Different strokes. The risk of jobs being taken over by technology / automation varies by country. It’s different strokes for different folks. In Africa, the range varies from 65% in Nigeria to 85% in Ethiopia and it is reasonable that as much as 64% of a Citi Research respondents [PDF] believe automation will lead to major challenges – especially with respect to labour and wealth distribution.
The scope of automation is widening and adoption is speeding up. Mainly because of the advancements in Machine Learning technology, including Data Mining, Machine Vision, Computational Statistics and other subfields of Artificial Intelligence (AI).
Computer and automation rigs are able to process larger data sets with more speed and accuracy and in turn, are making an economic case for more companies to deploy them.
Despite previous conclusions that non-routine jobs are not at risk of automation, these trends in data processing render such assurances shaky at best.
Work Fusion, for instance, a US-based software company, sells software to automate non-routine tasks which were previously cocooned from the reach of automation.
What the software does is simple, yet it puts all jobs at risk of future automation. The software divides specific non-routine jobs into smaller routine tasks, automates the routine aspects of the job and then recruits freelance workers for the non-routine aspects. As the freelancers work, the software monitors and learn from them, meaning that as time progresses, the machine will automate more of the non-routine tasks. The freelancers, essentially, are working themselves out of the system.
Careers are wont to be more disrupted than at any other point in the past and confronted with this reality, individuals and companies have some choices to make if they are to stay relevant in the rising dispensation.
In the movie, Hidden Figures; that paean to black ingenuity and specifically the uncelebrated strength of three African American female mathematicians at the mid-60s’ NASA, Dorothy Vaughan (played by Octavia Spencer) started a guerrilla FORTRAN training for the 30-odd colored ladies who previously were only adept at typewriting. Dorothy started this training regimen after she learned of the impending installation of an IBM 7090 electronic computer that could replace her co-workers at the NASA complex, with an understanding that though the IBM is faster, it would need humans to code it. When the time came for the machine to start firing on all cylinders, the colored ladies were ready to colonize the punch cards.
There was a smooth transition.
Like in the 60s with the introduction of faster, more capable computers, a talent mismatch already exists. Automation and robotics need specific human effort to work. This shortage of skills is one of the barriers to widespread adoption of automation and robotics.
As more skilled workers lose their job to automation across Africa, they will take up lower-skilled jobs that might lead to lower living standards. Early retraining, on the other hand, will prepare humans for a future powered by machines – which will increase the value of human effort and drive rapid economic progress.
A 2014 study by UK charity Nesta [PDF] found that for both UK and the US, almost 90% of creative jobs are at low or no risk of automation. This is mostly because creative jobs need a high level of perception, manipulation, creative intelligence, and social intelligence to carry out. These also happen to be the most profound bottlenecks to automation.
While the advancement of automation and robotics may be slower in Africa, the adoption is inevitable. Companies and individuals that have up-skilled in the creative aspects of their industry are more likely to be insulated from the effects of automation.
Not unlike Dorothy Vaughan, African companies from Yaba in Nigeria, to Ngong Road in Nairobi, need to acquire growth models that make them relevant in the future by training its existing workforce for this future.