AI, Automation And The Future Of Work

If you believe the media headlines, robots are coming to take anywhere up to 45% of our jobs, resulting in huge disruption and potentially mass unemployment.  Is that a realistic prognosis of the future of work?

The last few years has seen vast quantities of coverage on the potential impact that AI, robotics and associated technologies might have on our jobs and careers.  The majority of this coverage has been dystopian, with headlines predicting the number of jobs that might be automated away by new technologies.

It’s perhaps not surprising therefore that a recent study from researchers at Ball State University found that stress about automation was making people physically and mentally unwell.

“While estimates of potential job losses due to automation vary for our nation— with one as high as 47 percent—most people agree that the risk of automation is significant and growing,” the authors say. “People who live and work in areas where automation is taking place are sickened by the thought of losing their jobs and having no way of providing for themselves or their families.”

The study found that as the risk of automation rose by 10%, the physical and mental health of an area declines by 2.38%.  This doesn’t mean however that people are uniformly opposed to the use of AI-based technologies at work.

For instance, a survey by workforce solutions company Adecco recently found that leaders were optimistic about the impact AI will have.  The vast majority thought that not only would it make jobs easier by automating many of the mundane tasks that will our day, but it would also increase the number of jobs available.

“Far from the widespread fear that automation will make employees redundant, our research shows that the workplace of the future could create opportunities for more flexible and fulfilling work. Many organisations and employees are buying into the idea of flexible working, but struggling to implement the reality. Our research suggests that robots could be a significant part of the solution,” Adecco say.

New skills required

As AI-based technologies find their way into the workplace however, it’s inevitable that new skills will be required, both to develop the technologies in the first place, and then to work alongside them efficiently and effectively.  Indeed, a recent survey by EY found that a skills shortage was the single biggest barrier to the deployment of AI in the workplace.

This shortage of skills is likely to herald a renewed focus on skills development as organizations look to make up this shortfall.  Indeed, in 40% of the organizations surveyed by EY there was a plan to significantly increase expenditure on training and development.

This investment into training and development is likely to require a fundamental reassessment of jobs, with a mental alignment more towards the very nature of the work itself.  A recent report from Accenture advocates doing this in three main steps:

  1. Assess both tasks and skills -This will go beyond merely a record of the job roles within your organization into a detailed understanding of the tasks and skills that make up those roles.
  2. The creation of new roles – As AI applications mature, it’s inevitable that roles will change to focus more on insight and strategy than routine, repetitive work.
  3. Map skills to these new roles – The last step is to begin mapping the skills your organization needs with the skills it has.  This basic skills audit will allow you to take an evidence-based approach to developing the skills required in future.

Indeed, Accenture have further developed their thinking in this area to propose three broad categories of roles they believe will be crucial in working with AI in future.  These roles are:

  • Trainers – who help computers learn and become smarter.
  • Explainers – who interpret the results produced by the computers to improve the transparency and accountability of their decisions.
  • Sustainers – who will ensure that the AI systems stay true to their original purpose and don’t move into unethical territory.

“It is becoming clear, however, that as people and intelligent machines begin to collaborate in entirely new ways, business leaders will have to pivot their workforce not just once, but twice. The second and truly transformational shift may be less than a decade away in some sectors. In the meantime, business leaders must make a more immediate pivot to take full advantage of the opportunities human-machine collaboration presents now, which can create the springboard to entirely new future growth opportunities and market disruptions.” they say.

The missing middle

The predominant narrative around AI and its impact on the workplace has taken a destructive form, the reality is that the skills shortages we’re seeing throughout the economy project a different picture.  It’s a picture of new skills being required in what’s known as the ‘missing middle’, or the interface between man and machine. As autonomous technologies become more powerful, there will be completely new roles, and new skills, emerging to work effectively alongside them.

The most successful organizations will be ones that don’t try and bolt AI onto legacy processes, but rather ones who recraft the way they work to better mesh with the possibilities the technologies present.  In their latest book, Human + Machine, Accenture’s Paul Daugherty and James Wilson outline five core principles they believe these organizations will exhibit:

  1. Mindset – the best organizations have a radically different approach towards business that sees human employees improving AI, and AI in turn improving the performance of human employees.  A crucial first step is to develop the potential of employees to apply automation to their various routine tasks.
  2. Experimentation – AI remains largely untested in many organizations, so successful implementation will require a constant search for ways in which processes can be improved by the technology, and an experimental mindset to try things out.  This is charting new territory so organizations will have to learn as they go, so the ability to create tests to derive business processes that work will be vital.
  3. Leadership – the best organizations make a specific commitment towards the responsible use of AI from the start.  The ethical, social, moral and legal implications of AI have been well investigated.  Therefore, executives must promote AI that is explainable, transparent accountable and free from biases.
  4. Data – most AI technologies today run on data, so it’s vital that organizations get their data house in order.  The accumulation and preparation of data is one of the biggest challenges for the successful deployment of AI systems today.  The best organizations have data that flows freely across departmental silos.
  5. Skills – to work effectively with AI will require what the authors refer to as ‘fusion skills’.  The next wave of AI technologies in the workplace will require humans to design, develop and train AI systems, as well as collaborating effectively with them.

Far from presenting a doomsday scenario akin to that depicted in science fiction movies, it presents a scenario where we are very much in control of how man and machine will evolve to work alongside each other in the workplaces of the future.  The challenge now is to make that scenario a reality.



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