Machine Learning, Deep learning, and Artificial Intelligence in Politics

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“Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted, and it would give you the right thing. We’re nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we work on.” —Larry Page

When we talk about machine learning, deep learning, and Artificial Intelligence (AI), it throws an idyllic image of Russian dolls that are nested inside each other where the largest being the artificial intelligence which fits both machine learning and its subset – deep learning within. Artificial Intelligence defines the human-to-machine relationship where when a machine becomes intelligent, they can connect data points, understand requests, and draw conclusions. Let’s consider the following –

  • You are leaving for a business trip, and your intelligent device automatically gives you the weather report and other travel alerts for the place you are traveling to.
  • You are planning a surprise anniversary dinner for your spouse, and your smart bot will help you in making a reservation and even remind you to pick up the cake.

In the above examples, the machine understands what information is required and thus looks at relationships between all the variables, derives an answer and automatically communicates to you.

In simple terms, machine learning and deep learning are subfields of artificial intelligence. Today, let’s talk about how these smart technologies apart from being a part of daily life have entered the political arena as well.

When you need to make sense out of huge volumes of data, it might become difficult to decide where to begin from to look out for interesting trends so you start exploring the data and for this task, we turn to machine learning.

Machine learning enables computers to get into a self-learning mode without being explicitly programmed. In other words, it is the most basic way of using algorithms to parse data and then make a prediction about something. The model of machine learning has been there in the system for some time but its capability to relate complex algorithms automatically to the big data has gained momentum over the last couple of years, and it has made its way into politics as well.

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If you go through the modern history, most of the political parties have had a limited number of tools to monitor their electoral campaign. They have been relying more on instincts rather than insights when running their campaigns. But now more and more political campaigns are relying on big data to maximize the effectiveness of their campaign.

The statistical techniques used by machine learning systems can automatically identify the patterns in massive amounts of data. In fact, it is now watchfully deployed in electoral campaigns to engage voters and to make them aware of important political issues.

With the improvement in both visual and audio technology and an explosion of usage of various social media channels, text posts and images have become a new norm through which political parties interact with the voters. The use of neural-network techniques or deep learning gives these political parties an unparalleled ability to factually study how these texts and images can shape the public opinion.

The political images are created with an intention to persuade the voters to vote for or against any political party. The use of neural network can accomplish this task for the politicians. It provides the key to extract features from people and objects which are politically relevant.

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This neural network or better known as Deep Learning is a subset of machine learning. It is a kind of computing system that is made up of interconnected units. The information is processed by responding to external inputs, and this process requires multiple passes at the data to derive the meaning. This methodology is used to learn complex patterns in vast volumes of data. Image and speech recognition are some of the typical applications.

There seems to be a wide variety of avenues for AI’s integration into the politics. From providing sets of computer algorithms to target certain sections of voters basis their internet activity, to more advanced operative work in politics, to automating public sector, to right up to the decision making role in the government, the possibilities are limitless.

The most crucial role that AI plays in the political system is during the party campaigning. Many political parties now use these algorithms to identify specific segments of the population which can be the probable voters for them by using tailor-made advertising campaigns for them. The most common example is analyzing online behavior of Facebook users and then engaging them with ads that pick their interest.

However, the use of technology can raise ethical issues as AI can be used to manipulate the voters. Since AI uses internet footprints to build voters profiles and then sends tailored messages. Another downside could be that political parties can use AI to spread fake news on social media and play with voter’s sentiments. Political parties have been using smart bots with autonomous accounts which are programmed to insistently spread a political message which is one-sided so as to create an illusion amongst the voters. A bitter political climate is created on social media platforms such as Facebook and Twitter to highlight negative messages about a party or candidate.

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However, the problem is not technology but the covert nature of the whole political system. An ethical approach to AI can work wonders for the political system. The algorithms which are used to mislead and confuse the voters can very well be used positively to support democracy. In fact, AI can be used to make sure that their elected candidates hear people’s voices.

Experts feel that as the technology behind AI would advance further, it is likely that more and more political groups will invest their funds into it.

Conclusion

As machine learning, deep learning, and AI continue to mature and evolve with time it’s time to start experimenting as to how these technologies can help political parties to work smarter, better and faster. It can be used to gain meaningful insights from data and automate existing operations. There has been a significant leap in AI capabilities and will continue to happen further, and it will be an exciting thing to see how politics will incorporate AI into their operations and how big it can become.

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