Source: Ryan Etter
It is quite straightforward to imagine automated machines replacing human workers in a factory environment. It is more difficult to imagine, however, artificially intelligent software performing tasks normally done by skilled office workers and even researchers, and at the first glance it seems fairly frightening. But is this fear of technology replacing humans justified?
We are currently living in an Information Age where technology is advancing at an exponential rate consistent with Moore’s Law (processing power for computers will double every two years). As a result, computers can be programmed to become increasingly more intelligent - even developing ‘senses’: from ‘hearing’ by iPhone’s personal assistant, Siri, and ‘seeing’ by the Google’s self-driving car, to actual article ‘writing’ by Narrative Science developed algorithms.
Whilst all of these technological developments can be appreciated as weird and wonderful, job stability must also be remembered. The thought of losing either your current or potential job to a machine is not ideal, but on the other hand, technology has spared countless numbers of people from the drudgery of repetitive and genuinely dull labour. It can also lower prices on goods, as companies do not have to pay as much in staff wages. From assembly line jobs and checkout operation to call centre services, machines have and will continue to replace human jobs.
But what kinds of occupations will become automated, and how far away from today is this computerisation? A report by the Oxford Martin School at the University of Oxford was published in 2013, which attempted to model the effects of computerisation on the future employment in the US. To be brief; it did not appear optimistic.
The researchers’ model included 702 specific occupations, and it was calculated that a potential 47% of total US jobs could be automated within the next 10-20 years. That’s a percentage that is hard to ignore.
Jobs involved in transportation, office work and production occupations were included in this 47% ‘risk’ category. To compare the model with today’s innovation, we already see investment by Google and various other car companies in vison and control research; so human vehicle drivers may become obsolete when technology advances far enough.
Interestingly, the model also predicted that service occupations - jobs that provide services to a person or a company - are also highly susceptible to computerisation within the next 10-20 years. Again, you can actually see how today’s programs, like Ross, a law research service powered by the famous Watson supercomputer, can carry out research at the same level as an entry-level paralegal (not yet qualified lawyer). And so, Ross’ automation has a potential to open a market for lawyers as well as people who cannot afford lawyers. An ultimately advanced version of Ross could answer legal questions and even deal with small law cases on its own, reducing the number of lawyers required.
Overall, the report concluded that employees in the mentioned ‘risky’ occupations would have to gain sets of skills which are not influenced by automatisation, such as one that require creativity and social intelligence, in order to find new career opportunities.
Despite all of the predictions specified in this report, the good news is that the researchers of this report assessed the certainty of their predicted model, and stated that it is only viable under various assumptions, such as public acceptance and relatively low amounts of cheap labour available at a time.
Another report, conducted by the Pew Research Center, surveyed almost 2000 people with expertise in artificial intelligence, robotics and economics to find out their opinion on the impact of automation from 2014 (when the survey was carried out) until 2025.
Interestingly, 52% of respondents speculated positive employment prospects, with enough job positions for humans. Their general view was that machines would not displace more jobs than they create. However, the other 48% of respondents hypothesised a more negative employment future, in which the machines will acquire a large proportion of both blue- and white-collar jobs. However, the one thing on which nearly all surveyed experts agreed upon, was that the replacement of human jobs by artificial machines will accelerate over the next 10 years.
So if the experts are divided on this view, how are we, the general public, to deal with the technological computerisation of our work-places? An appropriate point, made by internet sociologist, Howard Rheingold, was, “Only the best-educated humans will compete with machines… and education systems in the US and much of the rest of the world are still sitting students in rows and columns, teaching them to keep quiet and memorise what is told them, preparing them for life in a 20th century factory”.
Rheingold may be right, as he implies teaching techniques should be transformed if humans are to face the employability challenges associated with the “rise of the robots”.