“May you live in interesting times” – the Chinese certainly know how to create an insult still relevant hundreds of years later. The basis of capitalism is rocking, the liberalisation and globalisation of our economies is under threat, and the rise of machines and artificial intelligence suggests that many people must find new work and new ways of working.
Many years ago, Peter Drucker described the change from a production to a knowledge economy as being the rise of the knowledge worker. Such people use their knowledge, skills, training, and education to obtain competitive advantage for themselves, their job and their companies. Until recently, this has worked well, but increasingly knowledge workers worry that their traditional advantages and methods of gaining advantage through current education models, are being eroded.
The gig economy or a new set of values?
Peter Drucker noted that millions were displaced in the cotton industry when machines took over peoples’ work. Is there a danger of history repeating itself?
Today there is speculation that we are moving towards a gig economy, where individuals do not have regular work, but bid for work in their specialism on multiple sites. There are abuses, where pay rates are driven down, which devalues their skills set.
To add to this, there is a trend towards lower prices to benefit customers at the expense of lower paid workers and suppliers, as Nicolas Colin explained at the 2016 Global Drucker Forum.
What can we do in a machine age?
As digitisation takes over, this dependence on traditional education is under threat. Some say that more education and retraining is the answer. However, more of the same is seldom the answer to new problems. Can we even retrain millions of people to a new educational level quickly enough so that they can take advantage of new job roles? And can machines learn quicker than we can re-educate humans? If that is the most likely scenario, what can human beings do that is still valuable and attainable for the majority of people?
What do businesses need to do?
The machine doesn’t exercise judgement. It can process data; it can make recommendations based on the data. The machine is essentially past-centred. Its data comes from what has been, not what is yet to be. Its predictions assume extrapolation, not intuitive assumptions.
We know that the pace of change is accelerating, making past data less reliable as a predictor of future events and almost irrelevant as a predictor of future trends. Because of this, as business enablers, Hixsons are moving away from past performance to guide our clients, and much more into future gazing their markets, customers and results. This is what businesses need to focus on now.
The Judgement Worker
Machines also cannot contextualise the human condition in the way that only humans can. Perhaps from knowledge work we now see the rise of the Judgement Worker, a term that I have coined to describe interpreters of data, facts and the human condition, giving meaning and context to them. Judgement workers are essentially future-centred.
Personal services will not be done by machines. You don’t necessarily want a machine cutting your hair or looking after you in your declining years. And perhaps it is in the people-centric areas that status will change.
For example, the care sector is currently poorly paid and resourced, and carers, however good, have limited time to deal with their clients. With the rise of machines, there is an opportunity to remove certain mundane tasks, and introduce education in areas such as empathy, historical context, heuristics, self-knowledge, and other soft skills.
These skills would help carers anticipate and build on what they learn about their clients and adjust the care to keep their clients engaged with the world around them better and longer. This would lead to individual and societal benefits.
To do this requires a more rounded education, and a more generalist approach, rather than the subject specific silo-builders that many organisations have created through hierarchical practices.
Ascribing higher value to judgement work will need a change of educational emphasis. But identifying what work only humans can do may mitigate the projected employment crisis and help reclaim value for individuals, businesses and economies.