Artificial Intelligence and the Future of Work

Curated on Posted on by Stefaan Verhulst

Report by the National Academies: “AI technology is at an inflection point: a surge of technological progress has driven the rapid development and adoption of generative AI systems, such as ChatGPT, which are capable of generating text, images, or other content based on user requests.

This technical progress is likely to continue in coming years, with the potential to complement or replace human labor in certain tasks and reshape job markets. However, it is difficult to predict exactly which new AI capabilities might emerge, and when these advances might occur.

This National Academies’ report evaluates recent advances in AI technology and their implications for economic productivity, job stability, and income inequality, identifying research opportunities and data needs to equip workers and policymakers to flexibly respond to AI developments…(More)”

Code and Craft: How Generative Ai Tools Facilitate Job Crafting in Software Development

Curated on Posted on by Stefaan Verhulst

Paper by Leonie Rebecca Freise et al: “The rapid evolution of the software development industry challenges developers to manage their diverse tasks effectively. Traditional assistant tools in software development often fall short of supporting developers efficiently. This paper explores how generative artificial intelligence (GAI) tools, such as Github Copilot or ChatGPT, facilitate job crafting—a process where employees reshape their jobs to meet evolving demands. By integrating GAI tools into workflows, software developers can focus more on creative problem-solving, enhancing job satisfaction, and fostering a more innovative work environment. This study investigates how GAI tools influence task, cognitive, and relational job crafting behaviors among software developers, examining its implications for professional growth and adaptability within the industry. The paper provides insights into the transformative impacts of GAI tools on software development job crafting practices, emphasizing their role in enabling developers to redefine their job functions…(More)”.

Digital Distractions with Peer Influence: The Impact of Mobile App Usage on Academic and Labor Market Outcomes

Curated on Posted on by Stefaan Verhulst

Paper by Panle Jia Barwick, Siyu Chen, Chao Fu & Teng Li: “Concerns over the excessive use of mobile phones, especially among youths and young adults, are growing. Leveraging administrative student data from a Chinese university merged with mobile phone records, random roommate assignments, and a policy shock that affects peers’ peers, we present, to our knowledge, the first estimates of both behavioral spillover and contextual peer effects, and the first estimates of medium-term impacts of mobile app usage on academic achievement, physical health, and labor market outcomes. App usage is contagious: a one s.d. increase in roommates’ in-college app usage raises own app usage by 4.4% on average, with substantial heterogeneity across students. App usage is detrimental to both academic performance and labor market outcomes. A one s.d. increase in own app usage reduces GPAs by 36.2% of a within-cohort-major s.d. and lowers wages by 2.3%. Roommates’ app usage exerts both direct effects (e.g., noise and disruptions) and indirect effects (via behavioral spillovers) on GPA and wage, resulting in a total negative impact of over half the size of the own usage effect. Extending China’s minors’ game restriction policy of 3 hours per week to college students would boost their initial wages by 0.7%. Using high-frequency GPS data, we identify one underlying mechanism: high app usage crowds out time in study halls and increases absences from and late arrivals at lectures…(More)”.

The ABC’s of Who Benefits from Working with AI: Ability, Beliefs, and Calibration

Curated on Posted on by Stefaan Verhulst

Paper by Andrew Caplin: “We use a controlled experiment to show that ability and belief calibration jointly determine the benefits of working with Artificial Intelligence (AI). AI improves performance more for people with low baseline ability. However, holding ability constant, AI assistance is more valuable for people who are calibrated, meaning they have accurate beliefs about their own ability. People who know they have low ability gain the most from working with AI. In a counterfactual analysis, we show that eliminating miscalibration would cause AI to reduce performance inequality nearly twice as much as it already does…(More)”.

Future of Professionals

Curated on Posted on by Stefaan Verhulst

Report by Thomson Reuters: “First, the productivity benefits we have been promised are now becoming more apparent. As AI adoption has become widespread, professionals can more tangibly tell us about how they will use this transformative technology and the greater efficiency and value it will provide. The most common use cases for AI-powered technology thus far include drafting documents, summarizing information, and performing basic research. Second, there’s a tremendous sense of excitement about the value that new AI-powered technology can bring to the day-to-day lives of the professionals we surveyed. While more than half of professionals said they’re most excited about the benefits that new AI-powered technologies can bring in terms of time-savings, nearly 40% said the new value that will be brought is what excites them the most.

This report highlights how AI could free up that precious commodity of time. As with the adoption of all new technology, change appears moderate and the impact incremental. And yet, within the year, our respondents predicted that for professionals, AI could free up as much as four hours a week. What will they do with 200 extra hours of time a year? They might reinvest that time in strategic work, innovation, and professional development, which could help companies retain or advance their competitive advantage. Imagine the broader impact on the economy and GDP from this increased efficiency. For US lawyers alone, that is a combined 266 million hours of increased productivity. That could translate into $100,000 in new, billable time per lawyer each year, based on current average rates – with similar productivity gains projected across various professions. The time saved can also be reinvested in professional development, nurturing work-life balance, and focusing on wellness and mental health. Moreover, the economic and organizational benefits of these time-savings are substantial. They could lead to reduced operational costs and higher efficiency, while enabling organizations to redirect resources toward strategic initiatives, fostering growth and competitiveness.

Finally, it’s important to acknowledge there’s still a healthy amount of reticence among professionals to fully adopt AI. Respondents are concerned primarily with the accuracy of outputs, and almost two-thirds of respondents agreed that data security is a vital component of responsible use. These concerns aren’t trivial, and they warrant attention as we navigate this new era of technology. While AI can provide tremendous productivity benefits to professionals and generate greater value for businesses, that’s only possible if we build and use this technology responsibly.”…(More)”.

Is Software Eating the World?

Curated on Posted on by Stefaan Verhulst

Paper by Sangmin Aum & Yongseok Shin: “When explaining the declining labor income share in advanced economies, the macro literature finds that the elasticity of substitution between capital and labor is greater than one. However, the vast majority of micro-level estimates shows that capital and labor are complements (elasticity less than one). Using firm- and establishment-level data from Korea, we divide capital into equipment and software, as they may interact with labor in different ways. Our estimation shows that equipment and labor are complements (elasticity 0.6), consistent with other micro-level estimates, but software and labor are substitutes (1.6), a novel finding that helps reconcile the macro vs. micro-literature elasticity discord. As the quality of software improves, labor shares fall within firms because of factor substitution and endogenously rising markups. In addition, production reallocates toward firms that use software more intensively, as they become effectively more productive. Because in the data these firms have higher markups and lower labor shares, the reallocation further raises the aggregate markup and reduces the aggregate labor share. The rise of software accounts for two-thirds of the labor share decline in Korea between 1990 and 2018. The factor substitution and the markup channels are equally important. On the other hand, the falling equipment price plays a minor role, because the factor substitution and the markup channels offset each other…(More)”.

Artificial Intelligence and the Skill Premium

Curated on Posted on by Stefaan Verhulst

Paper by David E. Bloom et al: “How will the emergence of ChatGPT and other forms of artificial intelligence (AI) affect the skill premium? To address this question, we propose a nested constant elasticity of substitution production function that distinguishes among three types of capital: traditional physical capital (machines, assembly lines), industrial robots, and AI. Following the literature, we assume that industrial robots predominantly substitute for low-skill workers, whereas AI mainly helps to perform the tasks of high-skill workers. We show that AI reduces the skill premium as long as it is more substitutable for high-skill workers than low-skill workers are for high-skill workers…(More)”

The Formalization of Social Precarities

Curated on Posted on by Stefaan Verhulst

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

Curated on Posted on by Stefaan Verhulst

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

Curated on Posted on by Stefaan Verhulst

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)”.