Intelligent Automation and the Fourth Industrial Revolution

The content of this article is inspired by the Amazon bestseller book “Intelligent Automation.”

Intelligent Automation refers to a powerful and continually evolving set of technologies for automating knowledge work and augmenting the work of human knowledge workers. Based on the speed and scale of its recent advances, it is likely to have a huge impact on the world of work and, by extension, on all of society.

Klaus Schwab, founder and executive chairman of the World Economic Forum, has called intelligent automation “the fourth industrial revolution”.

Just like the previous industrial revolutions, which automated agricultural and manufacturing work, the fourth industrial revolution will bring disruption and upheaval to the job market and to society as a whole, and has the potential to make drastic changes, both for the better and for the worse. So what actions can we take now to ensure the positive changes and mitigate or eliminate the negative ones?

Let’s look at two extreme scenarios: an optimistic one and a pessimistic one. These illustrate the range of possible outcomes from the widespread adoption of IA. It is likely that the actual future will lie somewhere between the two, but we can use the two scenarios as a framework to guide our society closer to the optimistic one. I believe we can do this by meeting five critical imperatives: (1) evolving skills, (2) sharing the wealth, (3) rethinking work, (4) reinventing education, and finally (5) building a potential new society.

Two Scenarios at Opposite Ends of the Spectrum

The Optimistic Scenario

In the optimistic scenario, IA will create more new jobs than it will destroy, resulting in a net gain of jobs—and the new ones will typically be more interesting and fulfilling than those lost.

The World Economic Forum predicted in 2018 that workplace automation would create 133 million new jobs by 2022, while displacing only 75 million, resulting in a net increase of 58 million jobs.

We can predict what some of these new jobs will be—data scientists, robotics engineers, AI ethicists—but some will take us by surprise, like Uber did in the previous decade.

The optimistic scenario sees IA yielding significant productivity gains, leading to vastly improved standards of living and a net increase in jobs.

The Pessimistic Scenario

In the pessimistic scenario, the fourth industrial revolution will not follow the same pattern as the previous ones, but instead will progress too quickly for us to keep up. Jobs will be eliminated more quickly than employees can reskill, leaving a generation of people unemployable.

It took 100 years for the number of farmers to decrease by 90%, and 60 years for the number of factory workers to decrease by 75%. This comfortably slow pace gave older workers enough time to reskill or just carry on until retirement, and allowed children to grow up learning the skills needed for the new service economy. But this time we may only have 10–15 years to adapt, because technological change is now so fast and growing exponentially. Children currently in elementary school will enter the job market needing vastly different skills from those of their parents: if we want them to be employable, we must start preparing them now.

The other concern of IA pessimists is that humans have previously been able to adapt to technological disruption thanks to our intelligence—but this time it’s intelligence itself that’s being automated.

According to a survey by Yale and Oxford researchers, AI experts believe that within the next decade AI will outperform humans at writing high-school essays, driving, and working in retail, and it will write bestselling books by 2049. Furthermore, they predict a 50% chance of AI outperforming humans at all tasks within 45 years. If this comes to pass, how will humans be able to compete or remain useful? What unique roles will remain for us?

The Five Imperatives

Evolving Skills

In response to the automation and augmentation of work by IA, we need to redesign job roles and reskill employees, and incentivize working in collaboration with technology.

Sharing Wealth

Technological breakthroughs like IA tend to exacerbate wealth inequality: those who own the technology get richer, and those whose productivity is augmented by the technology are enabled to earn more, but those whose jobs are replaced by the technology lose out.

To ensure that the gains from IA are distributed fairly, we need to implement initiatives like Universal Basic Income, to give everyone a share in the increased wealth and financial security. On top of that baseline, those who wish to earn even more through their own capabilities augmented by IA can still do so.

Rethinking Work

Much of today’s work is boring, soulless, and unfulfilling. We need to move away from defining people by their jobs, and consider reducing or abolishing work, thanks to the time freed up by IA, and move towards more meaningful, creative or relational ways of spending our time.

Reinventing Education

We need to reorient education around helping people find their purpose in life, and move away from mass-produced education that focuses on work and trains people for skills that may become obsolete.

Building a New Society

If we free our society from its obsession with work, we have the potential to build a new culture focused on humanity, relationships, creativity, and respect for the environment. To achieve this, governments need to begin planning ahead now.

Preparing for both scenarios

If the optimistic scenario comes to pass, only imperatives 1 and 2 (evolving skills and sharing wealth) will be necessary. The other three will be optional, but it would be best to seize the opportunity to implement them anyway, to create a more resilient and human society.

In the pessimistic scenario, all five imperatives will be vital to prevent widespread unemployment and underemployment, leading to social unrest, and perhaps revolutions or wars.

Either way, we need to be ready with a thoughtful and rigorous plan that covers both scenarios and anything in between, so that we can manage the risks of both and prepare for the results.

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