Category Archives: Automation & Artificial Intelligence

Automation and a Changing Economy

Source: Conor McKay, Ethan Pollack & Alastair Fitzpayne, Aspen Institute, Future of Work Initiative, April 2019

Automation is an important ingredient driving economic growth and progress. Automation has enabled us to feed a growing population while allowing workers to transition from subsistence farming to new forms of work. Automation helped moved us from a craft system to mass production, from blue-collar to white-collar to “new collar” work—with better work, higher wages, more jobs, and better living standards.

But without adequate policies and institutions, automation can also have negative effects on individuals and communities. Emerging technologies—including artificial intelligence, machine learning, and advanced robotics—have the potential to automate many tasks currently performed by workers, leading to renewed questions over what the future holds for the American workforce. We must ensure the proper support structures are in place to promote opportunity and prosperity for all.
Automation and a Changing Economy is divided into two sections.

Part I, Automation and a Changing Economy: The Case for Action, explores how automation impacts the economic security and opportunity of the American worker…..

Part II of this report, Automation and a Changing Economy: Policies for Shared Prosperity, outlines a program to address automation’s challenges and opportunities……

Related:
Executive Summary

Automation and New Tasks: How Technology Displaces and Reinstates Labor

Source: Daron Acemoglu – MIT and NBER, Pascual Restrepo – Boston University, March 5, 2019

From the abstract:
We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the allocation of tasks to capital and labor—the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added and may reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which labor has a comparative advantage. The introduction of new tasks changes the task content of production in favor of labor because of a reinstatement effect,and always raises the labor share and labor demand. We show how the role of changes in the task content of production—due to automation and new tasks—can be inferred from industry-level data. Our empirical decomposition suggests that the slower growth of employment over the last three decades is accounted for by an acceleration in the displacement effect, especially in manufacturing, a weaker reinstatement effect, and slower growth of productivity than in previous decades

Future Work

Source: Jeffrey M. Hirsch – University of North Carolina School of Law, February 14, 2019

From the abstract:
The Industrial Revolution. The Digital Age. These revolutions radically altered the workplace and society. We may be on the cusp of a new era—one that will rival or even surpass these historic disruptions. Technology such as artificial intelligence, robotics, virtual reality, and cutting-edge monitoring devices are developing at a rapid pace. These technologies have already begun to infiltrate the workplace and will continue to do so at ever increasing speed and breadth.

This Article addresses the impact of these emerging technologies on the workplace of the present and the future. Drawing upon interviews with leading technologists, the Article explains the basics of these technologies, describes their current applications in the workplace, and predicts how they are likely to develop in the future. It then examines the legal and policy issues implicated by the adoption of technology in the workplace—most notably job losses, employee classification, privacy intrusions, discrimination, safety and health, and impacts on disabled workers. These changes will surely strain a workplace regulatory system that is ill-equipped to handle them. What is unclear is whether the strain will be so great that the system breaks, resulting in a new paradigm of work.

Whether or not we are on the brink of a workplace revolution or a more modest evolution, emerging technology will exacerbate the inadequacies of our current workplace laws. This Article discusses possible legislative and judicial reforms designed to ameliorate these problems and stave off the possibility of a collapse that would leave a critical mass of workers without any meaningful protection, power, or voice. The most far-reaching of these options is a proposed “Law of Work” that would address the wide-ranging and interrelated issues posed by these new technologies via a centralized regulatory scheme. This proposal, as well as other more narrowly focused reforms, highlight the major impacts of technology on our workplace laws, underscore both the current and future shortcomings of those laws, and serve as a foundation for further research and discussion on the future of work.

Automation and New Tasks: The Implications of the Task Content of Production for Labor Demand

Source: Daron Acemoglu – MIT, Pascual Restrepo – Boston University, November 6, 2018

From the abstract:
We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added (of an industry or economy) and may also reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which labor has a comparative advantage. The introduction of new tasks changes the task content of production in favor of labor because of a reinstatement effect, and always raises the labor share and labor demand. We show how the role of changes in the task content of production—due to automation and new tasks—can be inferred from industry-level data. Our empirical decomposition suggests that the slower growth of employment over the last three decades is accounted for by an acceleration in the displacement effect, especially in manufacturing, a weaker reinstatement effect, and slower growth of productivity than in previous decades.

Towards an AI Economy That Works for All

Source: Stephen Herzenberg, Keystone Research Center, February 2019

From the summary:
This is the first report of a Keystone Research Center project on the “Future of Work.” The aim is to identify public policies that could help ensure that the application and diffusion of artificial intelligence (AI) over the next several decades fosters an economy in which Americans generally thrive. The project is motivated, in part, by concern that the opposite could occur: that AI will exacerbate the already high levels of income and wealth inequality in the United States. Our most important conclusion is that AI need not make our inequalities more severe. Creative public policies could lead to an AI economy “that works for the many, not just the few.”

The study design has been informed by the two principal authors’ experience at the one-time Office of Technology Assessment (OTA) of the US Congress. To guide the undertaking and provide feedback on its products, we recruited an advisory panel of nationally recognized academics and representatives of think tanks and the corporate, labor, and non-profit sectors. The project methodology combines interviews with technology experts, policy analysis, synthesis of research literature and, still to come, sectoral studies.

This first report contains three main parts. (1) Following an introduction, Sections II-IV contain an analysis of AI’s likely impacts through the lens of technology. Section II reviews past impacts of innovations including robotics and information technology on the economy and jobs. Section III looks at AI itself, how it does and does not go beyond previous technologies and substitute for human capacities and intelligence. Section IV explores the difficulties of predicting AI’s job impacts. (2) Section V, “The Plight of the American Worker,” considers the labor market context in which AI systems will spread and the roots of the economic inequality from which the nation suffers. (3) Section VI surveys policies that could influence inequality and the distribution of the benefits of productivity growth as AI spreads.

Related:
Press Release

Automation and Artificial Intelligence: How machines are affecting people and places

Source: Mark Muro, Robert Maxim, and Jacob Whiton, Brookings Institution, January 2019

From the summary:
At first, technologists issued dystopian alarms about the power of automation and artificial intelligence (AI) to destroy jobs. Then came a correction, with a wave of reassurances. Now, the discourse appears to be arriving at a more complicated understanding, suggesting that automation will bring neither apocalypse nor utopia, but instead both benefits and stress alike. Such is the ambiguous and sometimes disembodied nature of the “future of work” discussion.

Hence the analysis presented here. Intended to bring often-inscrutable trends down to earth, the following report develops both backward and forward-looking analyses of the impacts of automation over the years 1980 to 2016 and 2016 to 2030 to assess past and upcoming trends as they affect both people and communities in the United States.

The report focuses on areas of potential occupational change rather than net employment losses or gains. Special attention is applied to digging beneath national top-line statistics to explore industry, geographical, and demographic variations. Finally, the report concludes by suggesting a comprehensive response framework for national and state-local policymakers.

Related:
Executive summary
Data appendices
Press release
Infographic

The Robots Are Already Here: How Automation Will Shake Up Recruiting

Source: Roy Maurer, SHRM, June 8, 2018

People have been talking about automating recruiting tasks and workflows for years, but recent advances in artificial intelligence and machine learning are starting to make that talk reality.

These technologies allow talent acquisition teams to automate processes that they previously performed manually, eliminating inefficiencies and boosting productivity.

Recruiting automation can be found at all stages of the hiring process, from candidate sourcing and engagement, through scheduling and interviewing, to final selection.

If Robots Steal Our Jobs, Maybe We Should Make Them Pay Tax

Source: Laura Paddison, Huffington Post, June 1, 2018

….The idea of a robot tax has bubbled up over the past couple of years, thanks to the backing of some high-profile figures, proposing it as a way of trying to prevent all the benefits of automation from flowing to a tiny slice of wealthy people.

Benoît Hamon — a socialist candidate in the French presidential elections last year — made a robot tax a plank in his campaign. Perhaps the most famous advocate is Microsoft billionaire Bill Gates. He told Quartz last year, “Right now, the human worker who does, say, $50,000 worth of work in a factory, that income is taxed and you get income tax, social security tax, all those things. If a robot comes in to do the same thing, you’d think that we’d tax the robot at a similar level.”

He says he believes taxing machines could slow the pace of automation, giving people a chance to retrain and giving governments time to put in place policies to protect people from intensifying inequality…..

Capitalism in the age of robots: work, income and wealth in the 21st-century

Source: Adair Turner, Chair of the Institute for New Economic Thinking – Lecture at School of Advanced International Studies, Johns Hopkins University, Washington DC April 10th 2018

My title is “Capitalism in the age of robots” and my aim is to consider the possible long-term impact of rapid technological progress – and in particular of work automation and artificial intelligence. And I will sometimes use the word “robots” as shorthand for any sort of machine – any combination of hardware and software – that can perform any sort of work, rather than specifically meaning something which looks like a human, with legs, arms and a smiley face.

I will argue that the rapid, unstoppable, and limitless progress of automation potential will have profound implications for the nature of and need for work, and for the distribution of income and wealth. But also profound implications for the very meaning of some concepts and measures which play a fundamental role in economic analysis – in particular productivity growth and GDP per capita. At the limit indeed, one can question whether the very concept of “an economy” or of “economics” – if defined as the study of production and consumption choices amid conditions of inherent scarcity – have any meaning in a world where, eventually, all human work activities can be automated.

And while the world of near total automation which I describe is still many years away – at least 50 and maybe 100– I will argue that gradual progress towards that future state is already having and will increasingly have, profound, paradoxical and potentially harmful, as well as potentially beneficial, consequences. In particular I will suggest that:
• The faster the underlying pace of technological advance, the lower the measured productivity growth rate will be
• Automation threatens income from activities essential to human welfare – but not income gained from zero-sum competition
• The more rapidly information and communication technology progresses, the more that wealth and income derive from inherently physical and subjective assets, such as land, brands, or beauty.
• In already rich developed countries increasing productivity growth should not be a major long term public policy priority
• Better skills cannot solve the problem of rising inequality : but excellent education must enable people to live fulfilled lives as engaged citizens, and is needed to prevent a radical decline in social mobility…..

Automation, skills use and training

Source: Ljubica Nedelkoska, Glenda Quintini, Organisation for Economic Co-operation and Development, OECD Social, Employment and Migration Working Papers, No. 202, OECD Publishing, 2018

From the abstract:
This study focuses on the risk of automation and its interaction with training and the use of skills at work. Building on the expert assessment carried out by Carl Frey and Michael Osborne in 2013, the paper estimates the risk of automation for individual jobs based on the Survey of Adult Skills (PIAAC). The analysis improves on other international estimates of the individual risk of automation by using a more disaggregated occupational classification and identifying the same automation bottlenecks emerging from the experts’ discussion. Hence, it more closely aligns to the initial assessment of the potential automation deriving from the development of Machine Learning. Furthermore, this study investigates the same methodology using national data from Germany and United Kingdom, providing insights into the robustness of the results. The risk of automation is estimated for the 32 OECD countries that have participated in the Survey of Adult Skills (PIAAC) so far. Beyond the share of jobs likely to be significantly disrupted by automation of production and services, the accent is put on characteristics of these jobs and the characteristics of the workers who hold them. The risk is also assessed against the use of ICT at work and the role of training in helping workers transit to new career opportunities.

Related:
A study finds nearly half of jobs are vulnerable to automation
Source: The Economist, April 24, 2018

A WAVE of automation anxiety has hit the West. Just try typing “Will machines…” into Google. An algorithm offers to complete the sentence with differing degrees of disquiet: “…take my job?”; “…take all jobs?”; “…replace humans?”; “…take over the world?” 

Job-grabbing robots are no longer science fiction. In 2013 Carl Benedikt Frey and Michael Osborne of Oxford University used—what else?—a machine-learning algorithm to assess how easily 702 different kinds of job in America could be automated. They concluded that fully 47% could be done by machines “over the next decade or two”.

A new working paper by the OECD, a club of mostly rich countries, employs a similar approach, looking at other developed economies. Its technique differs from Mr Frey and Mr Osborne’s study by assessing the automatability of each task within a given job, based on a survey of skills in 2015. Overall, the study finds that 14% of jobs across 32 countries are highly vulnerable, defined as having at least a 70% chance of automation. A further 32% were slightly less imperilled, with a probability between 50% and 70%. At current employment rates, that puts 210m jobs at risk across the 32 countries in the study.