AI

AI, robotics and the future of work

AI, robotics and the future of work
Robots will take over 6 percent of jobs in USA by 2021, says a recent report by Forrester. Oxford University is even going as far as to say that by 2035, up to 47 percent of our jobs are at high risk of being automated. If that number doesn’t have an impact, imagine this: by the time the current generation of infants legally reaches adulthood, they will have done so in a world where nearly half of our current jobs may be automated.

What are the driving forces behind this development? And which jobs will be targeted?

The driving force behind the automation of jobs – other than continually increased computational power, the heart of everything IT – are two separate developments: Robotic Process Automation (RPA) and Artificial Intelligence (AI). Often lumped together, it is important to distinguish between the two as they appear similar on the surface but are in fact vastly different.

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RPA is automation in purest form, working on an “if this, then that” basis. Mention the right word – or every synonym or misspelling you can think of – and the bot is triggered to fire off one or more of its many preprogrammed actions. It’s doing what we did before – only faster. This makes it easy to imagine customer service employees being automated – the customer calls with a certain complaint or question and the RPA gives the appropriate response. Process completed. It is RPA that will have the most notable, short-term impact on our jobs.

With AI, it’s a different story altogether. AI combines techniques such as machine learning and deep learning to constantly redefine its models and thus, to refine itself. AI is much more adaptive than RPA. RPA will do what you tell it to do, and it will do it again and again and again (when asked). AI is built to be self-learning and as such, it will change what it does as it learns and goes along. It is capable of learning from your behavior as it goes along. And this aspect, the ability to offer personalized, contextual information, will turn out to be more transformative than RPA could ever hope to be, even if it takes AI more time to come to fruition.

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Our fear of a tyrannical AI is greatly surpassed by the ease with which AI slowly seeps into our lives.

And don’t kid yourself: AI is already all around us. The other day I got in my car and Google Maps told me: “it’s busy on the road, it’s a 57 minute drive to your home”. I was surprised, as I had not indicated that I was going home. But there’s no need to tell Google Maps that, as my behavior – driving home after work at a certain time of the day – is regular enough for it to guess where I’m going at that time of the day. Surprised at first, and perhaps a little agitated – “this is none of Google’s business!” – my reaction quickly shifted from agitation to expectation. As soon as I get in my car, I want to know how long it’ll take me to get to my house – and if Google Maps knows that traffic is particularly bad, why can’t it send a quick message to my wife (my next appointment) that I’ll be running late for dinner? Or, if we’re taking an Internet of Things perspective, it may even instruct my oven to cool down so dinner isn’t overcooked when I arrive ten minutes later than usual.

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