White Paper

Automation is of increasing importance to society, reflecting that the job market is changing composition. This article describes the methodology used by the Office for National Statistics (ONS) for producing estimates of the probability of automation for 2011 and 2017. We describe previous studies that have examined the impact of automation, before outlining the ONS approach. We present analysis of the probability of automation by demographic variables and highlight the skills and tasks that are at risk of automation within jobs.

Canada’s income inequality is quite similar to the UK’s, so we should focus on rising incomes and declining inequality, two sides of inclusive growth.

Digital identification, or “digital ID,” can be authenticated unambiguously through a digital channel, unlocking access to banking, government benefits, education, and many other critical services. Programs employing this relatively new technology have had mixed success to date—many have failed to attain even modest levels of usage, while a few have achieved large-scale implementation. Yet well-designed digital ID not only enables civic and social empowerment, but also makes possible real and inclusive economic gains—a less well understood aspect of the technology. The political risks and benefits of digital ID are potentially significant and deserve careful attention but are beyond the scope of this report. Here, we develop a framework to understand the potential economic impact of digital ID, informed by an analysis of nearly 100 ways in which digital ID can be used in Brazil, China, Ethiopia, India, Nigeria, the United Kingdom, and the United States.

Robotics and machine learning have improved productivity and enhanced the economies of many nations. Artificial intelligence (AI) has advanced into finance, transportation, defense, and energy management. The internet of things (IoT) is facilitated by high-speed networks and remote sensors to connect people and businesses. Yet amid these possible benefits, there is widespread fear that robots and AI will take jobs and throw millions of people into poverty.

[R]obots, artificial intelligence, computerized algorithms, mobile sensors, 3-D printing, and unmanned vehicles are here and transforming human life. People can decry these developments and worry about their “dehumanizing impact,” but we need to determine how emerging technologies are affecting employment and public policy.

The report, Postsecondary Education Metrics for the 21st Century, argues that it’s time to take a fresh look at how to best evaluate the performance of the province’s postsecondary system. It suggests that performance metrics be closely tied to government policy, focused on impact and outcomes rather than inputs, based on the best available data and motivated by a desire for improvement rather than accountability.

To prepare students for the future labour market, post-secondary institutions must improve the way they teach, measure and credential skills.

One of the first major attempts to measure employment-related skills in university and college students on a large scale shows that students are experiencing some gains in literacy, numeracy and critical-thinking scores over the course of their undergraduate studies. Yet, one in four graduating students scored below adequate in measures of literacy or numeracy, and less than a third scored at superior levels, according to findings by the Higher Education Quality Council of Ontario (HEQCO). HEQCO completed two large-scale trials involving more than 7,500 students at 20 Ontario universities and colleges to measure literacy, numeracy and critical-thinking skills in entering and graduating students. The results of the trials are contained in this report

Community capital provides a powerful opportunity for improving health and health equity in the GTA through networks and relationships at the inter-organizational and intersectoral level. Inter-organizational networks and community hub models help connect social services as widespread as community centres, settlement agencies, government services, cultural associations, employment services, educational systems and health care. Creating stronger connections between services has been shown to improve health, and social and economic outcomes for communities (Wood Green Community Services 2015). For example, in one Toronto initiative between schools and health care, providers worked together to close gaps in access to health care in low-income communities, improving both health and educational outcomes for young students (Yau and DeJesus 2016). Despite widespread agreement on the value of inter-organizational networks, such networks are often difficult to establish and maintain, and subsequently fail to meet people’s optimistic expectations (Weiner and Alexander 1998). The reason may be that we lack a practical understanding of how networks operate and how they might be strengthened to serve different community needs.