The challenge of enabling a "fairer future of work" was addressed at Nesta's event back in October. A world experiencing exponential change as digital and other technologies challenge our perspectives on life, society, business, the world of work, the nature of jobs, and the notion of "fairness" in the context of work - and even "work" itself – is the context.
It's hard to generalise about employment trends globally but
many developed economies are enjoying close to full employment, or low levels
of unemployment. Our political and economic systems and processes are geared to
creating an environment that seeks to provide full employment. But there is
uncertainty about how sustainable that model is, which begs the question, what
then?
The Changing Nature of Work
Based on the analysis of trends in work, the changing nature
of work, evolution of new business sectors as old traditional industries die,
ideas of how we prepare for new jobs, where the new jobs are created, and how
cohorts of existing workers are retrained to allow them to access employment
opportunities were the focus of the discussion. The use of new technologies
such as artificial intelligence (AI) and Big Data were behind ideas linking
candidates’ experiences, skills, and qualifications with job opportunities and
training interventions.
There's clearly a benefit in bringing data sets together to
inform faster decisions about the evolving jobs market now. Better data, better
information, better insight, better matching of people to jobs to support the
development of near term policy and action.
However, there's a "but". I understand the benefit
of extrapolating from the past to create insights about the evolution of the
jobs market and the world of work. I understand the benefit of seeking new data
sets, and bringing them together to help generate even more insight. But, will
a focus on analysing and extrapolating from the past alone, help us prepare
adequately for the future; especially if that future is radically different?
The Future of Work
If we look at the number of studies into the future of work
we see a significant range of possibilities from increasing levels of
employment through jobs created by new technologies and new industry sectors,
the radical redesign of many existing jobs, to potentially many jobs displaced
by automation technologies.
So for me, the question is how can we use foresight to
pressure test the assumptions we draw from extrapolating trends in jobs, work,
and the jobs market? What are the societal options we may need to consider to
ensure that people continue to live fulfilling lives? How does the nature of
education and training change in a world where we are uncertain about the
future of employment? And within the recruitment sector, how do we address the
rebalancing of technical skills with softer skills and human experiences?
The event demonstrated a number of valuable partnerships
across government (DoE / DWP) and between NGOs and government. These
partnerships become increasingly important given the likely change of emphasis
in the skills required for the future world of work. For example, if many
businesses are using the same automated / AI-enabled systems and products and
services have a very similar look and feel, how will we differentiate our
offerings to customers and clients? Can we re-align people to study a new portfolio
of skills where the balance tips from technical to creative and so called soft
skills? Even now, the question of
assessing a candidate’s soft skills is increasingly pertinent. Is the
recruitment sector truly capable of integrating soft skills into the selection
process?
Fairness
The notion of "fairness" is crucial in that access
to work and jobs must be made on the ability of the candidate to fulfil a given
role and not on the candidate’s ability to access the right technology. So the
democratisation of technology through ubiquitous connectivity is one example of
how national infrastructure needs significant improvement to support a fairness
expansion. Access to skills training enabling more people to use technology as
well as access to the technology itself needs to be addressed.
There was discussion about the applicability of some
technologies in supporting “fairness” including the effectiveness of facial
recognition with darker skin tones. Which begs a question of the development of
algorithms and specially the audit of them to ensure they are technically
capable of operating without bias.
Preparing People Better for Future Jobs
The question here is, can the effective use of jobs and work
data be used to prepare people better for future jobs?
Here, the idea of a “commons data set” accessible widely
would allow candidates, employers, recruiters, educators, and policy makers to
review evolving business sectors and more effectively match people and jobs –
and even provide support where start-ups would have access to the right talent
pool.
But the question of how to prepare for the longer term
future remains.
At what point, for example, do we need to switch from a
technical focused education system to one focused on more human skills; coaching,
facilitation, motivation, mind-set and leadership, creativity, collaboration,
problem solving, systems thinking etc.
Future job systems also need to factor in attitude as well
as technical skills. The labour market of the future is likely to have to
become more flexible, resilient, supported by suitable training and retraining,
and a much better understanding of the dynamics that will underpin the jobs
market in an increasingly digitised society subjected to exponential change.
Questions
Here are four questions that the event posed for me:
- How do organisations effectively assess soft skills and attitudes when recruiting new employees?
- What needs to happen to effectively match workers in the gig economy with work opportunities?
- What role should foresight play in setting the context for future focused education and training policy and design?
- What is the optimal balance between system and process automation and personal interaction in matching people with work opportunities?
Image Credit: Alexas Fotos via
https://pixabay.com/photos/figures-professions-work-funny-fun-1372458/
