The robots are coming... but could it make work more fulfilling?
“Some people will have some retraining, but that will mean they have time to focus on more important activities” Josh Hobbs, Master of Technological Futures graduate, Innovation Ventures Lead at CCL.
It used to be reserved as the plot of sci-fi stories but the idea of sharing the workplace with machines or robots is now very real.
The World Economic Forum (WEF) has noted that the Covid pandemic - and the economic paralysis it caused - is directly linked to the acceleration of the Fourth industrial revolution (4IR). This latest industrial revolution is characterised by the convergence between digital, biological and physical innovations stimulated by new technologies like artificial intelligence (AI) and machine-learning (ML), cloud computing, robotics, 3D printing and the Internet of Things (IoT). And it's going to change our lives in extraordinary ways.
But robots displacing humans in the workforce is nothing new. For the better part of 60 years, robotics and automation have been augmenting the work of humans. The term ‘automation depression’ was coined in the 1960s when people were displaced from factory floors, service station forecourts and offices, causing wide-scale unemployment.
Mention AI, machine learning and robotics today in relation to the workplace, and it’s often met by a fear that we’ll see this mass unemployment again. A McKinsey Global Institute report in 2017, ‘Jobs lost, jobs gained: workforce transitions in a time of automation’ found that between 75 million and 375 million people globally may need to change occupations and acquire new skills by 2030. But the impact is more likely to be felt in jobs that are primarily physical and performed in predictable environments, like operating machinery and preparing fast food.
There will also be a significant augmentation to support jobs and occupations still carried out by humans - where machines or AI do the grunt work and humans oversee and validate with an emotional, subjective perspective, as only humans can do.
Jobs as we know them today will change - that is inevitable. The WEF has identified the job landscape of 2025, and perhaps unsurprisingly there’s a lot of growth in digital and technical occupations, while a clear decrease in those more mundane repetitive occupations.
Use machines for the mundane
The opportunity AI and robotics provide human labour are to do more mundane or onerous tasks within a job. Humanity has been doing this for some time - we no longer harvest by hand, nor do we write everything down on paper or use an abacus to do our sums. Our productivity has increased out of sight compared to the pre-industrial era, and AI or ML is just another (albeit massive) step in that ‘less is more’ direction. When we harness the grunt power of machines, we free ourselves to focus on the more creative and arguably more fulfilling aspects of work.
Super human-machine teams
One common example cited of super human-machine teams is that of radiologists - where machine-learning algorithms can now be employed to scan and categorise masses of medical images that are then reviewed and checked by an experienced radiologist. If this task is performed just by humans, accuracy could be around 95 percent; performed by the machine-learning algorithm, accuracy increases to 97 percent. But when both a human and machine are teamed up together, accuracy increases to 99 percent. This type of augmentation removes the more mundane, repetitive tasks from humans but also provides an opportunity to increase efficiency, productivity and accuracy overall.
This partnership between humans and machines also opens doors for us to be more creative in our thinking. If we can spend less time doing and more time thinking and assessing, we’ll have better capacity for problem-solving. And there are a few challenges on the radar that our great minds could be set to solving.
Using AI, machine learning and robotics could also supercharge our capabilities. If we think of AI as a super brain we can plug ourselves into (not literally), we gain a significant ability to process, compute, and model all types of ideas quickly. The approach of testing and failing fast to problem solve will become all the easier with machines at the ready to help us do the heavy lifting.
Career counselling for an AI augmented future
The juncture we’re at now does mean it requires some careful consideration of career path planning. The traditional siloed career route is fast becoming obsolete. A resilient future requires people to have a more holistic view that takes into account technology, humanity and the interplay these have with the environment.
Daniel Susskind, author of ‘A world without work’, believes there are two main strategies to consider when thinking about careers in the future:
Either learn to be good at the sorts of things machines and systems cannot do (roles that require creativity, empathy, compassion, intuition) or;
Learn to build the machines, and become the master
Masters of technology
What is incredibly important is that if AI, ML and any of the 4IR technologies are to be in all our futures, then it's really on us to have a fairly applied understanding of what they’re capable of.
This is why at Tech Futures Lab we focus on keeping tech human, and why we developed the Master of Technological Futures programme. We need masters of these technologies from a human perspective - to ensure we remain in control; that we have an intimate understanding of what is happening inside the box; and that we ensure ethical application is always a mandate of development.
Opportunity awaits us
There are always two sides of the progress coin - and right now, while we’re at the beginnings of the 4IR, we must pay heed to the positives and negatives it can bring. We must take lessons from previous industrial revolutions when we focused too much on technology and the productivity gains without having any real awareness of the environmental trade-offs we’re now seeing coming home to roost. Our challenge now is to think ahead and use foresight to negate future dilemmas.
The irony is, AI could actually assist us to do just that.