Rigging Votes Is so 20th Century: Big Data Will Make Referendum Rigging Unnecessary
Distrust between people and government has reached a level where any vote above the level of a Parish Council attracts accusations of rigging and interference. Russia, the CIA and MI5 have been accused of interfering in the 2014 Referendum. Similar accusations were made about the EU referendum, the 2015 General Election, the EU referendum and the US Presidential election.
Britain’s voting process needs overhauling but there maybe no future need to rig votes. Two academics used Twitter tweets to predict Donald Trump’s victory in the US election and others have used data, including Facebook likes, which, despite Facebook hiding them from the public, can be obtained by publishing “fun” quizzes and psychological tests to profile everyone in the USA. This psychological profiling, once the province of experts, now automated, lets campaigners target messages to individuals and steer canvassers away from homes where their message will be resisted.
These techniques could be used negatively or positively. Ethical, Technical and legal restriction on their use needs to be imposed if, in a representative democracy, power is not to become the reward for having the largest budget. This is especially important for small groups such as Scotland’s Independence movement facing adversaries with effectively infinite funding.
Some of the new methods are outlined below and the implications for a second Independence Referendum and the democratic process in general are discussed
Predicting a Referendum Vote
The US Presidential election is, in essence, a referendum every four years deciding between Democrat and Republican visions. Traditional polling methods have proven unreliable, despite polling companies’ efforts to learn from their mistakes and social media analysis looks like partially displacing polls as predictors of voting behaviour.
In the 21st Century new sophisticated ways to inform campaigners which demographics to ignore and where and how to focus their efforts have been developed. The new methods assume behaviour indicates personality below the mask we put on every day to survive socially, and when the current behaviour of large groups of people, for example on Social Media, is analysed their future behaviour, for example how they will vote, can be predicted with a high level of confidence. It ilso turns out that individuals can be accurately profiled and their behaviour predicted with a high level of confidence.
Tom Jackson and Martin Sykora ignored how Twitter users said they would vote but analysed the emotions in election related tweets, which they identified using the hashtags associated with each party. Their hypothesis was that the more tweets representing an extreme emotion regarding a candidate, the fewer votes they would get. They defined a measure called “Choppiness” representing volatility in attitudes to a candidate. This seems to be a measure of volatility in terms of dips and spikes in the emotions revealed within the tweets. The less volatile, the less choppy the profile of emotions against time, the more likely the candidate was to win.
The tool they developed was inspired by a challenge to try and call the Scottish Independence Referendum correctly, but was first used in the 2015 General Election where it predicted the narrow Tory win. Their failure to predict the EU Referendum result was attributed to the fact that the over 65’s who rarely tweet, were biased towards Brexit.
Their model works best when emotions are involved in a personality driven campaign. Unlike polls, which are a snapshot in time, their model provides a longitudinal profile that can show trends and, used correctly, can allow candidates to trim their message in the light of their and their opponents’ successes and mistakes. Over time a user’s real feeling become apparent, perhaps unknown to themselves. Polls then become alternative methods of validating and verifying the model’s predictions.
A second Scottish Independence Referendum will clearly engage strong emotions on either side, though again non-tweeting by over 65s, may make the model’s predictions unreliable, though augmenting the data with letters to the papers on Independence and comments made on phone in programs may offset this. As with the 2014 Referendum the over 65s need to be courted no matter what the Twitter analysis says and its predictions, if this tool were to be used must be treated with caution.
Profiling the People
Tweet analysis works with masses of people in emotionally charged personality driven campaigns. Facebook likes can accurately allow an individual to be profiled accurately. Tweets can tell you what people are really likely to do, but a recent development in data driven psychology, a field known as psychometrics, allows campaigners to target the people who’s votes they need. To explain this needs a short high level view of the Five Factor theory of personality.
The Five Factor theory assumes everyone is a unique combination of five basic traits the strength of which can be measured by psychological questionnaires. It is then possible to assess the subject and guess how they will behave under different circumstances. The breakthrough in using this method was to eliminate the complex questionnaires and structured interviews previously used and replace them with actual behaviours, specifically Facebook likes. The researchers managed to get thousands of people to fill in these questionnaires voluntarily by means of a Facebook app. They then correlated this data with aspects of each person’s Facebook profile. This was done in an ethical fashion and allowed combining many weak data points to make strong predictions. On average, by 2012, 68 Facebook likes allowed prediction of someone’s skin colour with 95% accuracy and sexual orientation with 88% accuracy. After much work refining the models the researcher could evaluate a person better after ten likes than could their workmates, better after seventy likes than their friends, better after 150 likes than their parents could and after 300 likes better than their partner could. More likes could provide a person with more information than they know about themselves.
Soon after these results were published Facebook made likes private by default.
It is also possible now to search for specific profiles. And manipulate them. Or, a government or just a rogue agent could find the profiles of potential dissenters. A criminal organisation could search for gullible people to act as mules or rich people who might be susceptible to blackmail or a Nigerian Fee Scam.
And this technique was used in the Brexit Referendum and in the US Presidential Election. The messages put out were data driven. Using a vastly wider range of data than Facebook likes a model was created that could profile the personality of every individual in the USA. In principle this would mean that everyone in the USA could receive a campaign message targeted to them personally.
The full details of how this helped Trump win the election are given below  but is not hard to see how the same techniques could, and probably will, be used in a second independence referendum. The Independence movement needs to find funding to use these techniques, bearing in mind that the company Trump used may refuse to do business with pro-Independence groups even if they have the money so the tools temselves may need recreating in short order.
Psychometrics can be used for good or ill. It can be used to identify potential serial killers or earmark potential dissidents for “accidents”. It can be used to manipulate voters or for public education delivering messages that motivate beneficial changes in lifestyle. How it is used is a matter for public policy, not a few sociopaths and psychopaths in positions of power. It would be surprising if dictatorial governments were not looking to use these techniques to control the population and the dangers go well beyond referenda and elections, especially if they are combined with AI to automate the process of manipulating the people.
A government that is unhappy with the people no longer needs to choose a new people and Big Brother does not need security cameras in each home because the people will happily reveal their actions and intent. Room 101 in the Ministry of Love can be replaced by a rack of servers.
This is not the sort of world most people would want.