Report by by Tobias Sytsma, and Éder M. Sousa: “The rapid development of artificial intelligence (AI) has the potential to revolutionize the labor force with new generative AI tools that are projected to contribute trillions of dollars to the global economy by 2040. However, this opportunity comes with concerns about the impact of AI on workers and labor markets. As AI technology continues to evolve, there is a growing need for research to understand the technology’s implications for workers, firms, and markets. This report addresses this pressing need by exploring the relationship between occupational exposure and AI-related technologies, wages,... (More >)
Generative AI, Jobs, and Policy Response
Paper by the Global Partnership on AI: “Generative AI and the Future of Work remains notably absent from the global AI governance dialogue. Given the transformative potential of this technology in the workplace, this oversight suggests a significant gap, especially considering the substantial implications this technology has for workers, economies and society at large. As interest grows in the effects of Generative AI on occupations, debates centre around roles being replaced or enhanced by technology. Yet there is an incognita, the “Big Unknown”, an important number of workers whose future depends on decisions yet to be madeIn this brief,... (More >)
These Prisoners Are Training AI
Article by Morgan Meaker: “…Around the world, millions of so-called “clickworkers” train artificial intelligence models, teaching machines the difference between pedestrians and palm trees, or what combination of words describe violence or sexual abuse. Usually these workers are stationed in the global south, where wages are cheap. OpenAI, for example, uses an outsourcing firm that employs clickworkers in Kenya, Uganda, and India. That arrangement works for American companies, operating in the world’s most widely spoken language, English. But there are not a lot of people in the global south who speak Finnish. That’s why Metroc turned to prison labor.... (More >)
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
Paper by Fabrizio Dell’Acqua et al: “The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine the performance implications of AI on realistic, complex, and knowledge-intensive tasks. The pre-registered experiment involved 758 consultants comprising about 7% of the individual contributor-level consultants at the company. After establishing a performance baseline on a similar task, subjects were randomly assigned to one of three conditions: no AI access, GPT-4 AI access,... (More >)
Unleashing the metaverse for skills and workforce development
Article by Gemma Rodon, Marjorie Chinen, and Diego Angel-Urdinola: “The metaverse is revolutionizing skills and workforce development, reshaping learning in fields like auto-mechanics, health care, welding and various vocations. It offers future workers with invaluable, cost-effective, flexible, standardized and safe apprenticeship opportunities tailored for the demands of the global economy….Given its importance and potential, the World Bank’s EdTech team, with support from a Digital Development Partnership Grant, has recently completed a knowledge pack (KP) that provides evidence and case studies showcasing the advantages and results of using the metaverse, notably virtual and extended reality (XR) labs, for workforce development... (More >)
Unleashing possibilities, ignoring risks: Why we need tools to manage AI’s impact on jobs
Article by Katya Klinova and Anton Korinek: “…Predicting the effects of a new technology on labor demand is difficult and involves significant uncertainty. Some would argue that, given the uncertainty, we should let the “invisible hand” of the market decide our technological destiny. But we believe that the difficulty of answering the question “Who is going to benefit and who is going to lose out?” should not serve as an excuse for never posing the question in the first place. As we emphasized, the incentives for cutting labor costs are artificially inflated. Moreover, the invisible hand theorem does not... (More >)
Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology
Paper by Nikhil Agarwal, Alex Moehring, Pranav Rajpurkar & Tobias Salz: “While Artificial Intelligence (AI) algorithms have achieved performance levels comparable to human experts on various predictive tasks, human experts can still access valuable contextual information not yet incorporated into AI predictions. Humans assisted by AI predictions could outperform both human-alone or AI-alone. We conduct an experiment with professional radiologists that varies the availability of AI assistance and contextual information to study the effectiveness of human-AI collaboration and to investigate how to optimize it. Our findings reveal that (i) providing AI predictions does not uniformly increase diagnostic quality, and... (More >)
AI and the automation of work
Essay by Benedict Evans: “…We should start by remembering that we’ve been automating work for 200 years. Every time we go through a wave of automation, whole classes of jobs go away, but new classes of jobs get created. There is frictional pain and dislocation in that process, and sometimes the new jobs go to different people in different places, but over time the total number of jobs doesn’t go down, and we have all become more prosperous. When this is happening to your own generation, it seems natural and intuitive to worry that this time, there aren’t going... (More >)
Artificial Intelligence, Big Data, Algorithmic Management, and Labor Law
Chapter by Pauline Kim: “Employers are increasingly relying on algorithms and AI to manage their workforces, using automated systems to recruit, screen, select, supervise, discipline, and even terminate employees. This chapter explores the effects of these systems on the rights of workers in standard work relationships, who are presumptively protected by labor laws. It examines how these new technological tools affect fundamental worker interests and how existing law applies, focusing primarily as examples on two particular concerns—nondiscrimination and privacy. Although current law provides some protections, legal doctrine has largely developed with human managers in mind, and as a result,... (More >)
The A.I. Revolution Will Change Work. Nobody Agrees How.
Sarah Kessler in The New York Times: “In 2013, researchers at Oxford University published a startling number about the future of work: 47 percent of all United States jobs, they estimated, were “at risk” of automation “over some unspecified number of years, perhaps a decade or two.” But a decade later, unemployment in the country is at record low levels. The tsunami of grim headlines back then — like “The Rich and Their Robots Are About to Make Half the World’s Jobs Disappear” — look wildly off the mark. But the study’s authors say they didn’t actually mean to... (More >)
