Executive Summary

Technological development is central to long-term economic growth and prosperity. In the past two decades, one particular form of technology has captured the attention of researchers as well as policy-makers: digital technology. Digital technology has created new methods for commerce to take place, from the introduction of new and more efficient modes of communication to entire digital platforms where buyers and sellers can interact. These changes mean that theoretical models and empirical measurements designed during and for the pre-digital era to understand economic dynamics fail to fully capture economic activities that happen digitally, obfuscating our ability to understand their broader impact.

One particular area where such considerations are needed is in how digital technology affects workers and labour. A number of conceptual problems present themselves, from estimating the value of a particular digital technology asset (especially concerning assets that are intangible, such as software, which is costless to replicate once produced) to challenges in delineating cases where digital technology complements workers and where it replaces workers.

As Canada and the rest of the world emerge from the COVID-19 pandemic, many workers have had to reconcile the dramatic impact of the pandemic on the way they work, as almost one in three workers in Canada worked most of their hours from home in 2020 (Mehdi & Morissette, 2021). Such changes were also felt by businesses, where one in 10 recorded half or more of their total sales online in 2020, an increase of almost 50% from 2019 (Statistics Canada, 2021). Such drastic changes also necessitated national statistical agencies to amend data collection methods to provide actionable insights for policy. As a result, Statistics Canada, introduced the Canadian Survey on Business Conditions, the Canadian Perspectives Survey Series, as well as introduced new measures into the Labour Force Survey and increased the frequency by which the Jobs Vacancy and Wages Surveys are released (monthly from quarterly). In Canada, this also meant that the way the 2021 census data collection was done was affected (Statistics Canada, 2020).

Now, more than ever, we need an approach to understand digital technology’s impact on work and labour to capture the full range of economic activities that have and will take place. Through this knowledge synthesis, we will systematically review the conceptual ways in which technologies have been understood to impact economic processes, focusing especially on efforts and advancements made in the recent decade on how digital technologies impact work, labour, and the broader economy.

As this report lays out in detail, the way researchers have approached an understanding of technology and its impact on growth and development has evolved considerably in the past two decades, befitting the exponential growth of technology itself. The digital era, defined in large part by the proliferation of the personal computer and advances in computing power, has not only altered the structure of the economy but also significantly impacted the way we work and, subsequently, the methods employed to understand that change.

Long-run perspectives on why technological change and development is important to economic growth is not new, but the debate between exogenous and endogenous growth theories point to the growing sophistication of the discourse and the attention given to problems of job polarization and other inequities, such as gender-based and geographic disparities.

As focus shifted to endogenous growth theories, a new wave of research began to further explore and understand the uneven effects, tangent to explicit concerns with economic growth, that technological change has on labour, giving rise to theoretical frameworks to explain why some workers have not benefited (in the short run) from digital technology. This has led to the development of the theory of skill-biased technical change — or technological change that those who are “skilled” can fully take advantage of, while those who are not “skilled” lose out.

While the new skill-biased literature makes it clear that some “low-skilled” workers are losing out, this discourse left certain puzzles unanswered, such as the fact that despite what appeared to be clear gains going to technically trained and highly skilled workers, post-secondary students were not moving unidirectionally toward such training and occupations. From here, we see the rise of task-based approaches to understanding different types of skills (cognitive and manual) and specific tasks, be they routine (more open to automation) or nonroutine (less open to automation). Herein we see the crucial contention that some types of labour (namely those defined by cognitive and nonroutine tasks) are more clearly complemented by technological change (and automation) rather than replaced by it.

Although there have been great strides made in advancing and defining consistent and useful taxonomies and frameworks for types of skills and specific tasks, it is clear that the enormous variety of possible tasks makes measurement extremely difficult and thus data even harder to generate. Without this data scholars will struggle to conduct adequate research, and policy-makers will lack evidence to inform desirable policy objectives and their appropriate instruments.

This knowledge synthesis explores the discourse and literature on the digital economy, focusing on how we have come to know what we do about technology’s impact on labour and the economy more broadly. Importantly, this report does not focus specifically on the findings of the research per se, although there is ample attention given to research findings, but rather attention is paid to the approaches, frameworks, and specific measurements devised to help conceptualize and ultimately measure the impact of technology, with specific attention to the ways technology either replaces labour or augments it.