Training and education for the unemployed has a long tradition in Denmark and especially came into focus with the labour market reforms in the early 1990s. During the last decade the use of training and education however became subject to criticism. Higher priority was given to programmes that were more job-targeted like training counselling, traineeships and wage-subsidies. The main reason for this policy shift was the rising demand for labour and the low unemployment in the years preceding the present economic crisis. Also, evaluation studies generally found limited and often even negative effects of educational programmes.

In the seminal study, Frey & Osborne reported that 47% of the total employment in the United States is at risk of computerization. Many studies estimate how automation of work influences employment. In Japan, however, there are few studies which investigate the effect of automation and networking on future employment. It is important to discuss this based on facts and evidence. This paper describes the present situation in Japan on the impact of artificial intelligence (AI) on employment, utilizing a survey study. We first visited Japanese companies and conducted a field survey on the new technologies being introduced. Following this, in August 2017, we conducted a survey study of about 10,000 companies. This paper discusses the output of the survey study

The 2000s ushered in significant demographic and economic changes that have redrawn the map of economic opportunity in metropolitan America. Two economic downturns and the weak recoveries that followed left the nation with fewer jobs in 2010 than in 2000. As jobs declined, they continued to push farther outward within the nation’s largest metro areas. Almost every major metro area saw jobs shift away from the urban core during the 2000s.1 As jobs suburbanized, so did people. Minorities and the poor suburbanized at the fastest pace, such that, by 2010 in the nation’s largest metro areas, the majority of every major ethnic and racial group and the majority of the poor lived in suburbs for the first time.2 Where people and jobs locate within metro areas over time affects how close they are to one another. The outward shift of both people and jobs in the 2000s changed their proximity to each other, and often not for the better. This study takes a new approach to determine how many jobs people live near, or what we term job proximity, throughout the United States. Proximity can influence a range of outcomes, from the fiscal health of a community to employment opportunities for residents. Differences across people and places in job proximity, and trends over time, illustrate how economic and demographic shifts in the 2000s reshaped the map of economic opportunity for different communities and populations.

Three and a half years after the Great Recession officially ended, unemployment in the United States remains stubbornly high. Yet many employers still struggle to fill certain types of vacancies, especially for so-called middle-skills jobs—in computer technology, nursing, high-skill manufacturing, and other fields—that require postsecondary technical education and training and, in some cases, college math courses or degrees. Currently in the U.S. about 69 million people work in middle-skills jobs, representing roughly 48% of the labor force.

Blue collar immigrant Latinos have increasingly gained employment within North Carolina's growing meatpacking industry and declining textile industry from 1980 to 2000. This paper uses three decades of Census data to provide a theoretically descriptive discussion about trends and patterns that have emerged within these industries. Results indicate that in meatpacking, Latinos are being crowded into low wage ghettos, despite cases where they are substituting for exiting white workers or where they have been queued upward into better paying jobs. In textiles, Latinos gained employment because they are inexpensive labor or because they are substituting for whites and slowing growth among blacks. Within narrow occupational categories, interpretations of growing Latino presence were consistent from macro to micro levels while in other cases crowding in meatpacking and wage discrimination in textiles were not foreshadowed. Overall, Latinos appear to be affecting employment rates of whites more than blacks in both industries.

Anticipating and preparing for the impact of digital on the workforce is urgent, and just as critical to Accenture’s business as it is to our corporate citizenship initiative, Skills to Succeed. When we look at the world today and five to 10 years into the future, we see a different picture from the backdrop against which Skills to Succeed was created. The rapid pace and scale of technological change and global flows of information, among other forces, are disrupting labor markets and fundamentally altering the future of work. While these shifts may create economic growth, new jobs and flexible work, they may also lead to the automation of routine, manual roles. The ability to seize these opportunities and manage potential obstacles, however, is not evenly distributed.1 Vulnerable and marginalized populations could face a ‘double disadvantage’ in the future, due to a lack of awareness of or means to adapt to these changes. It is with these challenges in mind that we undertook our research, New Skills Now: Inclusion in the Digital Economy, to surface insights that we hope will be useful to our target audience.

Social democratic capitalism helps countries achieve economic security and equality of opportunity and can be replicated by other rich democratic nations.

There is a lot we don't know about what automation will mean for jobs in the future, including its impact (if any) on gender inequality. This note reviews evidence and forecasts on that question and makes four main points: (1) past automation has been (broadly) positive for women's average quality of life, economic empowerment, and equality; (2) forecasts of the gendered impact of automation and AI going forward based on the current distribution of employment suggest considerable uncertainty and a gender inequality of impact that is marginal compared to the potential impact overall; (3) the bigger risk---and/or opportunity---is likely to be in the combined impact of automation, policy, and social norms in changing the type of work that is seen as male or female; and (4) minimizing any potential aggravating impact of automation and AI on inequalities in economic power in the future can best be achieved by maximizing economic equality today.

The "future of work" is an evolving concept with wide-reaching implications for the economy, workforce, education, and society--including workers, business owners, students, and the people who serve them. The impact from these changes brings a sense of urgency to stay a few steps ahead and address systems' gaps and faulty machinery that threaten to put low-income workers and students at a disadvantage. This brief will provide an overview on the changing nature of employment relationships that have implications for low-wage workers. It will also feature recommendations to help education and workforce development practitioners and policymakers address the demands of the future economy, including recommendations for new approaches to business engagement.