Tasks, Automation, and the Rise in US Wage Inequality


Paper by Daron Acemoglu & Pascual Restrepo: “We document that between 50% and 70% of changes in the US wage structure over the last four decades are accounted for by the relative wage declines of worker groups specialized in routine tasks in industries experiencing rapid automation. We develop a conceptual framework where tasks across a number of industries are allocated to different types of labor and capital. Automation technologies expand the set of tasks performed by capital, displacing certain worker groups from employment opportunities for which they have comparative advantage. This framework yields a simple equation linking wage changes of a demographic group to the task displacement it experiences.

We report robust evidence in favor of this relationship and show that regression models incorporating task displacement explain much of the changes in education differentials between 1980 and 2016. Our task displacement variable captures the effects of automation technologies (and to a lesser degree offshoring) rather than those of rising market power, markups or deunionization, which themselves do not appear to play a major role in US wage inequality. We also propose a methodology for evaluating the full general equilibrium effects of task displacement (which include induced changes in industry composition and ripple effects as tasks are reallocated across different groups). Our quantitative evaluation based on this methodology explains how major changes in wage inequality can go hand-in-hand with modest productivity gains….(More)”.

Building an Inclusive Digital Future


Article by Lee Jong-Wha: “…Addressing such questions is essential to preparing for the post-pandemic era, when all countries will need to embrace new ways of working, producing, and consuming. Digitalization can make a huge contribution to public health, the environment, consumer welfare, and wealth creation across society, but only if the public and private sectors work together to ensure inclusiveness.

Most countries will need policies to narrow the gaps in digital skills and access, because a growing share of jobs will require more technological know-how. Education systems must do more to equip students with the knowledge and skills they will need in a digital future. And job training must keep all workers up to date on the latest digital technologies.

Governments have a critical role to play on all of these fronts. It was state support and commitments that brought us revolutionary innovations like the internet, antibiotics, renewable energy, and the mRNA technology behind the development of the most effective COVID-19 vaccines. To fulfill their role as market makers, governments need to increase investments in physical infrastructure and human capital, and provide financial and tax incentives to ensure equitable access to critical technologies. They should also be exploring ways to provide more grants, subsidies, and technical support for small and medium enterprises and start-ups, so that the benefits of digital revolution do not remain limited to a few large companies….(More)”.

AI and Shared Prosperity


Paper by Katya Klinova and Anton Korinek: “Future advances in AI that automate away human labor may have stark implications for labor markets and inequality. This paper proposes a framework to analyze the effects of specific types of AI systems on the labor market, based on how much labor demand they will create versus displace, while taking into account that productivity gains also make society wealthier and thereby contribute to additional labor demand. This analysis enables ethically-minded companies creating or deploying AI systems as well as researchers and policymakers to take into account the effects of their actions on labor markets and inequality, and therefore to steer progress in AI in a direction that advances shared prosperity and an inclusive economic future for all of humanity…(More)”.

New York vs Big Tech: Lawmakers Float Data Tax in Privacy Push


GovTech article: “While New York is not the first state to propose data privacy legislation, it is the first to propose a data privacy bill that would implement a tax on big tech companies that benefit from the sale of New Yorkers’ consumer data.

Known as the Data Economy Labor Compensation and Accountability Act, the bill looks to enact a 2 percent tax on annual receipts earned off New York residents’ data. This tax and other rules and regulations aimed at safeguarding citizens’ data will be enforced by a newly created Office of Consumer Data Protection outlined in the bill.

The office would require all data controllers and processors to register annually in order to meet state compliance requirements. Failure to do so, the bill states, would result in fines.

As for the tax, all funds will be put toward improving education and closing the digital divide.

“The revenue from the tax will be put towards digital literacy, workforce redevelopment, STEAM education (science, technology, engineering, arts and mathematics), K-12 education, workforce reskilling and retraining,” said Sen. Andrew Gounardes, D-22.

As for why the bill is being proposed now, Gounardes said, “Every day, big tech companies like Amazon, Apple, Facebook and Google capitalize on the unpaid labor of billions of people to create their products and services through targeted advertising and artificial intelligence.”…(More)”

Platform Workers, Data Dominion and Challenges to Work-life Quality


Paper by Mabel Choo and Mark Findlay: “Originally this short reflection was intended to explore the relationship between the under-regulated labour environment of gig workers and their appreciation of work-life quality. It was never intended as a comprehensive governance critique of what is variously known as independent, franchised, or autonomous service delivery transactions facilitated through platform providers. Rather it was to represent a suggestive snapshot of how workers in these contested employment contexts viewed the relevance of regulation (or its absence) and the impact that new forms of regulation might offer for work-life quality.

By exploring secondary source commentary on worker experiences and attitudes it became clear that profound information deficits regarding how their personal data was being marketed meant that expecting any detailed appreciation of regulatory need and potentials was unrealistic from such a disempowered workforce. In addition, the more apparent was the practice of the platforms re-using and marketising this data without the knowledge or informed consent of the data subjects (service providers and customers) the more necessary it seemed to factor in this commercialisation when regulatory possibilities are to be considered.

The platform providers have sheltered their clandestine use of worker data (whether it be from pervasive surveillance or transaction histories) behind dubious discourse about disruptive economies, non-employment responsibilities, and the distinction between business and private data. In what follows we endeavor to challenge these disempowering interpretations and assertions, while arguing the case that at the very least data subjects need to know what platforms do with the data they produce and have some say in its re-use. In proposing these basic pre-conditions for labour transactions, we hope that work-life experience can be enhanced. Many of the identified needs for regulation and suggestions as to the form it should take are at this point declaratory in the paper, and as such require more empirical modelling to evaluate their potential influences in bettering work-life quality….(More)”

Digital Technologies, Innovation, and Skills: Emerging Trajectories and Challenges


Paper by Tommaso Ciarli et al: “In order to better understand the complex and dialectical relationships between digital technologies, innovation, and skills, it is necessary to improve our understanding of the coevolution between the trajectories of connected digital technologies, firm innovation routines, and skills formation. This is critical as organizations recombine and adapt digital technologies; they require new skills to innovate, learn, and adapt to evolving digital technologies, while digital technologies change the codification of knowledge for productive and innovative activities. The coevolution between digital technologies, innovation, and skills also requires, and is driven by, a reorganization of productive and innovation processes, both within and between firms. We observe this in all economic sectors, from agriculture to services. Based on evidence on past technologies in the innovation literature, we suggest that we might require a new set of stylized facts to better map the main future trajectories of digital technologies, their adoption, use, and recombination in organizations, to improve our understanding of their impact on productivity, employment and inequality. The papers in this special issue contribute to a better understanding of the interdependence between digital technologies, innovation, and skills….(More)”.

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)”.