Don't be beguiled by Orwell: using plain and clear language is not always a moral virtue

Ed Smith's "Left Field" column.

Orwell season has led me back to his famous essay “Politics and the English Language”, first published in 1946. It is written with enviable clarity. But is it true? Orwell argues that “the great enemy of clear language is insincerity. When there is a gap between one’s real and one’s declared aims, one turns as it were instinctively to long words.”

I suspect the opposite is now true. When politicians or corporate front men have to bridge a gap between what they are saying and what they know to be true, their preferred technique is to convey authenticity by speaking with misleading simplicity. The ubiquitous injunction “Let’s be clear”, followed by a list of five bogus bullet-points, is a much more common refuge than the Latinate diction and Byzantine sentence structure that Orwell deplored.

We live in a self-consciously plain-spoken political era. But Orwell’s advice, ironically, has not elevated the substance of debate; it has merely helped the political class to avoid the subject more skilfully. The art of spin is not (quite) supplanting truth with lies. It aspires to replace awkward complexities with catchy simplicity. Successful spin does not leave the effect of skilful persuasiveness; it creates the impression of unavoidable common sense. Hence the artifice becomes invisible – just as a truly charming person is considered nice rather than “charming”.

There is a new puritanism about the way we use words, as though someone with a broad vocabulary or the ability to sustain a complex sentence is innately untrustworthy. Out with mandarin obfuscation and donnish paradoxes, in with lists and bullet points. But one method of avoiding awkward truths has been replaced by another. The political class now speaks as it dresses: in matt navy suits and open-necked white shirts. Elaborate adjectives have suffered the same fate as flowery ties. But this is not moral progress, it is just fashion.

The same techniques have infiltrated the literary world. Popular non-fiction has evolved using quotidian prose style to gloss over logical lacunae. The whole confessional genre relies on this technique. “Gladwellian”, properly defined, is the technique of using apparently natural, authentic and conversational style to lull readers into misplaced trust: disarmed, we miss the sleights of hand in the content.

As a professional cricketer, I learned the hard way that when a team-mate said, “Look mate, I’ll be straight with you because nobody else will”, he was about to be neither straight nor my mate. The most consistently dishonest player I encountered spent much of his career beginning conversations with engaging declarations of plain-spoken honesty. His confessional, transparent manner helped him get away with years of subtle back-stabbing. When another team-mate thanked him for sitting him down and saying, “Look mate, I’ll be straight with you because nobody else will”, I felt a horror of recognition: another one duped.

If I’d studied Shakespeare more closely, I wouldn’t have been so easily fooled. Othello’s tormentor, Iago, is seen as an honest and blunt man (though he does confess to the audience that “I am not what I am”). His public image derives from his affectation, his sharpness of speech. Iago is believed because he seems to talk in simple truths.

In King Lear, Cornwall and Kent argue about the correlation between directness and authenticity. Cornwall (wrong in this instance but right in general) argues that straightforwardness often masks the most serious frauds: “These kind of knaves I know, which in this plainness harbour more craft and corrupter end than twenty silly-ducking observants that stretch their duties nicely.”

Using plain and clear language is not a moral virtue, as Orwell hoped. Things aren’t that simple. In fact, giving the impression of clarity and straightforwardness is often a strategic game. The way we speak and the way we write are both forms of dress. We can, linguistically, dress ourselves up any way we like. We can affect plainness and directness just as much as we can affect sophistication and complexity. We can try to mislead or to impress, in either mode. Or we can use either register honestly.

Philip Collins, the speechwriter and columnist, has written a book about how to persuade an audience. The Art of Speeches and Presentations is a superb primer, full of erudition and practical wisdom. Collins holds up Orwell’s essay on politics and language as a model of sound advice. But deeper, more surprising truths – contra Orwell – emerge from his arguments. He explains how using simple, everyday speech is effective but he also quotes Thomas Macaulay’s argument that “the object of oratory is not truth, but persuasion”. Following this logic, there is, unavoidably, a distinction between ends and means. Whatever the moral merits of your argument, it is always best to present it in the clearest, most memorable style. Disarming linguistic simplicity is a technique that can be learned. But how you deploy that technical mastery – the authenticity of the argument – is quite a different matter.

There is a further irony about “Politics and the English Language”. Orwell argues that the sins of obfuscation and euphemism followed inevitably from the brutalities of his political era. In the age of the atom bomb and the Gulag, politicians reached for words that hid unpalatable truths. By contrast, our era of vague political muddle and unclear dividing lines has inspired a snappy, gritty style of political language: the no-nonsense, evidence-backed, bullet-pointed road to nowhere.

Orwell’s essay is rhetorically persuasive. And yet it makes little attempt to prove its central thesis. The reader, having nodded at a series of attractive and catchy stylistic observations, is tempted to accept the central thesis. In fact, Orwell’s combination of masterly style and under-examined logic is the perfect refutation of his own argument.


An image from the 1965 adaptation of Orwell's "1984". Photograph: Getty Images

Ed Smith is a journalist and author, most recently of Luck. He is a former professional cricketer and played for both Middlesex and England.

This article first appeared in the 11 February 2013 issue of the New Statesman, Assange Alone

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How science and statistics are taking over sport

An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others.

In the mid-1990s, statistics undergraduates at Lancaster University were asked to analyse goal-scoring in a hypothetical football match. When Mark Dixon, a researcher in the department, heard about the task, he grew curious. The analysis employed was a bit simplistic, but with a few tweaks it could become a powerful tool. Along with his fellow statistician Stuart Coles, he expanded the methods, and in doing so transformed how researchers – and gamblers – think about football.

The UK has always lagged behind the US when it comes to the mathematical analysis of sport. This is partly because of a lack of publicly available match data, and partly because of the structure of popular sports. A game such as baseball, with its one-on-one contests between pitcher and batter, can be separated into distinct events. Football is far messier, with a jumble of clashes affecting the outcome. It is also relatively low-scoring, in contrast to baseball or basketball – further reducing the number of notable events. Before Dixon and Coles came along, analysts such as Charles Reep had even concluded that “chance dominates the game”, making predictions all but impossible.

Successful prediction is about locating the right degree of abstraction. Strip away too much detail and the analysis becomes unrealistic. Include too many processes and it becomes hard to pin them down without vast amounts of data. The trick is to distil reality into key components: “As simple as possible, but no simpler,” as Einstein put it.

Dixon and Coles did this by focusing on three factors – attacking and defensive ability for each team, plus the fabled “home advantage”. With ever more datasets now available, betting syndicates and sports analytics firms are developing these ideas further, even including individual players in the analysis. This requires access to a great deal of computing power. Betting teams are hiring increasing numbers of science graduates, with statisticians putting together predictive models and computer scientists developing high-speed software.

But it’s not just betters who are turning to statistics. Many of the techniques are also making their way into sports management. Baseball led the way, with quantitative Moneyball tactics taking the Oakland Athletics to the play-offs in 2002 and 2003, but other sports are adopting scientific methods, too. Premier League football teams have gradually built up analytics departments in recent years, and all now employ statisticians. After winning the 2016 Masters, the golfer Danny Willett thanked the new analytics firm 15th Club, an offshoot of the football consultancy 21st Club.

Bringing statistics into sport has many advantages. First, we can test out common folklore. How big, say, is the “home advantage”? According to Ray Stefani, a sports researcher, it depends: rugby union teams, on average, are 25 per cent more likely to win than to lose at home. In NHL ice hockey, this advantage is only 10 per cent. Then there is the notion of “momentum”, often cited by pundits. Can a few good performances give a weaker team the boost it needs to keep winning? From baseball to football, numerous studies suggest it’s unlikely.

Statistical models can also help measure player quality. Teams typically examine past results before buying players, though it is future performances that count. What if a prospective signing had just enjoyed a few lucky games, or been propped up by talented team-mates? An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others. In many sports, scoring goals is subject to a greater degree of randomness than creating shots. When the ice hockey analyst Brian King used this information to identify the players in his local NHL squad who had profited most from sheer luck, he found that these were also the players being awarded new contracts.

Sometimes it’s not clear how a specific skill should be measured. Successful defenders – whether in British or American football – don’t always make a lot of tackles. Instead, they divert attacks by being in the right position. It is difficult to quantify this. When evaluating individual performances, it can be useful to estimate how well a team would have done without a particular player, which can produce surprising results.

The season before Gareth Bale moved from Tottenham Hotspur to Real Madrid for a record £85m in 2013, the sports consultancy Onside Analysis looked at which players were more important to the team: whose absence would cause most disruption? Although Bale was the clear star, it was actually the midfielder Moussa Dembélé who had the greatest impact on results.

As more data is made available, our ability to measure players and their overall performance will improve. Statistical models cannot capture everything. Not only would complete understanding of sport be dull – it would be impossible. Analytics groups know this and often employ experts to keep their models grounded in reality.

There will never be a magic formula that covers all aspects of human behaviour and psychology. However, for the analysts helping teams punch above their weight and the scientific betting syndicates taking on the bookmakers, this is not the aim. Rather, analytics is one more way to get an edge. In sport, as in betting, the best teams don’t get it right every time. But they know how to win more often than their opponents. 

Adam Kucharski is author of The Perfect Bet: How Science and Maths are Taking the Luck Out of Gambling (Profile Books)

This article first appeared in the 28 April 2016 issue of the New Statesman, The new fascism