Mapping Career Causeways

User Guide by Nesta: “This user guide shows how providers of careers information advice and guidance, policymakers and employers can use our innovative data tools to support workers and job seekers as they navigate the labour market.

Nesta’s Mapping Career Causeways project, supported by J.P. Morgan as part of their New Skills at Work initiative, applies state-of-the-art data science methods to create an algorithm that recommends job transitions and retraining to workers, with a focus on supporting those at high risk of automation. The algorithm works by measuring the similarity between over 1,600 jobs, displayed in our interactive ‘map of occupations’, based on the skills and tasks that make up each role.

Following the publication of the Mapping Career Causeways reportdata visualisation and open-source algorithm and codebase, we have developed a short user guide that demonstrates how you can take the insights and learnings from the Mapping Career Causeways project and implement them directly into your work….

The user guide shows how the Mapping Career Causeways research can be used to address common challenges identified by the stakeholders, such as:

  • Navigating the labour market can be overwhelming, and there is a need for a reliable source of insights (e.g. a tool) that helps to broaden a worker’s potential career opportunities whilst providing focused recommendations on the most valuable skills to invest in
  • There is no standardised data or a common ‘skills language’ to support career advice and guidance
  • There is a lack of understanding and clear data about which sectors are most at risk of automation, and which skills are most valuable for workers to invest in, in order to unlock lower-risk jobs
  • Most recruitment and transition practices rely heavily on relevant domain/sector experience and a worker’s contacts (i.e. who you know), and most employers do not take a skills-based approach to hiring
  • Fear, confidence and self esteem are significant barriers for workers to changing careers, in addition to barriers relating to time and finance
  • Localised information on training options, support for job seekers and live job opportunities would further enrich the model
  • Automation is just one of many trends that are changing the make-up and availability of jobs; other considerations such as digitalisation, the green transition, and regional factors must also be considered…(More)”.

Unlocking Responsible Access to Data to Increase Equity and Economic Mobility

Report by the Markle Foundation and the Bill and Melinda Gates Foundation (BMGF): “Economic mobility remains elusive for far too many Americans and has been declining for several decades. A person born in 1980 is 50% less likely to earn more than their parents than a person born in 1950 is. While all children who grow up in low-opportunity neighborhoods face mobility challenges, racial, ethnic, and gender disparities add even more complexity. In 99% of neighborhoods in America, Black boys earn less, and are more likely to fall into poverty, than white boys, even when they grow up on the same block, attend the same schools, and have the same family income. In 2016, a Pew Research study found that the median wealth of white households was ten times the median wealth of Black households and eight times that of Hispanic households. The COVID-19 pandemic has further exacerbated existing disparities, as communities of color suffer higher exposure and death rates, along with greater job loss and increased food and housing insecurity.

Reversing this overall decline to address the persistent racial, ethnic, and gender gaps in economic mobility is one of the great challenges of our time. Some progress has been made in identifying the causes and potential solutions to declining mobility, yet policymakers, researchers, and the public still lack access to critical data necessary to understand which policies, programs, interventions, and investments are most effective at creating opportunity for students and workers, particularly those struggling with intergenerational poverty. Data collected across all levels of governments, nonprofit organizations, and private sector companies can help answer foundational policy and research questions on what drives economic mobility. There are promising efforts underway to improve government data infrastructure and processes at both the federal and state levels, but critical data often remains siloed, and legitimate concerns about privacy and civil liberties can make data difficult to share. Often, data on vulnerable populations most in need of services is of poor quality or is not collected at all.

To tackle this challenge, the Bill and Melinda Gates Foundation (BMGF) and the Markle Foundation (Markle) spent much of 2020 working with a diverse range of experts to identify strategic opportunities to accelerate progress towards unlocking data to improve policymaking, answer foundational research questions, and ensure that individuals can easily and responsibly access the information they need to make informed decisions in a rapidly changing environment….(More)”.

Collaboration technology has been invaluable during the pandemic

TechRepublic: “The pandemic forced the enterprise to quickly pivot from familiar business practices and develop ways to successfully function while keeping employees safe. A new report from Zoom, The Impact of Video Communications During COVID-19, was released Thursday.

“Video communications were suddenly our lifeline to society, enabling us to continue work and school in a digital environment,” said Brendan Ittelson, chief technology officer of Zoomon the company’s blog. “Any baby steps toward digital transformation suddenly had to become leaps and bounds, with people reimagining their entire day-to-day practically overnight.”

Zoom commissioned the Boston Consulting Group (BCG) to conduct a survey and economic analysis to evaluate the economic impact of remote work and video communications solutions during the pandemic. BCG also conducted a survey and economic analysis, with a focus on which industries pivoted business processes using video conferencing, resulting in business continuity and even growth during a time of significant economic turmoil.

Key findings

  • In the U.S., the ability to work remotely saved 2.28 million jobs up to three times as many employees worked remotely, with a nearly three times increase in the use of video conferencing solutions.
  • Of the businesses surveyed, the total time spent on video conferencing solutions increased by as much as five times the numbers pre-pandemic.
  • BCG’s COVID-19 employee sentiment survey from 2020 showed that 70% of managers are more open to flexible remote working models than they were before the pandemic.
  • Hybrid working models will be the norm soon. The businesses surveyed expect more than a third of employees to work remotely beyond the pandemic.
  • The U.K. saved 550,000 jobs because of remote capabilities; Germany saved 372,00 jobs and France saved 250,000….(More)”.

Measuring Commuting and Economic Activity Inside Cities with Cell Phone Records

Paper by Gabriel Kreindler and Yuhei Miyauchi: “We show how to use commuting flows to infer the spatial distribution of income within a city. A simple workplace choice model predicts a gravity equation for commuting flows whose destination fixed effects correspond to wages. We implement this method with cell phone transaction data from Dhaka and Colombo. Model-predicted income predicts separate income data, at the workplace and residential level, and by skill group. Unlike machine learning approaches, our method does not require training data, yet achieves comparable predictive power. We show that hartals (transportation strikes) in Dhaka reduce commuting more for high model-predicted wage and high-skill commuters….(More)”.

Reddit Is America’s Unofficial Unemployment Hotline

Ella Koeze at The New York Times: “In early December, Alex Branch’s car broke down. A 23-year-old former arcade employee in southern Virginia, Mr. Branch had been receiving unemployment benefits since he was laid off in March, and figured he would have no problem paying for the repairs. But when he checked his bank account, he was troubled to find that the payments had stopped.

He had failed to get useful information from his state’s unemployment office before, so he turned to the one place he figured he could get an explanation: Reddit.

“I’m very confused and have no idea what to do,” Mr. Branch wrote on r/Unemployment, a Reddit forum whose popularity has skyrocketed during the pandemic.

The next day, another user commented on Mr. Branch’s post, using a common abbreviation for Extended Benefits, an emergency unemployment program. “Were you on EB? If so, EB was cut off Nov 21.”

Mr. Branch hadn’t realized he had been on Extended Benefits, which kicked in after he exhausted 26 weeks of regular unemployment plus 13 additional weeks granted in the March pandemic stimulus bill. Virginia stopped payments because the state’s unemployment rate had fallen under 5 percent, triggering an end to federal funding for the Extended Benefits program.

“I didn’t know about it,” he said in an interview. “That’s the biggest frustration that I had about it was the fact that I never received the email that it was going to be shut off.”

For many of the millions of Americans like Mr. Branch who lost jobs because of the coronavirus, the stress of being unemployed in a pandemic has been compounded by the difficulty of navigating disorganized and often antiquated state and federal unemployment systems. Information from overwhelmed state offices and websites is often confusing, and reaching an official who can answer questions nearly impossible….

Post after post on r/Unemployment conveys bureaucratic problems with endless variations: how to file a claim depending on your circumstances, what to do if you made a mistake on your claim, what different statuses on your claim might mean, how to navigate confusing and glitch-prone online portals and even how to speak to an actual person to get issues resolved….

Many people come to r/Unemployment to offer answers, not just find them.

Albert Peers, who had been working in a call center in San Diego until the pandemic, spends time every day trying to answer questions about California’s system. He lives alone and can’t easily return to work because he has a lowered immune system. After first visiting the site when he encountered a hitch in his own unemployment benefits, Mr. Peers, 56, was shocked by the number of people who had no idea what to do.

The thought that someone might go hungry or miss rent because they were simply stymied by the system was unacceptable to him. “At that point I just made a decision,” he said. “You know what, like a couple hours every day, because I just can’t turn away.”…(More)”.

Robot census: Gathering data to improve policymaking on new technologies

Essay by Robert Seamans: There is understandable excitement about the impact that new technologies like artificial intelligence (AI) and robotics will have on our economy. In our everyday lives, we already see the benefits of these technologies: when we use our smartphones to navigate from one location to another using the fastest available route or when a predictive typing algorithm helps us finish a sentence in our email. At the same time, there are concerns about possible negative effects of these new technologies on labor. The Council of Economic Advisers of the past two Administrations have addressed these issues in the annual Economic Report of the President (ERP). For example, the 2016 ERP included a chapter on technology and innovation that linked robotics to productivity and growth, and the 2019 ERP included a chapter on artificial intelligence that discussed the uneven effects of technological change. Both these chapters used data at highly aggregated levels, in part because that is the data that is available. As I’ve noted elsewhere, AI and robots are everywhere, except, as it turns out, in the data.

To date, there have been no large scale, systematic studies in the U.S. on how robots and AI affect productivity and labor in individual firms or establishments (a firm could own one or more establishments, which for example could be a plant in a manufacturing setting or a storefront in a retail setting). This is because the data are scarce. Academic researchers interested in the effects of AI and robotics on economic outcomes have mostly used aggregate country and industry-level data. Very recently, some have studied these issues at the firm level using data on robot imports to France, Spain, and other countries. I review a few of these academic papers in both categories below, which provide early findings on the nuanced role these new technologies have on labor. Thanks to some excellent work being done by the U.S. Census Bureau, however, we may soon have more data to work with. This includes new questions on robot purchases in the Annual Survey of Manufacturers and Annual Capital Expenditures Survey and new questions on other technologies including cloud computing and machine learning in the Annual Business Survey….(More)”.

Are New Technologies Changing the Nature of Work? The Evidence So Far

Report by Kristyn Frank and Marc Frenette for the Institute for Research on Public Policy (Canada): “In recent years, ground breaking advances in artificial intelligence and their implications for automation technology have fuelled speculation that the very nature of work is being altered in unprecedented ways. News headlines regularly refer to the ”changing nature of work,” but what does it mean? Is there evidence that work has already been transformed by the new technologies? And if so, are these changes more dramatic than those experienced before?

In this paper, Kristyn Frank and Marc Frenette offer insights on these questions, based on the new research they conducted with their colleague Zhe Yang at Statistics Canada. Two aspects of work are under the microscope: the mix of work activities (or tasks) that constitute a job, and the mix of jobs in the economy. If new automation technologies are indeed changing the nature of work, the authors argue, then nonautomatable tasks should be increasingly important, and employment should be shifting toward occupations primarily involving such tasks.

According to the authors, nonroutine cognitive tasks (analytical or interpersonal) did become more important between 2011 and 2018. However, the changes were relatively modest, ranging from a 1.5 percent increase in the average importance of establishing and maintaining interpersonal relationships, to a 3.7 percent increase in analyzing data or information. Routine cognitive tasks — such as data entry — also gained importance, but these gains were even smaller. The picture is less clear for routine manual tasks, as the importance of tasks for which the pace is determined by the speed of equipment declined by close to 3 percent, whereas other tasks in that category became slightly more important.

Looking at longer-term shifts in overall employment, between 1987 and 2018, the authors find a gradual increase in the share of workers employed in occupations associated with nonroutine tasks, and a decline in routine-task-related occupations. The most pronounced shift in employment was away from production, craft, repair and operative occupations toward managerial, professional and technical occupations. However, they note that this shift to nonroutine occupations was not more pronounced between 2011 and 2018 than it was in the preceding decades. For instance, the share of employment in managerial, professional and technical occupations increased by 1.8 percentage points between 2011 and 2018, compared with a 6 percentage point increase between 1987 and 2010.

Most sociodemographic groups experienced the shift toward nonroutine jobs, although there were some exceptions. For instance, the employment share of workers in managerial, professional and technical occupations increased for all workers, but much more so for women than for men. Interestingly, there was a decline in the employment shares of workers in these occupations among those with a post-­secondary education. The explanation for this lies in the major increase over the past three decades in the proportion of workers with post-secondary education, which led some of them to move into jobs for which they are overqualified….(More)”.

The Rule of Technology – How Technology Is Used to Disturb Basic Labor Law Protections

Paper by Tammy Katsabian: “Much has been written on technology and the law. Leading scholars are occupied with the power dynamics between capital, technology, and the law, along with their implications for society and human rights. Alongside that, various labor law scholars focus on the implications of smart technology on employees’ rights throughout the recruitment and employment periods and on workers’ status and rights in the growing phenomenon of platform-based work. This article aims to contribute to the current scholarship by zooming it out and observing from a bird’s-eye view how certain actors use technology to manipulate and challenge basic legal categories in labor today. This is done by referring to legal, sociological, and internet scholarship on the matter.

The main argument elaborated throughout this article is that digital technology is used to blur and distort many of the basic labor law protections. Because of this, legal categories and rights in the labor field seem to be outdated and need to be adjusted to this new reality.
By providing four detailed examples, the article unpacks how employers, giant high-tech companies, and society use various forms of technology to constantly disturb legal categories in the labor field regarding time, sphere, and relations. In this way, the article demonstrates how social media sites, information communication technologies, and artificial intelligence are used to blur the traditional concepts of privacy, working time and place, the employment contract, and community. This increased blurriness and fragility in labor have created many new difficulties that require new ways of thinking about regulation. Therefore, the article argues that both law and technology have to be modified to cope with the new challenges. Following this, the article proposes three possible ways in which to start considering the regulation of labor in the digital reality: (1) embrace flexibility as part of the legal order and use it as an interpretive tool and not just as an obstacle, (2) broaden the current legal protection and add a procedural layer to the legal rights at stake, and (3) use technology as part of the solution to the dilemmas that technology itself has emphasized. By doing so, this article seeks to enable more accurate thinking on law and regulation in the digital reality, particularly in the labor field, as well as in other fields and contexts….(More)”.

Cognitive Science as a New People Science for the Future of Work

Brief by Frida Polli et al: “The notion of studying people in jobs as a science—in fields such as human resource management, people analytics, and industrial-organizational psychology—dates back to at least the early 20th century. In 1919, Yale psychologist Henry Charles Link wrote, “The application of science to the problem of employment is just beginning to receive serious attention,” at last providing an alternative to the “hire and fire” methods of 19th-century employers. A year later, prominent organizational theorists Ordway Teal and Henry C. Metcalf claimed, “The new focus in administration is to be the human element. The new center of attention and solicitude is the individual person, the worker.” The overall conclusion at the time was that various social and psychological factors governed differences in employee productivity and satisfaction….This Brief Proceeds in Five Sections:

● First, we review the limitations of traditional approaches to people science. In particular, we focus on four needs of the modern employer that are not satisfied by the status quo: job fit, soft skills, fairness, and flexibility.

● Second, we present the foundations of a new people science by explaining how advancements in fields like cognitive science and neuroscience can be used to understand the individual differences between humans.

● Third, we describe four best practices that should govern the application of the new people science theories to real-world employment contexts.

● Fourth, we present a case study of how one platform company has used the new people science to create hiring models for five high-growth roles.● Finally, we explain how the type of insights presented in Section IV can be made actionable in the context of retraining employees for the future of work….(More)”.

10 Questions That Will Determine the Future of Work

Article by Jeffrey Brown and Stefaan Verhulst: “…But in many cases, policymakers face a blizzard of contradictory information and forecasts that can lead to confusion and inaction. Unable to make sense of the torrent of data being thrown their way, policymakers often end up being preoccupied by the answers presented — rather than reflecting on the questions that matter.

If we want to design “good” future-of-work policies, we must have an inclusive and wide-ranging discussion of what we are trying to solve before we attempt to develop and deploy solutions….

We have found that policymakers often fail to ask questions and are often uncertain about the variables that underpin a problem.

In addition, few of the interventions that have been deployed make the best use of data, an emerging but underused asset that is increasingly available as a result of the ongoing digital transformation. If civil society, think tanks and others fail to create the space for a sustainable future-of-work policy to germinate, “solutions” without clearly articulated problems will continue to dictate policy…

Our 100 Questions Initiative seeks to interrupt this cycle of preoccupation with answers by ensuring that policymakers are, first of all, armed with a methodology they can use to ask the right questions and from there, craft the right solutions.

We are now releasing the top 10 questions and are seeking the public’s assistance through voting and providing feedback on whether or not these are really the right questions we should be asking:

Preparing for the Future of Work

  1. How can we determine the value of skills relevant to the future-of work-marketplace, and how can we increase the value of human labor in the 21st century?
  2. What are the economic and social costs and benefits of modernizing worker-support systems and providing social protection for workers of all employment backgrounds, but particularly for women and those in part-time or informal work?
  3. How does the current use of AI affect diversity and equity in the labor force? How can AI be used to increase the participation of underrepresented groups (including women, Black people, Latinx people, and low-income communities)? What aspects/strategies have proved most effective in reducing AI biases?…(More) (See also: