Interview with Professor Didier Fouarge and Principal Consultant Cornelia Suta
In this interview Professor Didier Fouarge, Director of the Research Centre for Education and the Labour Market at Maastricht University, and Cornelia Suta, Principal Consultant at Cambridge Econometrics, are asked about the Technequality Horizon 2020 project they are working on and how this project will help understand the complexities of labour in the age of automation.
1 Tell us a little bit about Technequality, and your particular involvement?
Fouarge: The aim of Technequality is to understand the impact of technological development and automation on society and education.
There are six projects or ‘work packages’ that sit beneath Technequality. I am research leader for Work Package 1, ‘The future of work in Europe’, which seeks to identify the jobs and new skills we might need to learn in the age of automation. Can we quantity and qualify the impact of automation and inform social policies which are needed to accommodate? What skills will be needed in the light of automation? These are the sort of questions we have been asking and seeking to quantify.
Suta: Since May 2020 I have been leading the work on behalf of Cambridge Econometrics for Technequality. Cambridge Econometrics was involved in Work Package 1, looking at the scenario based on the Cedefop Skills forecast data set. We quantified scenarios in collaboration with ROA. We are also contributing to another work package.
One aspect of automation involves tasks being done by robots instead of people which, for example, is already happening in car manufacturing. Another aspect of automation involves how robots can help humans in dealing with the production of goods and services. With AI and robotics, humans might all together become redundant in production processes involving manual labour. Smart and intelligent processes might even take over human occupations/thinking.
2 Can you expand a bit more about scenarios and why they are important?
Suta: Sure. In essence, a scenario is a pathway to the future. When it comes to the potential impact of automation, we face many uncertainties. We need scenarios to help us understand what can happen if we make different assumptions on the future. They help us address questions like what will happen if much of my job can be automatable? What impact will policy have on the adoption of these technologies? To understand and quantify the impact of uncertainty, we compare a business-as-usual scenario, where current trends continue in the future, with alternative scenarios that assume slight alterations in the future trends.
For example, by setting scenarios that look at faster or slower adoption of AI and quantifying the impact of such adoption on jobs and skills in the EU using our macroeconomic modelling, we can contribute towards more informed and targeted policy development.
Scenario results can help plan and build resilience against any unforeseen market forces that enable a transition to adoption of automation that keeps the labour market steady without too many hits along the way.
3 How do you think Technequality will benefit future policy development?
Fouarge: The hope is that through our work in this H2020 project we can put concrete numbers on what we expect the impact of automation to be on job losses including potential risks in industry and any skill development.
This in turn can help inform the policy makers manage a just transition in a targeted and effective way.
Our 22 scenarios can help policy makers identify the impact of policy interventions that affect the speed of adoption of new technologies, and how this would affect certain worker profiles in different industries and occupations. Policy can help manage the pace of automation take-up.
Everything differs across sectors. To remain competitive you need to move with the technology. Some sectors might be fast movers and adopters of automation because of competition. There might be differences in adoption across sectors because of the competition.
Our calculations are informative to industry and policy-makers, because we formulate the assumptions we make in the scenarios in an explicit way. We have generated a webtool that stakeholders can use to visualize the quantitative impact of automation in the scenarios we designed.
4 In what ways do you think the adoption of automation and the labour market will be affected by Covid-19 pandemic?
Fouarge: We know that a number of jobs have been under pressure of risk of automation. Covid has increased and accelerated the trends. For some jobs, the number of published vacancies are recovering but not for all. There is evidence in the decline of vacancies is sharper for administrative jobs, which we know are more likely prone to automation. This could be a possible negative trend that accelerates automation.
Suta: Two trends are caused by Covid:
- Social distancing has a major impact on what kind of technology we might adopt, by increasing the speed of adoption (e.g. robots do not need social distancing). Industries face different challenges related to social distancing, leading to the uptake of robotisation; perhaps even earlier than anticipated if the pandemic hadn’t happened.
- Digitalisation increased due to Covid because we are relying a lot more on digital products such as e-commerce and technology enabling remote working.
There is also a case of existing trends experiencing an acceleration such as the automatisation of the service sector. Previously, human interaction in the service sector was not threatened by automation, but Covid has placed a lot more pressure to adopt new technologies that favour virtual interaction. This has also placed more pressure on industries to remain competitive. In other cases, it brought the creation of new tech such as sanitiser spray sensors.
5 What do you think are the major trends for the next decade on automation for Europe’s labour market?
Fouarge: As Europe gradually takes a path towards covid recovery, the future of work is on everyone’s mind. How much of the labour force will work from home? How will workers be managed in an era where social distancing might remain? One of the more negative impacts that might stay for the next decade is less opportunity to learn informally from one another due to less meetings in person. However, a change in working behaviour also leads to more digital skill uptake.
Suta: Ageing is a significant trend for the next decade. If certain industries have more people retiring than joining, then automation will be adopted sooner. This will lead to less transfer of knowledge from older generations to the newer generations, and less inter-generational workplaces. The ageing workforce with less digital skills and the uptake of automation could even cause structural changes in some industries.