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Sunday, March 26, 2017

Machine learning: Should we be excited or fearful for our jobs? |

How machine learning can drive efficiency rather than drive people out of their jobs, insist Nicola Mortimer, head of business products, marketing and operations at Three Ireland

Photo: vectorfusionart/Shutterstock

2017 will be a year of dramatic acceleration in the pace of development of artificial intelligence (AI) and the internet of things (IoT). Machine learning is predicted to be an integral part of more than 300m new smartphones sold this year. So, should we be excited or fearful for our jobs?

It has been predicted that machine learning capabilities will be present in more than 20pc of smartphones sold globally in 2017. With few devices more ubiquitous in the developed world than the smartphone, machines that learn will now be at the fingertips of a large percentage of the population.

What will the increasing development of machine learning, AI, machine-to-machine (M2M) communication and IoT mean for business and industry, and the people who work within them?

One of the important things to realise about the way machines learn, and therefore develop intelligence, is that it is not a mysterious, science-fiction process. Machine learning produces, in effect, nothing more than glorified data crunchers.

Machines that learn can learn only from the data they receive and analyse. What makes them such quick learners and so apparently intelligent is that – unlike humans – they can receive, absorb and analyse all the relevant data in the world at incredibly high speed, and then use it to inform the decisions they make.

Importantly, for the development of true AI, these machines are now also beginning to learn from the data and adapt their behaviour accordingly. For example, at the simplest level, Google Translate now adapts as it learns, to make its translations more accurate.

At the other extreme, data gathered from the journeys of Tesla test vehicles is uploaded to the cloud and made available to all Tesla driverless cars. This means if a test vehicle has driven a stretch of road, when another Tesla vehicle travels it for the first time, it will know how to brake for a specific corner, which lane to take for a turn, even what driving line to take to avoid a large pothole.