Many previous waves of technological change have shifted what skills are demanded in the labour market, making some jobs obsolete while creating new ones. But the current wave of change may be the most rapid and unpredictable in history. How to prepare people to earn a livelihood in the digital age – and how to protect those struggling to do so – is a critical question for digital cooperation for governments and other stakeholders who aim to reduce inequality and achieve the SDGs.

At this stage, there appears to be limited value in attempting to predict whether robots and artificial intelligence will create more jobs than they eliminate, although technology historically has been a net job creator.68 Many studies attempt to predict the impact on the jobs market but there is far from being a consensus.69 The only certainty is that workers have entered a period of vast and growing uncertainty – and that this necessitates new mechanisms of cooperation.


Modern schools were developed in response to the industrial revolution, and they may ultimately need fundamental reform to be fit for the digital age – but it is currently difficult to see more than the broad contours of the changes that are likely to be needed.

Countries are still in early stages of learning how to use digital tools in education and how to prepare students for digital economies and societies. These will be ongoing challenges for governments and other stakeholders. Some countries are now exposing even very young children to science and robotics. Alongside such broader digital literacy efforts, it may be even more important to focus from an early age on developing children’s “soft skills”, such as social and emotional intelligence, creativity, collaboration and critical thinking. One widely referenced study concludes that occupations requiring such soft skills are less likely to be automated.70

Teaching about specific technologies should always be based on strong foundational knowledge in science and math, as this is less likely to become obsolete. At a degree level, science, technology, engineering and mathematics (STEM) curricula need to borrow from the humanities and social sciences, and vice versa: STEM students need to be encouraged to think about the ethical and social implications of their disciplines, while humanities and social science students need a basic understanding of data science.71 More informal approaches to learning may be needed to prepare students for working in cross-disciplinary teams, and where such informal approaches already exist in the developing world they should be fully appreciated for their value.

As the boundaries increasingly blur between ‘work’ and ‘learning’, the need to enable and incentivise lifelong learning was emphasised in many of the written contributions the Panel received.

Lifelong learning should be affordable, portable and accessible to all. Responsibility for lifelong learning should be shared between workers themselves, governments, education institutions, the informal sector and industry: digital cooperation mechanisms should bring these groups together for regular debates on what skills are required and how training can be delivered. Workers should have flexibility to explore how best to opt into or design their own approach to lifelong learning.

There are emerging examples of government efforts to use social security systems and public-private partnerships to incentivise and empower workers to learn new skills and plan for a changing labour market. Among those drawn to the Panel’s attention were efforts by the International Trade Union Confederation in Ghana and Rwanda,72 France’s Compte Personnel de Formation, Scotland’s Individual Training Account, Finland’s transformation of work and the labour market sub-group under its national AI programme, and Singapore’s Skills Framework for Information and Communication Technology (ICT).

However, reskilling cannot be the only answer to inequality in the labour market – especially as the workers most able to learn new skills will be those who start with the advantage of comparatively higher levels of education.73


New business models are fuelling the rise of an informal or “gig” economy, in which workers typically have flexibility but not job or income security.74 In industrialised countries, as more and more people work unpredictable hours as freelancers, independent contractors, agency workers or workers on internet platforms, there is an urgent need to rethink labour codes developed decades ago when factory jobs were the norm.75

Promising initiatives include Germany’s Crowdsourcing Code of Conduct, which sets out guidelines on fair payment, reasonable timing and data protection for internet platform workers, and employs an ombudsman to mediate disputes; and Belgium’s Titre-Services and France’s Chèque Emploi Service Universel, which offer tax incentives for people engaging casual workers to participate in a voucher scheme that enables the workers to qualify for formal labour rights. There are also examples of digital technologies enabling new ways for workers to engage in collective bargaining.76

While the gig economy tends to make work less formal in industrialised countries, in the developing world the majority of people have long worked in the informal sector.77 For these workers, gig economy arrangements may be more formal and transparent, and – with appropriate cooperation measures with technology firms – easier for governments to oversee.78 The challenge, as with industrialised countries, is to uphold labour rights while still allowing flexibility and innovation.

In all national contexts, protecting workers and promoting job creation in the digital age will require smart regulations and investments, and policies on taxation and social protection policies which support workers as they seek to transition to new opportunities.

Next: 2.3 Regional and global economic policy cooperation

Source: https://comment.eurodig.org/digital-cooperation-report/2-2-rethinking-how-we-work-and-learn/