Category Archives: Automation & Artificial Intelligence

Artificial intelligence: Implications for the future of work

Source: John Howard, American Journal of Industrial Medicine, Early View, August 22, 2019

From the abstract:
Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering. The modern field of AI began at a small summer workshop at Dartmouth College in 1956. Since then, AI applications made possible by machine learning (ML), an AI subdiscipline, include Internet searches, e‐commerce sites, goods and services recommender systems, image and speech recognition, sensor technologies, robotic devices, and cognitive decision support systems (DSSs). As more applications are integrated into everyday life, AI is predicted to have a globally transformative influence on economic and social structures similar to the effect that other general‐purpose technologies, such as steam engines, railroads, electricity, electronics, and the Internet, have had. Novel AI applications in the workplace of the future raise important issues for occupational safety and health. This commentary reviews the origins of AI, use of ML methods, and emerging AI applications embedded in physical objects like sensor technologies, robotic devices, or operationalized in intelligent DSSs. Selected implications on the future of work arising from the use of AI applications, including job displacement from automation and management of human‐machine interactions, are also reviewed. Engaging in strategic foresight about AI workplace applications will shift occupational research and practice from a reactive posture to a proactive one. Understanding the possibilities and challenges of AI for the future of work will help mitigate the unfavorable effects of AI on worker safety, health, and well‐being.

When Robots Make Legal Mistakes

Source: Susan C. Morse, Oklahoma Law Review, Vol. 72, 2019

From the abstract:
The questions presented by robots’ legal mistakes are examples of the legal process inquiry that asks when the law will accept decisions as final, even if they are mistaken. Legal decision-making robots include market robots and government robots. In either category, they can make mistakes of undercompliance or overcompliance. A market robot’s overcompliance mistake or a government robot’s undercompliance mistake is unlikely to be challenged. On the other hand, government enforcement can challenge a market robot’s undercompliance mistake, and an aggrieved regulated party can object to a government robot’s overcompliance mistake. Especially if robots cannot defend their legal decisions due to a lack of explainability, they will have an incentive to make decisions that will avoid the prospect of challenge. This incentive could encourage counterintuitive results. For instance, it could encourage market robots to overcomply and government robots to undercomply with the law.

The future of work in America: People and places, today and tomorrow

Source: Susan Lund, James Manyika, Liz Hilton Segel, André Dua, Bryan Hancock, Scott Rutherford, and Brent Macon, McKinsey Global Institute, July 2019

From the summary:

…..A new report from the McKinsey Global Institute, The future of work in America: People and places, today and tomorrow, analyzes more than 3,000 US counties and 315 cities and finds they are on sharply different paths. Automation is not happening in a vacuum, and the health of local economies today will affect their ability to adapt and thrive in the face of the changes that lie ahead.

The trends outlined in this report could widen existing disparities between high-growth cities and struggling rural areas, and between high-wage workers and everyone else. But this is not a foregone conclusion. The United States can improve outcomes nationwide by connecting displaced workers with new opportunities, equipping people with the skills they need to succeed, revitalizing distressed areas, and supporting workers in transition. Returning to more inclusive growth will require the combined energy and ingenuity of business leaders, policy makers, educators, and nonprofits across the country…..

The Invisible Web of Work: The Intertwining of A-I, Electronic Surveillance, and Labor Law

Source: Richard A. Bales, Katherine V.W. Stone, UCLA School of Law, Public Law Research Paper No. 19-18, Last revised: June 30, 2019

From the abstract:
Employers and others who hire or engage workers to perform services use a dizzying array of electronic mechanisms to make personnel decisions about hiring, worker evaluation, compensation, discipline, and retention. These electronic mechanisms include electronic trackers, surveillance cameras, metabolism monitors, wearable biological measuring devices, and implantable technology. These tools enable employers to record their workers’ every movement, listen in on their conversations, measure minute aspects of performance, and detect oppositional organizing activities. The data collected is transformed by means of artificial intelligence (A-I) algorithms into a permanent electronic resume that can identify and predict an individual’s performance as well as their work ethic, personality, union proclivity, employer loyalty, and future health care costs. The electronic resume produced by A-I will accompany workers from job to job as they move around the boundaryless workplace. Thus A-I and electronic monitoring produce an invisible electronic web that threatens to invade worker privacy, deter unionization, enable subtle forms of employer blackballing, exacerbate employment discrimination, render unions ineffective, and obliterate the protections of the labor laws.

This article describes the many ways A-I is being used in the workplace and how its use is transforming the practices of hiring, evaluating, compensating, controlling, and dismissing workers. It then focuses on four areas of law in which A-I threatens to undermine worker protections: anti-discrimination law, privacy law, antitrust law, and labor law. Finally, this article maps out an agenda for future law reform and research.

Is Technology Widening the Gender Gap? Automation and the Future of Female Employment

Source: Mariya Brussevich, Era Dabla-Norris, Salma Khalid, IMF Working Paper No. 19/91, May 2019

From the abstract:
Using individual level data on task composition at work for 30 advanced and emerging economies, we find that women, on average, perform more routine tasks than men/tasks that are more prone to automation. To quantify the impact on jobs, we relate data on task composition at work to occupation level estimates of probability of automation, controlling for a rich set of individual characteristics (e.g., education, age, literacy and numeracy skills). Our results indicate that female workers are at a significantly higher risk for displacement by automation than male workers, with 11 percent of the female workforce at high risk of being automated given the current state of technology, albeit with significant cross-country heterogeneity. The probability of automation is lower for younger cohorts of women, and for those in managerial positions.

Artificial Intelligence, Discretion, and Bureaucracy

Source: Justin B. Bullock, The American Review of Public Administration, OnlineFirst, Published June 18, 2019
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From the abstract:
This essay highlights the increasing use of artificial intelligence (AI) in governance and society and explores the relationship between AI, discretion, and bureaucracy. AI is an advanced information communication technology tool (ICT) that changes both the nature of human discretion within a bureaucracy and the structure of bureaucracies. To better understand this relationship, AI, discretion, and bureaucracy are explored in some length. It is argued that discretion and decision-making are strongly influenced by intelligence, and that improvements in intelligence, such as AI, can help improve the overall quality of administration. Furthermore, the characteristics, strength, and weaknesses of both human discretion and AI are explored. Once these characteristics are laid out, a further exploration of the role AI may play in bureaucracies and bureaucratic structure is presented, followed by a specific focus on systems-level bureaucracies. In addition, it is argued that task distribution and task characteristics play a large role, along with the organizational and legal context, in whether a task favors human discretion or the use of AI. Complexity and uncertainty are presented as the major defining characteristics for categorizing tasks. Finally, a discussion is provided about the important cautions and concerns of utilizing AI in governance, in particular, with respect to existential risk and administrative evil.

The Future Of Work 2.0: Navigating The Transition To New Possibilities

Source: David Gibson, Aspen Institute, Report Of The 2018 Aspen Institute Roundtable On Institutional Innovation, 2019

From the summary:
Today’s leading businesses are dealing with a changing work environment that goes beyond artificial intelligence and robots. Instead, it encompasses the work machines and humans will do together. This report of the 2018 Roundtable, written by David Gibson, explores the Future of Work 2.0—focusing on how all stakeholders can realize the opportunities and possibilities of automation in the work landscape. It features a robust discussion on education, business structures, models of employment and leadership philosophies.

Chapters include:
Introduction
AI, Robotics and the Future of Work
Building the New Workspace
Maximizing Human Capital
The Future of Leadership

Visit the interactive Institutional Innovation report website to further explore the report.

Robotic health care is coming to a hospital near you

Source: Mattie Milner, Stephen Rice, The Conversation, May 7, 2019

Medical robots are helping doctors and other professionals save time, lower costs and shorten patient recovery times, but patients may not be ready. Our research into human perceptions of automated health care finds that people are wary of getting their health care from an automated system, but that they can adjust to the idea – especially if it saves them money.

Hospitals and medical practices are already using a fair amount of automation. For instance, in one San Francisco hospital and other places, delivery robots – about the size of a mini-fridge – zip through the hallways delivering pills, bringing lunch to patients and ferrying specimens and medical equipment to different labs. Some hospitals are set up for delivery robots to open remote-control doors and even use elevators to get around the building.

Workforce Automation: Better Data Needed to Assess and Plan for Effects of Advanced Technologies on Jobs

Source: GAO-19-257, Published: March 7, 2019

From the summary:
Robots, artificial intelligence, and other advanced technologies are changing the workplace. We visited companies to observe the effects on workers. Effects varied, with some companies reducing their workforces, many moving workers to different roles, and some hiring workers due to increased production or new skill needs.

Workforce data doesn’t identify the causes of employment shifts, making it difficult to assess technology’s effects. Additional information could help agencies design programs to prepare workers for jobs of the future.

We recommended that the Department of Labor develop ways to better track workforce effects of technologies…..

Women, Automation, and the Future of Work

Source: Ariane Hegewisch, Chandra Childers, Heidi Hartmann, Institute for Women’s Policy Research, IWPR #C47, March 13, 2019

From the executive summary:
From driverless cars to factories operated by robots and stores with self-checkout systems, automation and technology are changing the way we perceive and do work. But how do all these technological changes affect men and women differently?

According to Women, Automation, and the Future of Work, an Institute for Women’s Policy Research (IWPR) report, technological change will affect men and women differently in a number of ways. The first study of its kind in the United States, this report estimates the risk of automation across occupations by gender and presents a comprehensive picture of what we know—and what we don’t—about how the future of work will affect women workers.

This study finds that discussions about technological change and the future of work must include gender as part of the analysis. That’s because the jobs most commonly held by women—cashiers,secretaries, and bookkeeping clerks, for example—face some of the highest risks of becoming automated in the future. And while men are not immune to the risks of technological change, women are even more likely to work in jobs where technology and automation threaten to displace them.

This report examines not only the impact of these technological shifts on the quantity of jobs but also the quality of jobs in the future. Drawing on occupational projections from the Bureau of Labor Statistics and recent research on the potential for automation across occupations, IWPR researchers developed a Future of Work Database to analyze the potential impact of technological changes on:

■ the number of jobs
■ the nature of work and how it’s done
■ the quality of work
■ the future of work and family

By increasing our understanding of the potential impact of these technological changes, we can create more gender-aware policies that will increase equality and the quality of jobs in the coming decades.