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Artificial intelligence as a driver of democracy

There will be dozens of new job titles emerging in the next few years that In a world where inequality seems to be on an inexorable rise, will the proliferation of AI be the solution that closes the gap between the privileged and underprivileged? If it’s used ethically, then all the potential is there.

Even though quality of life around the world has improved by almost all metrics over the last 50 years, from literacy to life expectancy, the divide between the ‘haves’ and ‘have-nots’ tends to dominate the news headlines, and it would be wrong to pretend that there are not endemic issues which need to be addressed if as a society we want to strive for true equality.

It’s most likely a fool’s errand to try and ‘fix’ the system from the top down. But to try and make sure that everyone gets access to the quality of life most of us are already lucky enough to enjoy, there’s plenty that can be done from the bottom up.

Primary amongst these is the potential of artificial intelligence to continue improving the quality of life for the minority who still suffer through living in poverty, without access to proper healthcare, or those who struggle to access the services society can and should provide.

An inclusive revolution

Crowd of people taking pictures

AI technology is beginning to be more and more obvious in our day to day lives. It’s not just the 1 in 5 Americans who now own a smart assistant. We order food and taxis through AI-powered apps and purchase items through sites where algorithms monitor our behaviour and learn our preferences for a personalised experience. So far, so convenient. But there are deeper benefits.

On top of the access to comms, services and conveniences that we could never have had previously, unpopular manual jobs - of which there are many - can now be automated and streamlined. The displacement of humans that follows is more of an opportunity than a setback, and there will be dozens of new job titles emerging in the next few years that provide more chances for people to deliver value to an organization while challenging themselves.

Closing the gap

This tech is becoming more widespread and available, and, following market rules, cheaper. Before long it will be par for the course in areas like social services, charity campaigns, healthcare, and more.

We know the evidence that shows the introduction of automation and machine-learning leads to cost and time savings - if we pass that saved resource onto people, hopefully, they will enjoy a better level of service or just a better deal in life with greater access to all you need to live within an era of abundance. Equality will become a reality to a greater percentage of society than we have known before.

Think of the gap in healthcare services. In the US or Europe, it might be between private and state care. In other countries, there’s a lack of basic services full stop. AI will close the gap in the former, and invigorate the latter. When advanced AI analysis like IBM’s Watson is available across the board, it’s going to make less difference how much you pay for healthcare. In sub-Saharan Africa, for example, where isolated communities struggle to access doctors, AI-powered apps and the spread of mobile technology means that communities can self-diagnose and self-treat, and gain valuable healthcare information for day to day life. Kenya’s ‘KEMSA’ project is a great example of this.

Ethical dilemmas

If we’re struggling as humans to get autonomous vehicles on the road without running into potential ethical problems at every turn, then striving for ‘Democracy 2.0’ is unlikely to be without its struggles from a moral perspective.

With cars, there are stark examples. An automated car is driving along when a child runs into the road. Does it swerve to avoid the child and kill and old lady, keep going and kill the child, or brake so sharply the passenger comes flying through the windscreen? However, this sort of thinking is often quite legitimately criticised for being extremely unlikely to apply in real-world situations.

But applying machine learning to human data sets to decide which members of society get priority access to social care? That’s something which will, initially at least, be a very real challenge for us. However, having an agreed set of rules to teach AI with when it comes to these sensitive social decisions can arguably remove the element of human bias and error. It can sometimes be preferable to have sensitive decisions made dispassionately.

I believe there will be many more positive choices to make though, in the AI-powered pursuit of humanity’s updated form of democracy.

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