robot boost is yet to arrive

To adapt a 30-year-old quip from the great economist Robert Solow: you can see the robots everywhere except in the productivity statistics. This fact has been puzzling me for a few years now. Productivity growth is disappointing — especially but not only in the UK — and it has been for years. Unemployment is near record lows, and employment is high. All this is the opposite of what one would expect if the robot job apocalypse was upon us.

Yet there is no denying the remarkable advances in various branches of artificial intelligence. The most talked-about example is the self-driving car. This technology has come a long way in a short time, which is more than one can say for the original participants in the 2004 Darpa Grand Challenge, a race sponsored by the US military. With large cash prizes for the first autonomous vehicle to complete a 150-mile course in the Mojave desert, the best effort foundered after just seven miles. The contest became a punchline. Just 13 years later, nobody is laughing about autonomous vehicles.

Then there are deep-learning technologies such as AlphaGo Zero, which took just 72 hours to teach itself to become seemingly invincible at the formidable board game, Go. Alexa, Cortana, Google Assistant and Siri have made voice recognition an everyday miracle. Strides are being made in image recognition, medical diagnosis and translation. There are behind-the-scenes triumphs: deep learning is optimising power-hungry cooling in server farms.

All of this makes the puzzle of high employment and low productivity even more puzzling. Yet there are several ways to resolve it. A simple explanation is that the robot talk is all hype. Computer scientists have been over-optimistic before. Nobel laureate Herbert Simon predicted in 1957 that a computer would beat the world chess champion within 10 years; it took 40. In 1970 Marvin Minsky predicted that computers would have human-like general intelligence “within three to eight years”, a prediction even more inaccurate than Mr Simon’s.

A more encouraging story is that we are understating productivity, for example, by undervaluing the output of services in general and the digital economy in particular, much of which is free and therefore invisible to normal measures of economic output.

A third possibility is that — to borrow an idea from the writer William Gibson — the future has already arrived, but it is unevenly distributed. Perhaps the zero-sum scramble to dominate winner-takes-all markets is simply squandering most of the potential gains.

To tease apart these accounts, a research paper by a team including both sides: Erik Brynjolfsson, an economist well known for his writings on “the new machine age”, and Chad Syverson, one of the leading experts on economic productivity.

The researchers argue that the productivity slowdown is real. It may feel plausible to suggest our data simply are not good enough to recognise that productivity is growing strongly, but the story seems off in a number of ways — most obviously that the productivity shortfall is just too large to be a statistical illusion. Something similar can be said for the zero-sum fight for corporate dominance: it may well be happening, but is it really so wasteful that huge productivity gains simply evaporate?

How, then, to resolve the puzzle? In the simplest way possible: to say, “just wait”. There is no contradiction between disappointing productivity growth now and spectacular productivity growth in the near future.

This is true in the narrow statistical sense that productivity growth tends to bounce around: a bad decade may be followed by another bad decade, or by a good one, and today’s productivity growth tells us little about tomorrow’s.

But it is also true that there tends to be a delay between a technical breakthrough and a productivity surge. The most famous case in point is the electric motor, which seemed poised to transform American manufacturing in the 1890s, but did not realise that potential until the 1920s. To take advantage of the new technology, factory owners had to turn their organisations upside down, with new architecture, processes and training. Prof Brynjolfsson’s early research in the 1990s found companies saw little benefit from investing in computers unless they also reorganised.

If the benefits of today’s new ideas are real but delayed, that may also explain the productivity slowdown itself. Consider the self-driving car: right now it is a research expense, all cost and no benefit. Later, it will start to displace traditional cars, the traditional car industry, and many related businesses from parking garages to automotive repair. Finally, perhaps decades after a self-driving car becomes feasible, the full benefits are likely to be apparent. One does not simply invent a new machine: economic progress requires much more than that.

Perhaps, then, this is a brief lull before an explosion of new technology that will radically reshape the world around us. Or perhaps we are due for another decade or two of disappointment. Either scenario seems possible — and both of them promise an uncomfortable ride.

 
Written for and first published in the Financial Times on 17 November 2017.

My new book is “Fifty Inventions That Shaped The Modern Economy”. Grab yourself a copy in the US or in the UK (slightly different title) or through your local bookshop.

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The dangers of dark nudging

“If you want people to do the right thing, make it easy.”

That is the simplest possible summary of Nudge (UK) (US) by Cass Sunstein and Richard Thaler. We are all fallible creatures, and so benevolent policymakers need to make sure that the path of least resistance goes to a happy destination. It is a simple but important idea, and deservedly influential: Mr Sunstein became a senior adviser to President Obama, while Mr Thaler is this year’s winner of the Nobel memorial prize in economics.

Policy wonks have nudged people to sign up for organ donation, to increase their pension contributions — and even insulate their homes by coupling home insulation with an attic-decluttering service. All we have to do is make it easy for people to do the right thing.

But what if you want people to do the wrong thing? The answer: make that easy; or make the right thing difficult. Messrs Thaler and Sunstein are well aware of the risk of malign nudges, and have been searching for the right word to describe them. Mr Thaler likes “sludge” — obfuscatory language or procedures that accidentally or deliberately encourage inertia. Voter ID laws, he says, are a good example of sludge, calculated to softly disenfranchise. Meanwhile Mr Sunstein has written an entire book about the “ethics of influence” (UK) (US).

And as we are starting to realise, Vladimir Putin is well aware of the opportunity that behavioural science presents, too. Rumours circulate that the Russian authorities are keen recruiters of young psychologists and behavioural economists; I have no proof of that, but it seems like a reasonable thing for the Russian government to do. I am willing to bet that not all of them are working on attic-decluttering.

According to Richard Burr, chair of the US Senate intelligence committee, Russian troll accounts on Facebook managed to organise both a protest and a counter-protest in Houston, in May 2016. Americans are perfectly willing to face off against each other on the streets, but if you want it to happen more often, make it easy.

A number of other memes, political advertisements and provocateur accounts — both left- and rightwing — have since been identified as of Russian origin. Social media networks have unwittingly sold them air time; news sites have cited them; people have shared them, or spent effort refuting them. Nudge isn’t the word for this, but neither is sludge. What about “grudge”?

The Russians are not alone in using grudge theory to manipulate public opinion. Three social scientists — Gary King, Jennifer Pan and Margaret Roberts — recently managed to infiltrate networks of shills in China, who are paid to post helpful messages on Chinese social media. (Their nickname is the “50 cent army”.) Unlike the Russian trolls, their aim has been to avoid engaging “in debate or argument of any kind . . . they seem to avoid controversial issues entirely”. The tactic is, rather, to keep changing the subject, especially at politically sensitive moments, by talking about the weather, sports — anything. If you want potential protesters to make cheery small talk instead, make it easy.

Just as noble tools can be turned to wicked ends, so shady techniques can be used to do the work of the angels. For example, why not disrupt online markets for illegal drugs by leaving bad reviews for vendors? Research by social scientists Scott Duxbury and Dana Haynie suggests that because people rely on user reviews on illicit markets, law enforcement officers could attack those markets by faking negative reviews, thus undermining trust.

The parallel with Mr Putin is alarmingly clear: it is possible to attack democracy and rational discourse by creating an information ecosystem where everyone yells at everyone else and nobody believes anything.

But we should not give too much credit to Mr Putin. He did not create the information ecosystem of the western world; we did. The Russians just gave us a push, and probably not a very big push at that. Perhaps I should say they gave us a nudge.

Social media do seem vulnerable to dark nudges from foreign powers. But more worrying is our vulnerability to smears, skews and superficiality without any outside intervention at all. Messrs Sunstein and Thaler ask policymakers to make it easy to do the right thing; what have we made it easy to do?

It is easy to find a like-minded tribe. It is easy to share, retweet or “like” something we have not even read. It is easy to repeat false claims. It is easy to get angry or personal.

It’s less easy to distinguish truth from lies, to clear time and attention to read something deep, and to reward an important article with something more than a digital thumbs up. But then, none of this is fundamental to the business model of many media companies — or of the social media networks that spread the news.

Nudge, sludge or grudge, we can change this. And we should start by asking ourselves whether when it comes to news, information and debate, we have made it difficult to do the right thing — and all too easy to stray.

 

 
Written for and first published in the Financial Times on 10 November 2017.

My new book is “Fifty Inventions That Shaped The Modern Economy”. Grab yourself a copy in the US or in the UK (slightly different title) or through your local bookshop.

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Curious books

I’ve written recently about how much I’ve been enjoying Soonish (UK) (US) by Kelly and Zach Weinersmith, a highly amusing exploration of the latest technologies from satellite launch vehicles to 3D printed houses to gene therapy to self-organising robot swarms.

But what else is out there to celebrate the curious?

I recommend Steven Johnson’s Wonderland: How Play Made The Modern World (UK) (US) – a history of technology and economics with a difference. Johnson covers music, fashion, sports and much else with a lovely light touch.

Caspar Henderson’s new book is A New Map Of Wonders (UK) (US– it’s an exploration of art, science, and the way we perceive the world around us. The book itself is a kind of cabinet of wonders, packed with surprises and delightful digressions.

Puzzle fans will have their minds blown – if you’ve not already encountered it – by Raymond Smullyan’s What Is The Name of This Book? (UK) (USBegins with some silly puzzles, moves to variants of the one-always-tells-the-truth, one-always-lies puzzle, and before you know it you’re in the middle of Godel’s incompleteness theorem.

Richard Feynman was often billed as a “curious character”, although I prefer his lectures to his autobiographical work. Try the astonishing QED (UK) (US). I remember trying to explain this one in the pub to my friends, aged 18.

Claude Shannon’s endless desire to play with things and ideas is explored in a solid new biography, A Mind At Play (UK) (USby Soni and Goodman.

Next on my list: Philip Ball’s Curiosity (UK) (USand Walter Isaacson’s Da Vinci (UK) (US), which has been getting good write-ups.

My UK publishers have a competition going on Twitter to win all seven of my books. Or you can purchase any of them here.

 

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4th of December, 2017MarginaliaComments off

A way to poke Facebook off its uncontested perch

We need to talk about Facebook. Google (or Alphabet, if you prefer) is more ubiquitous; Apple makes more money; Amazon is a more obvious threat to the bricks-and-mortar economy; yet there is something uniquely troubling about the social media leviathan.

One concern is Facebook’s unwholesome contribution to our diet of information. Because what we see in Facebook is a function of what our friends share, the site echoes our prejudices. This effect is accentuated — at least modestly — by Facebook’s own algorithms, which have learnt to show us more of what we like to keep our eyeballs on the site.

Then there is accuracy. Whether what we are shown is true or false does not much matter for Facebook’s business model, unless we start to show more interest in not being lied to. For now, fake news entrepreneurs have realised that it is far more profitable to invent eye-catching fables than to research and confirm the everyday truth.

We are also beginning to realise that Facebook is the perfect vector for carefully-targeted advertisements containing dark political smears. A false claim in a TV spot or the side of a campaign bus can be challenged; a false claim carefully targeted to a few thousand voters in a swing state may go unchallenged and, for that matter, unnoticed except by the intended few.

These problems are sometimes exaggerated, and are not Facebook’s alone: Twitter is politically polarised; Google also shows targeted ads; and few Facebook news feeds are as relentlessly blinkered as the pages of a British tabloid newspaper. But Facebook bundles them into a uniquely powerful package.

And the inconvenient fact is that Facebook seems to make us miserable. We log on like joyless addicts, two billion of us each month. I doubt that we truly value Facebook. But we use it anyway. Writing in the London Review of Books, John Lanchester cites numerous studies that suggest Facebook use goes hand in hand with envy and sadness, and quite plausibly causes them. It is also a notorious time-sink and source of distraction.

None of this is good, unless you are Facebook. But behind all these injuries is a final insult: there is no serious alternative. Buyers of Microsoft’s Office and Apple’s iPhone could choose something else. Even dominant services such as Google’s search or Amazon’s store could in principle be challenged. It would be no easy thing to build a better rival, but anyone who did would be just a click away.

In contrast, making a superior social network app is not enough to unseat Facebook: the main appeal of the site is that everyone already uses it. A rival social network would need to somehow attract groups of users en masse, an extremely difficult prospect. Two of the companies that were managing it — WhatsApp and Instagram — were bought by Facebook. It is hard to understand why regulators thought these mergers were benign.

The lack of competition may explain why Facebook retains its grip on our attention despite being clunky and pernicious; a company that faces no serious competition can afford to stop worrying about keeping its users happy. It is easy to imagine a better social network than Facebook: more privacy, a slicker interface, and less fake news. It is not so easy to see how such a rival could tempt entire social groups to migrate together.

Could regulators change this? Perhaps. They could certainly have been more aggressive in scrutinising mergers. But traditional measures such as price regulation seem less relevant to what is, after all, a free service.  Instead, we should ask ourselves if we can find a way to re-introduce serious competition in social networking.

Luigi Zingales and Guy Rolnik of the University of Chicago have proposed an intriguing idea. They build on the concept of “number portability”, the principle that you own your own phone number, and you can take your number with you to a different phone provider. The idea has promise in retail banking.

Zingales and Rolnik suggest an analogy: social graph portability. The idea is that I could take my Facebook contacts with me to another service — call it “ZingBook”. I could read their Facebook posts on ZingBook and they could see my ZingBook posts over on Facebook.  I can send emails from any program or service provider to any other, so why not guarantee interconnection between social networks? I would get whatever it was I liked about ZingBook while maintaining contact with my own social network back on Facebook.

In practice, the Zingales/Rolnik idea faces serious stumbling blocks — making the technology work, preventing cheating, and navigating permissions. If a friend decides to move over to, say, NaziBook, will he still receive my Facebook content? Will I even know where my words are now being viewed?  But the idea of social graph portability squarely addresses one of the big issues of 21st-century economic policy. The new tech titans need serious competition. For a social network, serious competition needs new rules to enable it.
Written for and first published in the Financial Times on 3 November 2017.

My new book is “Fifty Inventions That Shaped The Modern Economy”. Grab yourself a copy in the US or in the UK (slightly different title) or through your local bookshop.

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