Future of human work in the age of AI

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Since the Industrial Revolution, the speculations that mechanisation ⚙️ will take away the jobs have been high. Such rumours remained rumours only for the most part of the time since. There was indeed a decline in numbers of jobs in certain sectors, only to be compensated by the emergence of other totally new sectors. When the fields become factories, the farmers who lost their jobs became factory workers. The cart-drivers become lorry drivers and so on. This switch required fairly insignificant reskilling. A farmer becomes factory worker with somewhat the same, or a bit enhanced and different, set of skills.

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With more and more sophistication within the factories, some factory workers got laid off but new avenues of work emerged. Demand rose for new technicians to maintain those machines, more researchers needed to further improve the technologies, etc. This time the switch needed a bit more specialization.

Does that mean we should not take the current threats of automation seriously? Not really. This time it is different. Although the loss of some jobs in the future due to automation will be compensated by the creation of other jobs, the challenge, however, is the level of skills needed to make the switch. This time it might not be the cart-driver being pushed to become a lorry driver. Metaphorically, it could be the cart itself being required to turn into the lorry engine.

The developments in automation so far have  made man’s life easier. Machines should not be seen as competing with humans. If that were the case, they have left humans far behind already. As long as they act like personal assistants, only taking over workload, all is well. A human may still have delivered the last amazon_logo_RGB shipment you unpacked but the order was received, recorded, sorted, packed and dispatched by a series of algorithems/robots.

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Robots in Amazon warehouse. (Image Courtesy: Reuters)

Worry kicks in with the future prospects of Artificial Intelligence (AI). AI not only has the ability to out-perform humans, it may even one day render humans out of the league. If this sounds like a crazy idea, remember that computer program trained in chess has already defeated the world chess champion(s). This is news not from 2017 but from 1997. The news from 2017 is AI technology defeating a computer program in a game of chess, only after learning it itself in four hours time. Welcome to the age of Machine Learning.

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Machine learning allows a computer program to learn itself, without any programming fed to it. Machines can then make decisions on their own, requiring lesser and lessee human intervention as they improve. Machine learning systems are already in place. When you take out a rather previously unmatched sum of money from your ATM, it is machine learning that rings the bells of a suspected fraudulent transaction on your cell phone. It is not that the system suspects your identity while you wait for the machine to dispel currency notes. It simply compares your current transaction amount against your previous records of withdrawals. This is a simple example of machine learning at work. As long as what machine learning does is to facilitate humans, all is well.

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If the AI begins to take the workload off humans that much that they become absolutely irrelevant, that’s the point of raising red flags. 🚩

What can be done? If the rate of development in automation is slowed down, the future generations can buy more time in getting prepared for such frequent switches in employment expected in the future. The human mind has evolved over millenniums. The current rate of switching expected of humans is a bit too much of a change for them to handle, thus resulting in fatigue and anxiety. People used to stay in the same career whole their lives. It has already started to change and in the future a career for a lifetime will become something of the history.

We cannot halt the loss of the jobs altogether. That would mean giving up on all the great benefits the technologies of the future have the potential of offering to the service of mankind. So far in history loss of jobs due to automation has always resulted in the creation of others. Though, the task force for the future this time is expected not only to be more adaptable but also ironically equally specialized.

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As a compensation for the jobs lost to the hands of robots, governments of the future should strive to create an even higher number of jobs simultaneously. That stands as a towering challenge.

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Hence, of all the –bilities, ‘learnability’ will prove to be the most useful ability in staying relevant in the future. Any job that involves ‘routine-work’ is definite to get automated. So if you are a checkout cashier, you better start taking online courses now. By being able to always learn new skills with time, humans can ensure that they are not outdone absolutely. The (constructive) technologies should be embraced as assisting hands. By adjusting the model of progress the developers should steer it in such a direction that it at least fully protects the humans from becoming irrelevant, if not their jobs.

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