There has never been a better time to be a politician. Essay

There has never been a better time to be a politician.

All through cutting-edge history, the political competitors have just had a predetermined number of instruments to take the temperature of the electorate. as a rule, they have needed to depend on impulses as opposed to valuable information or insights when running for office.

But now the times have changed, numerous historical choices made by individuals are presently made by computers. Algorithms tally cast a ballot, support approve loans and advances Mastercard applications, targets residents and neighborhood for strategy investigations, select citizens for IRS reviews, allow or deny immigration visas, and many more. Nowadays, huge information can be utilized to amplify the adequacy of a political battle. Machine learning frameworks are based on factual procedures that can naturally distinguish designs in information by making algorithmic evaluations. Artificial Intelligence can be utilized to control singular voters. Political bots which are autonomous accounts on different social media platforms were customized to forcefully spread uneven political strategy that endeavors to shape open talk and confront political suppositions. The biggest example of artificial intelligence making a difference in political elections was US 2016 Presidential elections. But before we dig deep into an above-mentioned fancy word which runs on algorithms, lets first understand what algorithms are?

“An algorithm is a set of rules for getting specific output from a specific input. Each step must be so precisely defined it can be translated into computer language and executed by machine” by Donald E. Knuth.

The present term of decision for a critical thinking technique, algorithm, is normally utilized these days for the arrangement of principles a machine (and particularly a computer) pursues to accomplish a special objective. It doesn’t generally apply to computer intervened actions, be that as may. The term may as precisely be utilized of the means followed in making a pizza or comprehending a Rubik’s Cube with respect to computer fueled information analysis.

The algorithm is regularly matched with words determining the actions for which a lot of guidelines have been structured. A search algorithm, for instance, is a technique that figures out what sort of data is recovered from a huge mass of information. An encryption algorithm is a set of tenets by which data or messages are encoded with the goal that unauthorized people can’t pursue them.

Despite the fact that previously bore witness to in the mid 20th century (and, up to this point, utilized carefully as a term of arithmetic and computing), the algorithm has a shockingly profound history. It was framed from algorism “the arrangement of Arabic numerals”, a word that returns to Middle English and at last originated from the name of 9th-century Persian mathematician Muhammad ibn Mūsā al-Khwārizm, who was also a space expert and researcher in the House of Wisdom in Baghdad.

The Political affair

Social media has drastically changed the way political campaigns are run and how candidates interact with the voters. It has made the political candidates more accountable and accessible to the voters. The fact that political parties have now the ability to publish content and broadcast it to millions of people instantaneously through opinion is driven posts and analytics.

How does this work?

1. Social media posts have made interaction with voters, a little more direct. They do not have the need to use traditional methods to reach their voters, like advertising and outdoor campaigns (which use up a lot of capital).

2. Political campaign managers have started using free ads to publicize their campaign which has led to no or minimal campaign funds being used on advertising. This is essentially free advertising.

3. Micro-blogging and other social media website have become instrumental in making campaign events viral. The share and retweets help in increasing visibility and eventually the campaign gains a lot of traction. Algorithms in social media drive opinions based on the user's likes, shares and content “clicked” on. These click farms are used to make campaigns viral.

4. Political candidates use the rich voter analytics available to them and use it to tailor content that satisfies different social groups and people from different people. This helps drive the same message: “Vote for me”, but in different but effective ways.

The predictive power of social media using algorithms

With the advent of the internet and the accessibility on smartphones, microblogging has become quite popular. Social platforms like Twitter, Facebook have become communication tools for users. Users can share their thoughts individually and emotionally. They encourage surprisingly assorted and exclusive interest while quickening the arrangement of powerful efforts.

One can easily say that users write their life on social media. People share their opinions about the present ongoing trends, discuss events, debate on current events because of the freedom of expressing these social media platforms provide them with. With the advancement accessibility of these platforms in their palm, people share more and more views on sports, politics, religion and this data can be effectively used for marketing campaigns and promoting products. This data is fetched and analyzed in an appropriate way can be used to predict real-life events. Not only future, Christel, but an author also tried to predict the present using Google trends and analyzed it to helpful for retail marketing. In addition, researchers have reported that the publicly Available social media data can be used to predict flu epidemics, stock market trends, housing market trends, and politics.

Data retrieved from social media platforms need to be processed before analyses. These are some self-explanatory steps which are needed to be performed for the desired outcomes:

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1. The US Elections:

Political campaigns in the recent past have raised serious questions on the democratic nature of elections around the world. Many instances revealed that “Pioneering technologies” were utilized by political entities to their advantages, distorting the constitutionality of elections and undermining citizen’s rights. The US Elections of 2016 is an ideal example. Be it exploiting the data of millions of social media users to strategize the campaigns (Cadwalladr & Graham-Harrison, 2018) or the usage of social bots to polarize online political discussions and spread false information (Bessi & Ferrara, 2016), it had a centralized focus on digital media platforms in an unprecedented way, influencing people and changing their views. It was proof of the extent to which algorithms are governing our lives, making our decisions and following us like a shadow. Yet we hardly realize.

The US presidential elections of 2016 involved unethical and iniquitous acts of more than one manner. It was a battle of digital power and dominance armed with technology, which exploited digital labour markets (Casilli, 2016) and violated privacy policies. In the end, Trump won, but was it a righteous win? Well, he owes a lot to technology. Many facts were disclosed and yet they simply remain as facts. Revelations and disclosure of such acts force us to think whether we are really free in this world, or are we mere puppets, dominated and ruled by the powerful bearers of AI.

Social media platforms like Twitter acts as major channels for political polarization. It was recently that the platform was accused of political bias against conservatives, in India (Mehta, 2019). In a world, where one-third of the population is connected by online media (Nag, 2019) and use it as a medium for political exchange and expression, platforms like Twitter are powerful than ever. They control what we see by promoting certain ideologies and restricting others. And this has a major impact on how we think and make political decisions. But do we ever realize that we entitle these platforms to such powerful rights while we sign up for them? Most of us don’t.

Now, the crucial question is, who is going to protect our democracies and regulate these disrupting technologies? The answer lies in the future as no one is fully aware of the scope of these technologies as they evolve over time.

Brexit: how the EU Referendum was won with Data Science. YouGov’s experimental poll conducted interview samples of around 50",000 people without caring much for getting a fair demographic spread. They used step-by-step restitution and post-lamination to determine groups of voters within the population. Essentially, divide the electorate into more grainy sectors of population and loading swings based on it.

AggregateIQ, a Canadian political consultancy and technology firm, got £3.5 million for the “Leave” campaign. Step number one – to create a campaign to learn what different clusters of electorates think about different issues around the EU. They did this by giving people the chance to win an aggregate bet statistically impossible to win (a 1 in 5",000",000",000",000",000",000",000 chance). Then, the findings of research were used to build micro-targeted messages to different demographic targets of electorate. During the referendum, more than 1 billion Facebook advertisements with pro-leave messages were served. For example, those voters who were less “racist” could receive photos of Boris Johnson saying, “I’m pro-immigration, but above all, I’m pro-controlled immigration”. Other voters could receive messages like “TURKEY HAS A POPULATION OF 76 MILLION. TURKEY IS JOINING THE EU. GOOD IDEA??”. If they clicked on the relevant advert, they would then receive continuous advertisements of the same subject to keep this point of view. Most of AggregateIQ’s budget was dumped on these types of adverts just before the EU referendum with about 7 million people targeted during this period. Thus, on the 23rd of June 2016, 17",410",742 people voted to leave the EU, and 16",141",241 voted to remain.

Data Science is changing the political landscape through misuse of Facebook user data, because it can psychometrically profile the entire electorate by using a viral personality app myPersonality and cross-referencing personality types according to what people like. Since we are in the digital age, we share more data about us and create more ways of information to reach us. Modern marketing and advertising create relevant and personalised messages to reach more target segments, and politics is just another client in this market.

The “Remain” campaign failed to embrace the latest tools and technology that were available from the explosion in data science. They could target voters that the “Leave” campaign targeted and the hesitating ones. They used classic techniques of traditional pollsters and failed. It’s time for politics to step into the 21st Century. We live in the post-truth era, when arguing pros and cons in a rational debate is substituted by launching “grenades” of true or false information that resonate with the electorate in an emotional way which then requires the opposition to “put out fires”. However, campaigns need to learn from Cambridge Analytica and AggregateIQ that old-school way of politics is gone, data science has come, and the winner is the one that stays ahead in the game


Bessi, A., & Ferrara, E. (2016). Social bots distort the 2016 U.S. Presidential election online discussion. Retrieved March 31, 2019, from

Cadwalladr, C., & Graham-Harrison, E. (2018). Revealed: 50 million Facebook profiles harvested for Cambridge Analytica in major data breach. Retrieved April 27, 2019, from

Casilli, A. A. (2016). Never mind the algorithms: the role of click farms and exploited digital labour in Trump's election. Retrieved March 31, 2019, from

Mehta, I. (2019). After the US, Twitter faces wrath from India’s right wing over alleged bias. Retrieved March 31, 2019, from

Nag, O. (2019). Only One-Third Of The Global Population Is Online. Retrieved April 24, 2019, from

New A. (11 January 2019), “Brexit: The Uncivil War showed us how the EU Referendum was won with Data Science”. Retrieved from

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