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AI and the new economy

A topic that has come up quite recently in public discussion is the changes that Artificial Intelligence (AI) is bringing to the global economy. Increased automation is overtaking jobs and this trend is only going to go up. An interesting article on the Economist already discussed about this, while BBC has a test to see whether your job will be automated in the future or not.

The economy is used to disruptive cycles of creative destruction where some jobs become obsolete and new ones are created. What is different, however, this time, is that some of the jobs that are becoming obsolete are while collar jobs, such as jobs in law, finance or medicine.

IBM’s Watson can now be used in medicine in order to crawl through the vast medical literature. Similarly, trading is being overtaken by algorithms.

It’s not clear how economic policy should respond to such changes. Joseph Schumpeter spoke of the cycle of creative destruction where technology destroys old jobs and brings new, but in this case we might inevitably see more jobs being destroyed than created.

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Artificial Intelligence is only one of the ways that technology is changing our lives. The other one is the rising trend of more and more people seeking more flexible ways to work. There are different ways to achieve that such as contracting, working from home or living the digital nomad lifestyle. Obviously, while flexible working is particularly suitable for jobs in tech, it can be done in other industries, Uber drivers being a prominent example.

This comes to no surprise, as a flexible working can improve one’s quality of life. It could also be beneficial for the economy. Guardian reports that:

“[…] the country as a whole would gain £6.9bn a year in working hours gained, and save £1.2bn a year on the cost of all that desk space and printing costs.”

work life balance

Artificial Intelligence disrupts everything

The end point is that not only the economy is changing, but also our model of working and living. The question is whether current regulations are prepared to deal with these kind of changes. While there has been a real scare in the last few years about machines overtaking civilisation, terminator-style, the real challenge that AI poses is not the destruction of humanity, but the disruption of a large part of the economy.

However, irrespective of how each country decides to regulate or deal with this issue, the two main point is that the technological advances are going to create value for society as a whole, so it is more of a question of how this change can happen without negative repercussions for the way of living of a large part of the working population.

There has been much conversation in the last couple of years regarding Uber. Taxi drivers are opposing Uber since it offers a cheaper (and in some cases better) service compared to taxis. Uber was banned in some German cities, but in London it has won the legal battle. It is clear that the different decisions in countries operating in the European Union are an indication of the confusion that exists regarding this new form of service.

Another obvious issue is safety-related regulations. This topic is particularly relevant for self-driving cars, for example. California has already made the first steps towards it. Uber is also, once again, involved in this discussion with acccusations that the Uber drivers’ criminal record is not properly screened.

AI car
Google’s new self-driving car

In any case, the world in next decade will look much different, hopefully in a better way. Successful regulation will go a long way to make sure the changes are positive. The only way for businesses to get ready for the upcoming changes is through education and digital transformation. This is one of the reasons I decided to start the Tesseract Academy, in order to educate decision makers on deep technical topics, such as AI and blockchain. Feel free to get in touch!

 


If you are interested to know more about how data science can be used in your business, make sure to check out my book The Decision Maker's Handbook to Data Science. Also, make sure to check out my courses, as well as my webinars:
  1. What it's like to be a data scientist 
  2. The importance of data strategy

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