Robots are set soon to take over more and more of our jobs.

That’s the prediction that comes from a range of recent research reports, notably by the World Economic Forum at its 2016 gathering in Davos, the McKinsey Global Institute and closer to home, a NSW Parliament briefing paper on future workforce trends.

This is the potential impact of what the World Economic Forum calls the ‘Fourth Industrial Revolution’. They use this term to describe the accelerating pace of technological changes, especially those that are “blurring the lines between the physical, digital and biological spheres”—the combination of things such as artificial intelligence, robotics, nanotechnology and 3D printing.

The World Economic Forum research report on the future of jobs projects that by 2020, 7.1 million jobs are expected to be lost, versus just 2 million gained.

It is not just manual labour and those in routine and semi-routine occupations where machines are likely to outperform humans. Sophisticated computerisation technologies are putting the jobs of administrative workers, technicians and some lower-level service providers and professionals at risk too. Examples include paralegal work being replaced by sophisticated algorithms and law enforcement officers being ousted by cheap and convenient camera sensors.

While there is no room for complacency, there is a positive side to this current wave of technological disruption. New technologies can also bring more flexible workplaces, more engaged workers and new types of work and vital skills that we are yet to imagine or recognise as valuable.

The World Economic Forum report singles out management and leadership skills as enduring ones for survival in this latest industrial revolution. Social skills such as persuasion and emotional intelligence are expected to be in even higher demand than technical skills across many industries. So too are creativity, active listening and critical thinking.

The threat of job losses, especially for particularly vulnerable workers and local communities, is a powerful incentive to find a better solution—whether that is retraining, attracting new investment, enterprises and infrastructure, or creating new jobs and start-ups. In other words, adversity drives innovation. And, particularly important is the kind of innovation where humans consistently add value to the technological advances of robots.

What does this human side of innovation look like? A couple of articles that take a fresh angle offer food for thought.

First, Tom Foremski, the publisher of, argues that while Silicon Valley is a place where start-ups can scale their business, it is no longer the place for sourcing innovative ideas, because of its “self-segregated business park monoculture”.

He contends that Silicon Valley employment practices reduce diversity to simplistic accounting of gender numbers and skin colours, and insulate their people from everyday struggles, resulting in essentially frictionless, predictable living for Silicon Valley creatives.

No original experiences and no real problems means no original ideas.

Foremski contrasts this with the vast urban landscape of New York City, brimming with “a diversity of genders, skin colours, ages, economic backgrounds, national cultures and artistic expression”. It is a place of creativity, quirkiness, multiple sub-cultures, and tough problems. Adversity and diversity combine in a massive incubator of ideas.

The second article by Ron Ashkenas and Markus Spiegel in Harvard Business Review online summarises their research into effective innovation in large global companies. One of their key findings is that the most successful innovation teams were not those that worked like well-oiled machines, but those that resembled more chaotic, but adaptive ant colonies.

The efficient machine-like teams follow highly defined processes and rigid execution plans, but they were the least effective at achieving their goals and coming up with innovations. The successful innovation teams were able to adapt quickly to changes in their environment, because they had a set of simple rules and a clear end goal, allowing them more flexibility and ability to learn along the way.

Ashkenas and Spiegel identify four conditions to make innovation teams more effective:

  1. A powerful central mission and a loose central structure.
  2. Frequent interaction to maximize learning.
  3. Constant experimentation.
  4. Freedom to look for the next horizon.

Perhaps the race between robots and humans still has a way to run.



Jenna McGregor, Davos 2016: robots will steal 5 million jobs by 2020, Sydney Morning Herald, 20 January 2016,

Chris Angus, Future workforce trends in NSW: Emerging technologies and their potential impact, Briefing Paper No.13/2015, NSW Parliamentary Research Service, December 2015.

James Manyika et al, Digital America: A tale of the haves and the have-mores, McKinsey Global Institute, December 2015,

Tom Foremski, Silicon Valley Gets on the Same Bus Every Day—Innovation Needs Diversity, 15 January 2016, LinkedIn Pulse.

Ron Ashkenas and Markus Spiegel, Your Innovation Team Shouldn’t Run Like a Well-Oiled Machine, Harvard Business Review online, 28 October 2015,