White Paper

This report analyzes key drivers that will reshape the landscape of work and identifies key work skills needed in the next 10 years. It does not consider what will be the jobs of the future. Many studies have tried to predict specific job categories and labor requirements. Consistently over the years, however, it has been shown that such predictions are difficult and many of the past predictions have been proven wrong. Rather than focusing on future jobs, this report looks at future work skills-proficiencies and abilities required across different jobs and work settings.

Among Canadians aged 15 to 64, Internet access reached near-saturation levels in 2016, but its diffusion into the senior population was far less extensive. This study uses four cycles of the General Social Survey (2007, 2010, 2013 and 2016) to describe changes in Canadian seniors’ rates of Internet use, and examines the sociodemographic factors associated with such use. The findings suggest that age is the primary determinant of Internet use among seniors, but that differences in educational attainment and other demographic characteristics are also important. From 2007 to 2016, Internet use doubled from 32% to 68% among Canadians aged 65 and older. During this time, the absolute gap in the prevalence of Internet use between seniors and Canadians aged 45 to 54 declined from 49 to 28 percentage points. Within the senior population, Internet use progressively declined at older ages. Current age differences in Internet use likely correspond with the comparatively limited exposure of Canadian seniors to the Internet via their social networks, as well as differences in educational attainment and other characteristics correlated with Internet use. This suggests that the slow diffusion of Internet use in the senior population was rooted in historical circumstances more so than reflecting the aging process. Given the comparatively high rates of Internet use among middle-aged Canadians (aged 45 to 54) and younger seniors, it is anticipated that age gaps in Internet use will continue to decrease.

Cognitive technologies and business process reengineering could be a match made in heaven, but only if organisations do the work to redesign their processes with cognitive technologies' specific capabilities in mind. New automation and cognitive technologies present a unique opportunity to redesign knowledge-based work, but they likely will not do so without a concerted effort to redesign work processes around their capabilities. In order to achieve the productivity and effectiveness benefits that these technologies offer, companies may need to adopt, or readopt, techniques from a variety of systematic approaches to process improvement and change. Key Take-outs: While other approaches to organizational structure—primarily including business functions such as marketing, finance, and supply chain—may be more familiar, business processes can bring a powerful perspective on monitoring and improving work. Process thinking is at the core of not only business process reengineering, but also Total Quality Management, Six Sigma, and Lean.

The digital and creative sector is an important part of the UK economy. It encompasses a wide range of activities, including telecommunications; computer programming and consultancy; publishing; films and music; programming and broadcasting; design and photography; and creative arts and entertainment. This report covers the digital and creative sector across all four nations of the UK.

We study the impact of rising robot exposure on the careers of individual manufacturing workers, and the equilibrium impact across industries and local labor markets in Germany. We find no evidence that robots cause total job losses, but they do affect the composition of aggregate employment. Every robot destroys two manufacturing jobs. This accounts for almost 23% of the overall decline of manufacturing employment in Germany over the period 1994–2014, roughly 275,000 jobs. But this loss was fully offset by additional jobs in the service sector. Moreover, robots have not raised the displacement risk for incumbent manufacturing workers. Quite in contrast, more robot exposed workers are even more likely to remain employed in their original workplace, though not necessarily performing the same tasks, and the aggregate manufacturing decline is solely driven by fewer new jobs for young labor market entrants. This enhanced job stability for insiders comes at the cost of lower wages. The negative impact of robots on individual earnings arises mainly for medium-skilled workers in machine operating occupations, while high-skilled managers gain. In the aggregate, robots raise labor productivity but not wages. Thereby they contribute to the decline of the labor income share.

The first question posed by Delphi concerned the extremely controversial extent of unemployment feared or expected from technological transformation. Nearly unanimously, and independent of the age of respondents or from which region they came, the experts anticipated a globally rising unemployment rate on average from today’s circa 6 percent (Allen 2015) to 11 percent in 2020, with a continual rise up to 24 percent by 2050. 12 2050: THE FUTURE OF WORK. However, it is important to remember that the above figures are all averages of the responses. Some respondents expect an unemployment rate of up to 50 percent by 2050 or even a state of “nearly total unemployment”. Equally, the more experience respondents have with forecasting, the higher their estimates are pitched. The expectations of the less experienced experts as to the extent of the anticipated unemployment rate were on average 21 percent while the more experienced among them levelled out at 27 percent. By the same token, those experts with more competence in the fields of artificial intelligence and technology development also made higher estimates (for example, respondents with greater expertise estimated the global unemployment rate at 14, not 11, percent by 2020). In other words, the more respondents knew about predicting the future and the evolution of technology, the larger their estimates of expected unemployment were.

Autonomous vehicles (AVs) are set to be the next major technological breakthrough of the 21st century. The AV industry in Canada will create 34,700 new jobs between 2017 and 2021. However, Canada lags behind major automobile manufacturing countries such as the US, Japan, and Germany. The extent to which Canada can harness the positive impacts on employment in high-tech sectors from autonomous vehicles (e.g., automotive engineering, ICT in general) will depend crucially on the role Canada plays in the development of this new technology. Furthermore, the adoption of autonomous vehicle technology will generate new opportunities for inclusivity and economic participation for underrepresented groups — such as individuals with disabilities, Indigenous peoples, and people living in rural or remote areas — as long-distance travel becomes more manageable. AV adoption will also require a comprehensive retrofitting of our road infrastructure and changes to our traffic laws. Such changes will boost demand for civil engineers, urban and land use planners, consultants, and policy analysts. On the other side of the ledger, most driving jobs will be phased out as the technology improves. How fast this will happen depends on how efficiently various driving occupations can be automated. Although drivers make up only 0.5% of the Canadian labour force, they have, on average, the lowest level of education among workers affected by AV technology. Supporting these workers through a difficult period of transition should therefore be a social and economic priority. In addition to drivers, mechanics and other workers will need re-training, either to adapt to the changing skill demand of their occupation or to transition into other fields.

The focus of this project was to review the existing English and French language literature, both Canadian and International, which address the following themes: Definitions of specific digital skills, including their similarities and differences; Benchmarks used to assess digital skills; Strategies related to information and communications technology (ICT) and digital economy skills, including operative definitions, components, and evaluations (if any); Taxonomies of stakeholders as well as initiatives documented to promote digital skills, including goals, tactics, and impacts; and, Potential models that may serve as a basis for further consultation with relevant stakeholders.