The future of work
According to a leading business consultancy, 3-14% of the global workforce will need to
switch to a different occupation within the next 10-15 years, and all workers will need to
adapt as their occupations evolve alongside increasingly capable machines. Automation - or
'embodied artificial intelligence' (AI) -is one aspect of the disruptive effects of
technology on the labour market. 'Disembodied AI', like the algorithms running in our
smartphones, is another.
Dr Stella Pachidi from Cambridge Judge Business School believes that some of the most
fundamental changes are happening as a result of the 'algorithmication' ofjobs that are
dependent on data rather than on production-the so-called knowledge economy.Algorithms are
capable of learning from data to undertake tasks that previously needed human judgement,
such as reading legal contracts, analysing medical scans and gathe1ing market intelligence.
'In many cases, they can outperform humans,' says Pachidi. 'Organisations are attracted to
using algorithms because they want to make choices based on what they consider is "perfect
information", as well as to reduce costs and enhance productivity.'
'But these enhancements are not without consequences,' says Pachidi. 'If routine cognitive
tasks are taken over by Al, how do professions develop their future experts?' she asks. 'One
way of learning about a job is "legitimate peripheral participation"-a novice stands next to
experts and learns by observation. If this isn' t happening, then you need to find new ways
to learn.'
Another issue is the extent to which the technology influences or even controls the
workforce. For over two years, Pachidi monitored a telecommunications company. 'The way
telecoms salespeople work is through personal and frequent contact with clients, using the
benefit of experience to assess a situation and reach a decision. However, the company had
started using a[n] ... algorithm that defined when account managers should contact certain
customers about which kinds of campaigns and what to offer them.'
The algorithm-usually built by external designers - often becomes the keeper of knowledge,
she explains. In cases like this, Pachidi believes, a short-sighted view begins to creep
into working practices whereby workers learn through the 'algorithm's eyes' and become
dependent on its instructions. Alternative explorations-where experimentation and human
instinct lead to progress and new ideas-are effectively discouraged.
Pachidi and colleagues even observed people developing strategies to make the algorithm work
to their own advantage. 'We are seeing cases where workers feed the algorithm with false
data to reach their targets,' she reports.
It's scenarios like these that many researchers are working to avoid. Their objective is to
make AI technologies more trustworthy and transparent, so that organisations and individuals
understand how AI decisions are made. In the meantime, says Pachidi, 'We need to make sure
we fully understand the dilemmas that this new world raises regarding expertise,
occupational boundaries and control.'
Economist Professor Hamish Low believes that the future of work will involve major
transitions across the whole life course for everyone: 'The traditional trajectory of
full-time education followed by full-time work followed by a pensioned retirement is a thing
of the past,' says Low. Instead, he envisages a multistage employment life: one where
retraining happens across the life course, and where multiple jobs and no job happen by
choice at different stages.
On the subject of job losses, Low believes the predictions are founded on a fallacy: 'It
assumes that the number of jobs is fixed. If in 30 years, half of 100 jobs are being carried
out by robots, that doesn't mean we are left with just 50 jobs for humans. The number of
jobs will increase: we would expect there to be 150 jobs.'
Dr Ewan McGaughey, at Cambridge's Centre for Business Research and King's College London,
agrees that 'apocalyptic' views about the future of work are misguided. 'It's the laws that
restrict the supply of capital to the job market, not the advent of new technologies that
causes unemployment.'
His recently published research answers the question of whether automation, AI and robotics
will mean a 'jobless future' by looking at the causes of unemployment. 'History is clear
that change can mean redundancies. But social policies can tackle this through retraining
and redeployment.'
He adds: 'If there is going to be change to jobs as a result of AI and robotics then I'd like
to see governments seizing the opportunity to improve policy to enforce good job security.
We can "reprogramme" the law to prepare for a fairer future of work and leisure.'
McGaughey's findings are a call to arms to leaders of organisations, governments and banks
to pre-empt the coming changes with bold new policies that guarantee full employment, fair
incomes and a thriving economic democracy.
'The promises of these new technologies are astounding. They deliver humankind the capacity
to live in a way that nobody could have once imagined,' he adds. 'Just as the industrial
revolution brought people past subsistence agriculture, and the corporate revolution enabled
mass production, a third revolution has been pronounced. But it will not only be one of
technology. The next revolution will be social.'