Automation will take over tasks, not jobs
The degree of job transformation will depend on how many discrete automatable tasks within a job that could be logically ‘broken-down’ and be cost-effectively supplemented or replaced by machines, artificial intelligence, or robotics in a socially acceptable manner.
McKinsey found that, from a technical standpoint, a job that occupies up to 45% of an employee’s time could be automated by adapting currently available or demonstrated technologies.
It is important to note that as each job is made up of multiple, discrete, or different types of task or activities varying degrees of technical feasibility, it was found that less than 5% of jobs could be fully automated. That is, every activity in the job could be handled by a machine.
This means that only up to 5% of jobs could potentially be lost because of automation.
With the exponential advances in technology and machine learning, it may not be long before more jobs could be fully automated. It’s only a matter of time.
While it is technically feasible to automate, it may not be economically and socially acceptable.
There are five factors according to McKinsey that will determine whether tasks or activities within jobs can be automated:
- Technically feasibility for doing so.
- The cost to automate the task and whether it makes economic sense to do so.
- Availability of skills and the cost of workers who might otherwise have to do the activity.
- Benefits (e.g., superior performance) and value of automation beyond just labor-cost substitution.
- Whether automation is permitted by regulation and is socially (and morally and ethically) acceptable to do so in the geographical location in question.
There are various scenarios at play here that will determine whether automation will take over our jobs.
Scenario 1 – Voluntary substitution
We allow machines to voluntarily substitute our jobs because we are no longer prepared to do the work ourselves.
In fact, we are happy for machines to take over our jobs. Examples of voluntary substitution include military service, car production and manufacturing, space exploration, underwater exploration, duct cleaning, crime fighting, fixing oil spills, investigating hazardous environments, and commercialised agriculture.
Scenario 2 – Involuntary substitution
Machines can be more efficient or effective than humans in doing manual, repetitive, boring, and dangerous tasks.
As such, we are involuntarily substituted by machines even when we are still able to do the job. Examples of involuntary substitution include truck driving, parcel delivery, inventory stocking, and floor cleaning.
Scenario 3 – An acute labor shortage
Machines can be deployed in industries and jobs where there are acute labor shortages. There’s no choice for humans but for machines to be deployed and perform the jobs that we don’t have enough qualified people to do the work.
This problem will grow exponentially when larger numbers of Baby Boomers retire over the next decade or two. Robots could fill jobs that this generation is abandoning.
Scenario 4 – Uneconomical labor cost
Machines are deployed in industries where labor cost pressures will easily dictate the decision to automate. It is totally uneconomical to keep high-cost labor over lower-cost machines.
When labor cost becomes too expensive, organisations will have no choice but to use lower-cost robots and machines to substitute human labor to lower their operating cost and increase or maintain profitability.
Labor unions have to be mindful of their push for higher wages. The unintended consequence is for businesses to react to higher salaries and wages through lower-cost automation and off-shoring work to lower cost countries.
Scenario 5 –Co-development and augmentation
Humans can strategically co-develop machines with developers that will augment work and free us up to do higher value work. This will require higher level skills and competencies that include decision-making, conceptualising and analysing.
Therefore, demand for these higher level skills should increase over time to sustain or enhance incomes levels.
Humans will move up the value chain.
In this scenario, robots will co-exist comfortably with humans in workplaces and transform our jobs into new ones that require higher level skills. This is an ideal state where we proactively control our destiny and future through strategic collaboration and not the destruction of our own jobs and lifetime.
Scenario 6 – Unavailable technology, yet
Machines are good in content but are really bad in analysing, understanding and appreciating the context they are in, which is constantly changing.
Robots will not take over our jobs because we cannot teach or program machines to effectively analyse or conceptualise things, be creative and innovative, and be naturally interactive with humans (especially within a social context).
These are unique human-only tasks that cannot be done by robots, yet (at least for this moment).
Robots cannot look you in the eye, consider peoples’ feelings, moods and behaviors, feel emotional, empathy and sympathy, make a person feel taken care of or loved, establish trust and respect, be an independent critical and analytical thinker, and make sense of complicated concepts and context in a complicated world we live in.
Scenario 7 –Changing jobs prior to automation
We can re-learn and re-skill to acquire new skills and change jobs well before robots take over our jobs.
By anticipating these changes and future-proofing our jobs and incomes early, we can future-ready ourselves well before robots do eventually come and appear at our door-steps.
What’s important is to have or acquire employable or in-demand skills that can effectively fill employment vacancies and remain employable in the long-term.