Anthology edited by Murali Shanmugavelan and Aiha Nguyen: “…explores platformization from the point of view of precarious gig workers in the Majority World. In countries like Bangladesh, Brazil, and India — which reinforce social hierarchies via gender, race, and caste — precarious workers are often the most marginalized members of society. Labor platforms made familiar promises to workers in these countries: work would be democratized, and people would have the opportunity to be their own boss. Yet even as platforms have upended the legal relationship between worker and employer, they have leaned into social structures to keep workers precarious — and in fact formalized those social precarities through surveillance and data collection…(More)”.
The impact of generative artificial intelligence on socioeconomic inequalities and
policy making
Paper by Valerio Capraro et al: “Generative artificial intelligence, including chatbots like ChatGPT, has the potential to both exacerbate and ameliorate existing socioeconomic inequalities. In this article, we provide a state-of-the-art interdisciplinary overview of the probable impacts of generative AI on four critical domains: work, education, health, and information. Our goal is to warn about how generative AI could worsen existing inequalities while illuminating directions for using AI to resolve pervasive social problems. Generative AI in the workplace can boost productivity and create new jobs, but the benefits will likely be distributed unevenly. In education, it offers personalized learning but may widen the digital divide. In healthcare, it improves diagnostics and accessibility but could deepen pre-existing inequalities. For information, it democratizes content creation and access but also dramatically expands the production and proliferation of misinformation. Each section covers a specific topic, evaluates existing research, identifies critical gaps, and recommends research directions. We conclude with a section highlighting the role of policymaking to maximize generative AI’s potential to reduce inequalities while
mitigating its harmful effects. We discuss strengths and weaknesses of existing policy frameworks in the European Union, the United States, and the United Kingdom, observing that each fails to fully confront the socioeconomic challenges we have identified. We contend that these policies should promote shared prosperity through the advancement of generative AI. We suggest several concrete policies to encourage further research and debate. This article emphasizes the need for interdisciplinary collaborations to understand and address the complex challenges of generative AI…(More)”.
New Jersey is turning to AI to improve the job search process
Article by Beth Simone Noveck: “Americans are experiencing some conflicting feelings about AI.
While people are flocking to new roles like prompt engineer and AI ethicist, the technology is also predicted to put many jobs at risk, including computer programmers, data scientists, graphic designers, writers, lawyers.
Little wonder, then, that a national survey by the Heldrich Center for Workforce Development found an overwhelming majority of Americans (66%) believe that they “will need more technological skills to achieve their career goals.” One thing is certain: Workers will need to train for change. And in a world of misinformation-filled social media platforms, it is increasingly important for trusted public institutions to provide reliable, data-driven resources.
In New Jersey, we’ve tried doing just that by collaborating with workers, including many with disabilities, to design technology that will support better decision-making around training and career change. Investing in similar public AI-powered tools could help support better consumer choice across various domains. When a public entity designs, controls and implements AI, there is a far greater likelihood that this powerful technology will be used for good.
In New Jersey, the public can find reliable, independent, unbiased information about training and upskilling on the state’s new MyCareer website, which uses AI to make personalized recommendations about your career prospects, and the training you will need to be ready for a high-growth, in-demand job…(More)”.
Why we’re fighting to make sure labor unions have a voice in how AI is implemented
Article by Liz Shuler and Mike Kubzansky: “Earlier this month, Google’s co-founder admitted that the company had “definitely messed up” after its AI tool, Gemini, produced historically inaccurate images—including depictions of racially diverse Nazis. Sergey Brin cited a lack of “thorough testing” of the AI tool, but the incident is a good reminder that, despite all the hype around generative AI replacing human output, the technology still has a long way to go.
Of course, that hasn’t stopped companies from deploying AI in the workplace. Some even use the technology as an excuse to lay workers off. Since last May, at least 4,000 people have lost their jobs to AI, and 70% of workers across the country live with the fear that AI is coming for theirs next. And while the technology may still be in its infancy, it’s developing fast. Earlier this year, AI pioneer Mustafa Suleyman said that “left completely to the market and to their own devices, [AI tools are] fundamentally labor-replacing.” Without changes now, AI could be coming to replace a lot of people’s jobs.
It doesn’t have to be this way. AI has enormous potential to build prosperity and unleash human creativity, but only if it also works for working people. Ensuring that happens requires giving the voice of workers—the people who will engage with these technologies every day, and whose lives, health, and livelihoods are increasingly affected by AI and automation—a seat at the decision-making table.
As president of the AFL-CIO, representing 12.5 million working people across 60 unions, and CEO of Omidyar Network, a social change philanthropy that supports responsible technology, we believe that the single best movement to give everyone a voice is the labor movement. Empowering workers—from warehouse associates to software engineers—is the most powerful tactic we have to ensure that AI develops in the interests of the many, not the few…(More)”.
Navigating the Future of Work: Perspectives on Automation, AI, and Economic Prosperity
Report by Erik Brynjolfsson, Adam Thierer and Daron Acemoglu: “Experts and the media tend to overestimate technology’s negative impact on employment. Case studies suggest that technology-induced unemployment fears are often exaggerated, evidenced by the McKinsey Global Institute reversing its AI forecasts and the growth in jobs predicted to be at high risk of automation.
Flexible work arrangements, technical recertification, and creative apprenticeship models offer real-time learning and adaptable skills development to prepare workers for future labor market and technological changes.
AI can potentially generate new employment opportunities, but the complex transition for workers displaced by automation—marked by the need for retraining and credentialing—indicates that the productivity benefits may not adequately compensate for job losses, particularly among low-skilled workers.
Instead of resorting to conflictual relationships, labor unions in the US must work with employers to support firm automation while simultaneously advocating for worker skill development, creating a competitive business enterprise built on strong worker representation similar to that found in Germany…(More)”.
Handbook of Artificial Intelligence at Work
Book edited by Martha Garcia-Murillo and Andrea Renda: “With the advancement in processing power and storage now enabling algorithms to expand their capabilities beyond their initial narrow applications, technology is becoming increasingly powerful. This highly topical Handbook provides a comprehensive overview of the impact of Artificial Intelligence (AI) on work, assessing its effect on an array of economic sectors, the resulting nature of work, and the subsequent policy implications of these changes.
Featuring contributions from leading experts across diverse fields, the Handbook of Artificial Intelligence at Work takes an interdisciplinary approach to understanding AI’s connections to existing economic, social, and political ecosystems. Considering a range of fields including agriculture, manufacturing, health care, education, law and government, the Handbook provides detailed sector-specific analyses of how AI is changing the nature of work, the challenges it presents and the opportunities it creates. Looking forward, it makes policy recommendations to address concerns, such as the potential displacement of some human labor by AI and growth in inequality affecting those lacking the necessary skills to interact with these technologies or without opportunities to do so.
This vital Handbook is an essential read for students and academics in the fields of business and management, information technology, AI, and public policy. It will also be highly informative from a cross-disciplinary perspective for practitioners, as well as policy makers with an interest in the development of AI technology…(More)”
Creating Real Value: Skills Data in Learning and Employment Records
Article by Nora Heffernan: “Over the last few months, I’ve asked the same question to corporate leaders from human resources, talent acquisition, learning and development, and management backgrounds. The question is this:
What kind of data needs to be included in learning and employment records to be of greatest value to you in your role and to your organization?
By data, I’m talking about credential attainment, employment history, and, emphatically, verified skills data: showing at an individual level what a candidate or employee knows and is able to do.
The answer varies slightly by industry and position, but unanimously, the employers I’ve talked to would find the greatest value in utilizing learning and employment records that include verified skills data. There is no equivocation.
And as the national conversation about skills-first talent management continues to ramp up, with half of companies indicating they plan to eliminate degree requirements for some jobs in the next year, the call for verified skill data will only get louder. Employers value skills data for multiple reasons…(More)”.
Name Your Industry—or Else!
Essay by Sarah M. Brownsberger on “The dehumanizing way economics data describes us”: “…My alma mater wants to know what industry I belong to. In a wash of good feeling after seeing old friends, I have gone to the school website to update my contact information. Name and address, easy, marital status, well and good—but next comes a drop-down menu asking for my “industry.”
In my surprise, I have an impulse to type “Where the bee sucks, there suck I!” But you can’t quote Shakespeare in a drop-down menu. You can only opt only for its options.
The school is certainly cutting-edge. Like a fashion item that you see once and assume is aberrant and then see ten times in a week, the word “industry” is all over town. Cryptocurrency is an industry. So are Elvis-themed marriages. Outdoor recreation is an industry. A brewery in my city hosts “Industry Night,” a happy hour “for those who work in the industry”—tapsters and servers.
Are we all in an industry? What happened to “occupation”?…(More)”.
Rebalancing AI
Article by Daron Acemoglu and Simon Johnson: “Optimistic forecasts regarding the growth implications of AI abound. AI adoption could boost productivity growth by 1.5 percentage points per year over a 10-year period and raise global GDP by 7 percent ($7 trillion in additional output), according to Goldman Sachs. Industry insiders offer even more excited estimates, including a supposed 10 percent chance of an “explosive growth” scenario, with global output rising more than 30 percent a year.
All this techno-optimism draws on the “productivity bandwagon”: a deep-rooted belief that technological change—including automation—drives higher productivity, which raises net wages and generates shared prosperity.
Such optimism is at odds with the historical record and seems particularly inappropriate for the current path of “just let AI happen,” which focuses primarily on automation (replacing people). We must recognize that there is no singular, inevitable path of development for new technology. And, assuming that the goal is to sustainably improve economic outcomes for more people, what policies would put AI development on the right path, with greater focus on enhancing what all workers can do?…(More)”
Using AI to support people with disability in the labour market
OECD Report: “People with disability face persisting difficulties in the labour market. There are concerns that AI, if managed poorly, could further exacerbate these challenges. Yet, AI also has the potential to create more inclusive and accommodating environments and might help remove some of the barriers faced by people with disability in the labour market. Building on interviews with more than 70 stakeholders, this report explores the potential of AI to foster employment for people with disability, accounting for both the transformative possibilities of AI-powered solutions and the risks attached to the increased use of AI for people with disability. It also identifies obstacles hindering the use of AI and discusses what governments could do to avoid the risks and seize the opportunities of using AI to support people with disability in the labour market…(More)”.