Canada is facing a quiet crisis. In the coming decade, half of all jobs will be disrupted by technology and automation. Some will change dramatically. Others will disappear completely, replaced by jobs that are yet to be invented. We are living through an era of radical change, with the latest advancements in artificial intelligence and automation transforming the way we work, even in unexpected fields such as law and customer service. How will we prepare Canadian youth for the workplace of the future? Over the past year, RBC conducted a major study of the Canadian workforce. We crisscrossed the country, talked to students, workers, educators and employers in every sector. We studied job openings and automation trends and dug into mountains of data to figure out how the country is changing and what we can do to prepare.

The commonly used figure to describe the gender wage ratio—that a woman earns 80 cents for every dollar earned by a man—understates the pay inequality problem by leaving many women workers out of the picture. This report argues that a multi-year analysis provides a more comprehensive picture of the gender wage gap and presents a more accurate measure of the income women actually bring home to support themselves and their families.

The Collaborative Economy is approaching thanks to advances in technologies related to Collaborative Internet, Big/Open Data, Crypto Currency and Additive Manufacturing. Policy makers wish to be prepared and understand their options in order that effective policies can be put in place in time to nurture the positive impacts and negate the negative impacts associated within range of potential afforded by this advance. The results of a short Delphi-inspired study reveal a wide range of opportunities and threats associated with the technologies supporting the Collaborative Economy. In the wider context, attention is drawn to a number of social, political, economic, moral and ethical issues also associated with the migration into this new way of working. Importantly, the impacts of the Collaborative Economy are not restricted to the conventional workplace, where economic activity currently takes place. In the Collaborative Economy, impacts are felt not only at home but also on the person, indeed the effects are felt everywhere. In conclusion, a number of policy options are presented for the consideration of policy makers.

This report is a follow-up to the CCC-sponsored roadmap that was published in May 2009 and presented to the Congressional Caucus on Robotics on May 21, 2009. That roadmap subsequently led to the creation of the National Robotics Initiative (NRI), which is jointly sponsored by NSF, USDA, NASA, and NIH. The NRI was launched in 2011. The present roadmap is an update to the former document in the areas of manufacturing, healthcare/medical, and service robotics. In recognition of the important role that space, and defense robotics has both to R&D but also as early adopters, new chapters were added for those areas. These new sections should primarily be seen as identifying areas with dual and multiple-use potential for multi-domain coordination. As such, the space and defense sections are complementary to independent roadmaps developed by agencies within those domains. The update of the roadmap has been organized by the Robotics Virtual Organization.

Automation will produce significant productivity gains that will reshape specific sectors and occupations. These gains are likely to be recirculated, with jobs reallocated rather than eliminated, economic output increased, and new sources of wealth created. The problem is likely to be one of how income and wealth are distributed. Automation could create a ‘paradox of plenty’: society would be far richer in aggregate, but, for many individuals and communities, technological change could reinforce inequalities of power and reward. These changes may well affect men and women differently, because men and women tend to have different jobs in the UK labour market. Our analysis shows that twice as many women as men work in occupations with a high potential for automation (9 per cent compared to 4 per cent of men), and that 64 per cent of jobs in these occupations are held by women. Migrants, and lone parents (typically women) are more likely to hold jobs with high automation potential. But technology is not destiny. This paper argues that automation presents an opportunity to narrow gender inequalities and sets out four propositions for change based on this premise.

Improving economic growth is a key policy objective for the Government. Therefore, understanding the drivers of productivity growth is a fundamental requirement for effective economic policy. Current measurements of productivity, based on the ‘tangible’ inputs of capital and labour, do not fully account for variations in performance. As a result of this there is a growing interest in ‘intangible’ assets and their potential to help us to better understand the sources of growth. Intangible assets are typically grouped into three main categories. • Economic Competences - such as brand equity which would include advertising and marketing expenditures. This category includes firm specific resources, including human capital (investments in training) and organisational structure (management). • Innovative Property - this includes both scientific R&D and non-scientific R&D. Non-scientific R&D includes research in social sciences and humanities, mineral exploration, new motion picture films and other forms of entertainment, new architectural and engineering design and new product development in financial industries. • Digitised information - this is often measured as IT capital, composed of software as well as databases. Existing studies at the macro level suggest intangible assets make a significant contribution to productivity growth and micro level studies suggest intangible assets help to explain difference in performance between firms. Because intangible assets are embedded in knowledge workers, and as such are difficult to disentangle from firms’ human capital, this research develops measures of intangible assets for UK firms based on the labour input of workers in high skilled organisation, R&D and IT related occupations. These measures are then used to assess how firms employ intangible assets to increase productivity and raise economic performance. The aims of this research are to explore: • the number and cost of intangible workers as a proportion of the overall workforce across a range of sectors; • the relationship between intangible assets and performance; and • the contribution of intangible assets to growth.

This guide is a part of the European Training Foundation (ETF), ILO and the European Centre for the Development of Vocational Training (Cedefop) series of guides on skills anticipation and matching. The main goal of this guide is to provide guidance through labour market monitoring and analyses of skills supply and demand. It is an introductory tool for everyone who wants to understand how labour market information (LMI) can be used for better anticipation and matching of skills demand and supply. It provides advice and recommendations for policy- and decision-makers on how to respond to market signals and how to react to early warning messages driven by LMI. Technical analysts and professionals can use this guide as a source of inspiration on how LMI systems can be further developed and used for policy analyses and interventions.

I build a model in which structural change creates a mismatch between the skill requirements in the available jobs and workers’ current skills. When the mismatch is severe, labor markets go through a prolonged adjustment process wherein job creation is low, and unemployment is high. Due to matching frictions, firms find it harder to locate workers with the requisite skills for novel jobs and they respond by creating fewer jobs. The paucity of novel jobs increases unemployment for all workers—including those who already hold the requisite skills—and discourages skill acquisition by workers. Moreover, structural change interacts with the business cycle, causing a large and long-lasting increase in unemployment that concentrates in recessions. I demonstrate that the decline in routine-cognitive jobs outside manufacturing—a pervasive structural change that has affected U.S. labor markets since the late 90s—created a skill mismatch that contributed to the long-lasting increase in unemployment observed during the Great Recession. My evidence suggests that the amplification effects introduced by matching frictions are important. Moreover, I find that the skill mismatch has a larger effect during recessions and in labor markets where the demand for goods and services is depressed.

Workforce agility is defined as the ability of employees and organizations to remain steadfast and maintain productivity in the face of change. When we refer to a flexible workforce, we’re talking about a staffing model that features non-traditional workers*. Such a model allows an organization to hire on an as-needed/on-demand, temporary basis to fulfill short- or long-term contracts that fill skills gaps. These are not the ‘temps’ of the past; instead, they range from blue collar, light industrial to highly skilled IT, engineering, accounting and HR professionals. The specifics of how organizations apply the definition depends on their industry. As a result, there are many ways to be a non-permanent employee.