If the post-work era is not managed well, it will result in more inequality, which will lead to the collapse of social cohesion and ultimately the collapse of the nation-state.
Artificial intelligence (AI) is no longer the preserve of science-fiction; it is now all around us. AI bots are navigating the internet and collecting information. AI is also changing the world of business and is automating routine tasks while shrinking the number of people participating in the workforce.
It is no longer a matter of choice, because AI is advancing so fast that we now have machines that can replicate the five senses. Computer vision is putting artificial eyes on robots, natural language processing is creating machines that can hear, AI noses are now able to smell toxic materials, AI tongues can now taste wines and offer opinions on their taste scores, and robots are now able to touch and feel objects.
And because of these advances it has become more apparent that jobs once done by human beings are now performed by AI machines. The doctor of the future will use AI to diagnose diseases and improve the effectiveness of medical care. Surgeries will be conducted by robots and power stations will run without human intervention. Basically, AI is ushering in the post-work era, where more production will be accomplished with fewer people.
The big question of our times is what will this post-work era mean for human identity? If this is not managed well it will result in a rise in inequality, which will lead to the collapse of social cohesion and ultimately of the nation-state.
Some proposed solutions to deal with this include universal basic income, taxing robots and job sharing. These policies, if implemented well, will deal with the material aspects of humans. But this alone is not enough. How about other factors such as human and machine identity?
AI will potentially threaten people’s identity and change their psychology when they are left without formal jobs. After all, work occupies many, if not most, of our waking hours. We are taught as we grow up that working hard is the only way to succeed in life. What do you do is the second most common question asked when we meet someone, second only to asking somebody’s name.
The idea of the post-work era idea and its impact on the nation-state is not new. In the 19th century Karl Marx postulated that the rise of machines, resulting in increased leisure, would ultimately cause the “withering of the state”. Aristotle foretold this era thousands of years ago when he said, “The end of labour is to the gain of leisure.”
In the first and second industrial revolutions, people spent their entire lives working for one employer. People did not have much choice in the kind of jobs they ended up with, but this was decided by the circumstances and the interplay of market forces. In the third and fourth industrial revolutions, job-hopping is increasingly common and socially acceptable.
As jobs will be very rare in the era of AI, the idea of long-term jobs will die. What will increasingly happen is that jobs will be shared among people and machines. Instead of having a full-time teacher one will have two teachers who work half the time a normal teacher worked in the previous era. Thus, jobs in the age of AI will be more fragmented. Thus, there will be more piece jobs, jobs on demand, less stable, less secure and less predictable. Holding multiple jobs at the same time will become the norm, rather than the exception. Sometimes this multiplicity will be caused by job availability, but increasingly it will also be because of choice.
Marx warned many years ago that workers felt alienated because they were reduced to a little component in a long chain of production units making a product they could not afford. Highly skilled workers will have more variety in available jobs and will choose jobs they are passionate about, even though these may not be full-time because of job sharing.
Which jobs will remain and which jobs will go? Routine jobs will be replaced by machines. In artificial intelligence there is a concept — the Moravec’s Paradox — which basically states that jobs that require high-level thinking skills are easier to automate than jobs that require low-level thinking skills. Framing this differently, this means jobs which require skills that have evolved for a longer time are much more difficult to automate than jobs that have evolved for a shorter time.
It is more difficult to automate a robot to catch a ball than to automate a robot to look at the demographic and financial data of a customer and give him or her a credit score. It is more difficult to automate kindness, which has been around for a long time, than to automate driving, which is a relatively new skill in human history.
Generally, jobs that require gross motor skills are easier to automate than those that require fine motor skills. The jobs that will remain will be those that require a human touch. From this analysis, it is clear that both blue-collar and white-collar jobs will be affected by AI.
Some jobs that will remain in the era of automation are those where the separation between work and play will be blurred. In the previous industrial revolutions, work was a mechanism for earning a livelihood that consumed physical and emotional energy. In that era play was for fun and often required people to spend money to gain access to it. In the fourth industrial age, the boundaries between work and play are shifting.
There has been a steady rise in voluntary activities and the amount of time people spend on them. One example of this is Wikipedia, which is compiled by volunteers around the world and has now replaced Encyclopaedia Britannica as a key information source.
The story of Wikipedia shows the blurring of the lines between amateur and professional work. Professional jobs were once paid work performed with or without passion, while amateur jobs were not paid work. But recently we have seen many collaborative amateur workers, often using crowd-sourcing platforms, tackling professional problems with great success.
A typical example of this is the concept of citizen scientists. And one well-known success story is the project on protein folding, where through gaming, amateurs made progress in understanding folding chains of amino acids so that therapies can be better targeted — and this has led to the development of synthetic proteins.
This suggests that human motivations are extensive and complex. We should also revisit productive and useful activities traditionally not counted as work, or paid for. These include clean-up campaigns as well as taking care of the sick, young and the elderly. With AI replacing both blue- and white-collar jobs, humans will increasingly be challenged to focus on what matters, beyond the traditional boundaries of the workplace or the notion of work itself, and pay more attention to important matters.
The AI age will force us to re-examine what we know and believe about ourselves as well as how we relate to the world and other people through work.
When money no longer defines work and professions, perhaps core values and meaning might become more important. When we can no longer claim one central professional identity any more, we might gain multiple and more fluid identities. The fourth industrial revolution will unlock the meaning of work and change our identities. DM
Yu Ke is an associate professor in the Department of Education Leadership and Management of the University of Johannesburg, and Tshilidzi Marwala is Vice-Chancellor and Principal of the University of Johannesburg.
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