Any number of stories can be told about the rise of machines — the role and place of "artificial intelligence" and a "natural" transition into a fourth industrial revolution — as some kind of ghost in the machine.
I place quotation marks around words here, to draw attention to the definitional questions around artificial intelligence (AI) and the idea that there is some natural and unstoppable process under way that lies beyond human abilities or interventions.
What I want to highlight is one story: the fear brought about by uncertainty, of possible ethical lapses and moral degeneration, and inevitable job losses "when machines are allowed to take over". The overriding fear, it seems, is over job losses.
This fear is fuelled by speculation by organisations such as McKinsey, which predicted that because of automation a third of workers in the US would be jobless by 2030. Forrester, one of the most influential research advisory firms in the world, predicted late in 2017 that AI may eliminate up to 10% of jobs in the US in 2018.
Be that as it may, I want to pull a strand from the "ghost in the machine" thesis, which suggests that like all living organisms we humans are essentially passive automata controlled by our environment, and that all we are able to do is manage fallout, risk and tension by adaptive responses.
I draw this strand from Arthur Koestler’s Ghost in the Machine, published almost 50 years ago. The concept retains some validity, but it should be dismantled, which is what Koestler attempted.
The point I wish to make, advisedly, is that we should not fear the rise of the machines and remain passive automata. I doubt that we will wake up on a Tuesday in the future and find ourselves on the event horizon of the age of machines.
We know incremental transformations are under way. We therefore have to work with AI and robotics and it is probably best to avoid conspiracy theories. Scientific and technological innovation has already changed the way we work — less so, perhaps, than it has taken away jobs.
We would be best advised, then, to focus on somewhat of a double movement of advancing technological innovation and productivity, and a countermovement that does not seek to disinvent technological achievements, but to adapt to new technologies.
It is extremely difficult to uninvent scientific achievements. Consider drone technology. We cannot roll back what has been achieved, but this does not mean we have to accept without question the way drones are used to kill people from safe rooms on different continents.
The advent of AI and robotics, such as it is, is also insufficient reason to abandon social objectives. For instance, in his address to the World Economic Forum in Davos last week, Indian Prime Minister Narendra Modi emphasised his country’s objectives of reducing poverty and income inequality and creating jobs by engaging with the opportunities (and dangers) of technology.
We should prepare workers, co-ops and companies to adapt skills and reorganise the way we work
As it goes, historically there have been significant lags between scientific achievements, the consequent introduction of new technologies, their productivity-enhancing benefits, and the overall social impact. What we cannot do is sit back and consider ourselves helpless — as were those passive automata Koestler referred to.
We should prepare workers, co-ops and companies to adapt skills and reorganise the way we work. Moreover, our education systems, rather than fight battles with imaginary enemies, should be progressive and forward-looking.
This is not just a problem in poorer societies. There are looming skills gaps in the wealthiest societies that cannot be filled. We may want to use these skills gaps to direct, develop and reform curricula across the social sciences, humanities, in engineering and the built environment.
One body of research (produced by Code, a US organisation working to expand access to computer science in schools) found that by the end of 2017 there were about 500,000 open computing jobs, for which there were only 43,000 computer science graduates. This is an enormous skills gap, which the wealthiest of societies are struggling to fill.
One aspect of this skills gap is the perception that everyone who wants to work in IT has to go to university. Yet these skills can be acquired in colleges and on-the-job training.
In short, we should probably do away with the misty-eyed belief that a human being can be "unskilled" and follow that up with deliberate interventions to prepare our workforce for the rise of the machines.
Scientific achievements cannot be rolled back, but we can learn to use them to create a better society.
• Lagardien was formerly executive dean of business and economic sciences at Nelson Mandela University, and has worked in the office of the chief economist of the World Bank as well as the secretariat of the National Planning Commission.
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