How Brexit Was Won
Regardless of what you think of Brexit, it remains one of the few major political accomplishments of the last two decades, other leading contenders being Obamacare (though it did not work as promised), the Iraq War, and Trump's election.[1] Since decision making in all large organizations eventually devolves into politics, anyone who cares about affecting change from within an organization should study successful attempts at reform. Fortunately, one of the main people behind Brexit, Dominic Cummings, is both very smart and very talented at explaining his methods. He wrote a long essay explaining how the Brexit referendum was won. The essay is hard to excerpt, doubly so because many of the lessons to learn from Cummings require changes in thinking rather than mere changes in tactics. Below I will excerpt a few passages in the hopes that you will be intrigued enough to read the full piece.
One point Cummings hit on repeatedly was that while the OUT campaign did a lot of things right and ran a better campaign than the IN campaign, they would not have won if the OUT team had not consistently screwed up important decisions.
I suspect that in general big mistakes cause defeat much more often than excellent moves cause victory. There are some theoretical reasons to suspect this is true from recent statistical analysis of human and computer decisions in chess. Two results are particularly interesting. 1) The very best computers seem to make moves that preserve the widest possible choices in the future, just as the most effective person in politics for whom we have good sources, Bismarck, operated always on the principle of ‘keep two irons in the fire’. (We tried to mimic this by adopting a message that we thought had the highest probability of winning in the largest number of plausible branching futures, hence £350m/NHS.) 2) Even great humans are distinguishable from great computers by their propensity to make clear tactical errors occasionally amid the fog of war. This is significant enough that it wipes out the advantage of going first—i.e. it being ‘your move’ is seen as a plus but in fact it is a minus for humans because of the probability of a significant error, while for computers this effect is absent. (See Human and Computer Preferences at Chess, 2014. It would be very interesting to know if these results are supported by the recent success of Deep Mind with computer GO.)
How Educated People Fool Themselves
The conformity of the educated is in some ways a good thing-most obviously, a basic consensus about things like not killing one’s domestic opponents that is extremely unusual historically. But it has many bad effects too. There is a collective lack of imagination which makes the system very susceptible to disastrous shocks. They share a narrow set of ideas about how the world works which mistakes their own view as the only possible sensible approach. They are aways writing about how ‘shocking’ things are to them—things that never were as low probability events as they imagine. They can’t imagine something like Stalin deliberately creating a famine or deliberately murdering millions. They tell themselves that Hitler will be ‘more sensible in power’ and ‘engagement’ is the right path. Western liberals (like Clinton and many pro-euro campaigners) and conservatives (like Bush) talked of relations with Putin as if he is a normal western politician rather than an ex-KGB mafia overlord with views very far from western liberals. They tell each other ‘I can’t imagine President Trump, it just can’t happen’. Many conservatives are now telling themselves that they should not take Trump too literally but that too is a failure of imagination—his character is clear to those unblinded by gang mentality and he will govern in character.
The referendum was a great example of this. Large numbers of people better educated than average—the sort of people who work as producers at the BBC—talked about their vote like this:
‘Farage is racist, he hates gay people and made that comment about foreigners with HIV, he wants to turn the clock back and pull the drawbridge up, I’m not like that, my friends aren’t like that, I am on the other side to people like that, I am tolerant and modern, I will vote IN.’
All over the country sentiments almost identical to this were expressed in large numbers. The idea that millions of graduates voted because they ‘studied the issues’ is laughable to anybody who spent time measuring opinion honestly. Almost none of these people know more about what a Customs Unions is than a bricky in Darlington. They did not vote on the basis of thinking hard about the dynamics of EMU or about how Brussels will cope with issues like gene drives. Millions thought—there’s two gangs and I know which one I’m in. Another subset of the better educated feared the short-term economic disruption of a Leave vote would cost them money. They also did not vote on the basis of deep consideration of the issues.
The Uselessness of Political Analysts
I often meet people who are cleverer than those in politics and successful but they have deluded views about politics because they pay too much attention to political analysis. Overall, unless you are professionally involved in politics you will be better off if you stop >95% active reading of political analysis. You will miss occasional worthwhile things but the effort of sorting them is not worth it. If something is genuinely very good / unusual and you have avoided isolating yourself in an echo chamber that insulates you from opinions very different to your own then someone reliable will send it to you. Even if you are professionally involved in politics I would do roughly the same. Extreme focus on important things you can control will repay far far more than time spent reading speculation about things you can’t control.
On Swing Voters
Swing voters who decide elections—both those who swing between Conservative/Labour and those who swing between IN/OUT—do not think like this. They support much tougher policies on violent crime than most Tory MPs AND much higher taxes on the rich than Blair, Brown, and Miliband. They support much tougher anti-terrorism laws than most Tory MPs AND they support much tougher action on white collar criminals and executive pay than Blair, Brown, and Miliband.
One of the key delusions that ‘the centre ground’ caused in SW1 concerned immigration. Most people convinced themselves that ‘swing voters’ must have a ‘moderate’ and ‘centre ground’ view between Farage and Corbyn. Wrong. About 80% of the country including almost all swing voters agreed with UKIP that immigration was out of control and something like an Australian points system was a good idea. This was true across party lines.
This was brought home to me very starkly one day. I was conducting focus groups of Conservative voters. I talked with them about immigration for 20 minutes (all focus groups now start with immigration and tend to revert to it within two minutes unless you stop them). We then moved onto the economy. After two minutes of listening I was puzzled and said—who did you vote for? Labour they all said. An admin error by the company meant that I had been talking to core Labour voters, not core Tory voters. On the subject of immigration, these working class / lower middle class people were practically indistinguishable from all the Tories and UKIP people I had been talking to.
Where Are There Real Experts?
This one is not from the main article, but from a link in the article to one of Cummings' old blog posts.[2]
Physics, mathematics, and computer science are domains in which there are real experts, unlike macro-economic forecasting which satisfies neither of the necessary conditions—1) enough structure in the information to enable good predictions, 2) conditions for good fast feedback and learning. Physicists and mathematicians regularly invade other fields but other fields do not invade theirs so we can see which fields are hardest for very talented people. It is no surprise that they can successfully invade politics and devise things that rout those who wrongly think they know what they are doing.