How artificial intelligence conquered democracy

There has never been a better time to be a politician. But it’s an even better time to be a machine learning engineer working for a politician.

Throughout modern history, political candidates have had only a limited number of tools to take the temperature of the electorate. More often than not, they’ve had to rely on instinct rather than insight when running for office.

Now big data can be used to maximise the effectiveness of a campaign. The next level will be using artificial intelligence in election campaigns and political life.

Machine learning systems are based on statistical techniques that can automatically identify patterns in data. These systems can already predict which US congressional bills will pass by making algorithmic assessments of the text of the bill as well as other variables such as how many sponsors it has and even the time of year it is being presented to congress.

Machine intelligence is also now being carefully deployed in election campaigns to engage voters and help them be more informed about key political issues.

This of course raises ethical questions. There is evidence, for example, to suggest that AI-powered technologies were used to manipulate citizens in Donald Trump’s 2016 election campaign. Some even claim these tools were decisive in the outcome of the vote.

And it remains unclear what role AI played in campaigning ahead of the Brexit referendum in the UK.

Did you vote because of AI?

Artificial intelligence can be used to manipulate individual voters. During the 2016 US presidential election, the data science firm Cambridge Analytica rolled out an extensive advertising campaign to target persuadable voters based on their individual psychology.

This highly sophisticated micro-targeting operation relied on big data and machine learning to influence people’s emotions. Different voters received different messages based on predictions about their susceptibility to different arguments. The paranoid received ads with messages based around fear. People with a conservative predisposition received ads with arguments based on tradition and community.

This was enabled by the availability of real-time data on voters, from their behaviour on social media to their consumption patterns and relationships. Their internet footprints were being used to build unique behavioural and psychographic profiles.

The problem with this approach is not the technology itself but the fact that the campaigning is covert and…

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