6.2Increased inequality and decline in employment quality

05.12.00Labor displacement - Economic impact

The literature frequently highlights concerns that generative AI systems could adversely impact the economy, potentially even leading to mass unemployment. This pertains to various fields, ranging from customer services to software engineering or crowdwork platforms. While new occupational fields like prompt engineering are created, the prevailing worry is that generative AI may exacerbate socioeconomic inequalities and lead to labor displacement. Additionally, papers debate potential large-scale worker deskilling induced by generative AI, but also productivity gains contingent upon outsourcing mundane or repetitive tasks to generative AI systems.

09.02.06Inequality of wealth

"Because a single human actor controlling an artificially intelligent agent will be able to harness greater power than a single human actor, this may create inequalities of wealth"

09.03.01Direct competition with humans

"One or more artificial agent(s) could have the capacity to directly outcompete humans, for example through capacity to perform work faster, better adaptation to change, vaster knowledge base to draw from, etc. This may result in human labor becoming more expensive or less effective than artificial labor, leading to redundancies or extinction of the human labor force."

09.04.01Competing for jobs

"AI agents may compete against humans for jobs, though history shows that when a technology replaces a human job, it creates new jobs that need more skills."

10.04.00Usurpation of jobs by automation

"Eliminated jobs in various types of companies."

13.01.07Data and Content Moderation Labor

"Two key ethical concerns in the use of crowdwork for generative AI systems are: crowdworkers are frequently subject to working conditions that are taxing and debilitative to both physical and mental health, and there is a widespread deficit in documenting the role crowdworkers play in AI development. This contributes to a lack of transparency and explainability in resulting model outputs. Manual review is necessary to limit the harmful outputs of AI systems, including generative AI systems. A common harmful practice is to intentionally employ crowdworkers with few labor protections, often taking advantage of highly vulnerable workers, such as refugees [119, p. 18], incarcerated people [54], or individuals experiencing immense economic hardship [98, 181]. This precarity allows a myriad of harmful practices, such as companies underpaying or even refusing to pay workers for completed work (see Gray and Suri [93, p. 90] and Berg et al. [29, p. 74]), with no avenues for worker recourse. Finally, critical aspects of crowdwork are often left poorly documented, or entirely undocumented [88]."

16.06.02Increasing inequality and negative effects on job quality

"Advances in LMs and the language technologies based on them could lead to the automation of tasks that are currently done by paid human workers, such as responding to customer-service queries, with negative effects on employment [3, 192]."

17.06.02Increasing inequality and negative effects on job quality

"Advances in LMs, and the language technologies based on them, could lead to the automation of tasks that are currently done by paid human workers, such as responding to customer-service queries, translating documents or writing computer code, with negative effects on employment."

18.06.03Inequality and precarity

"Amplifying social and economic inequality, or precarious or low-quality work"

18.06.05Exploitative data sourcing and enrichment

"Perpetuating exploitative labour practices to build AI systems (sourcing, user testing)"

19.03.00Economic AI Risks

"In the context of economic AI risks two major risks dominate. These refer to the disruption of the economic system due to an increase of AI technologies and automation. For instance, a higher level of AI integration into the manufacturing industry may result in massive unemployment, leading to a loss of taxpayers and thus negatively impacting the economic system (Boyd & Wilson, 2017; Scherer, 2016). This may also be associated with the risk of losing control and knowledge of organisational processes as AI systems take over an increasing number of tasks, replacing employees in these processes. "

19.03.02Replacement of humans and unemployment due to AI automation

19.04.00Social AI Risks

"Social AI risks particularly refer to loss of jobs (technological unemployment) due to increasing automation, reflected in a growing resistance by employees towards the integration of AI (Thierer et al., 2017; Winfield & Jirotka, 2018). In addition, the increasing integration of AI systems into all spheres of life poses a growing threat to privacy and to the security of individuals and society as a whole (Winfield & Jirotka, 2018; Wirtz et al., 2019)."

19.04.01Increasing social inequality

20.03.01Workforce substitution and transformation

"Frey and Osborne (2017) analyzed over 700 different jobs regarding their potential for replacement and automation, finding that 47 percent of the analyzed jobs are at risk of being completely substituted by robots or algorithms. This substitution of workforce can have grave impacts on unemployment and the social status of members of society (Stone et al., 2016)"

24.04.03Economic Harms

"These harms pertain to an individual’s or group’s economic standing. At the individual level, such harms include adverse impacts on an individual’s income, job quality or employment status. At the group level, such harms include deepening inequalities between groups or frustrating a group’s access to resources. Advanced AI assistants could cause economic harm by controlling, limiting or eliminating an individual’s or society’s ability to access financial resources, money or financial decision-making, thereby influencing an individual’s ability to accumulate wealth.

31.07.00Labor Manipulation, Theft, and Displacement

Major tech companies have also been the dominant players in developing new generative AI systems because training generative AI models requires massive swaths of data, computing power, and technical and financial resources. Their market dominance has a ripple effect on the labor market, affecting both workers within these companies and those implementing their generative AI products externally. With so much concentrated market power, expertise, and investment resources, these handful of major tech companies employ most of the research and development jobs in the generative AI field. The power to create jobs also means these tech companies can slash jobs in the face of economic uncertainty. And externally, the generative AI tools these companies develop have the potential to affect white-collar office work intended to increase worker productivity and automate tasks

31.07.02Job Automation Instead of Augmentation

"There are both positive and negative aspects to the impact of AI on labor. A White House report states that AI “has the potential to increase productivity, create new jobs, and raise living standards,” but it can also disrupt certain industries, causing significant changes, including job loss. Beyond risk of job loss, workers could find that generative AI tools automate parts of their jobs—or find that the requirements of their job have fundamentally changed. The impact of generative AI will depend on whether the technology is intended for automation (where automated systems replace human work) or augmentation (where AI is used to aid human workers). For the last two decades, rapid advances in automation have resulted in a “decline in labor share, stagnant wages[,] and the disappearance of good jobs in many advanced economies.”

31.07.03Devaluation of Labor & Heightened Economic Inequality

"According to a White House report, much of the development and adoption of AI is intended to automate rather than augment work. The report notes that a focus on automation could lead to a less democratic and less fair labor market...In addition, generative AI fuels the continued global labor disparities that exist in the research and development of AI technologies... The development of AI has always displayed a power disparity between those who work on AI models and those who control and profit from these tools. Overseas workers training AI chatbots or people whose online content has been involuntarily fed into the training models do not reap the enormous profits that generative AI tools accrue. Instead, companies exploiting underpaid and replaceable workers or the unpaid labor of artists and content creators are the ones coming out on top. The development of generative AI technologies only contributes to this power disparity, where tech companies that heavily invest in generative AI tools benefit at the expense of workers.

33.04.01Labor market

"The labor market can face challenges from generative AI. As mentioned earlier, generative AI could be applied in a wide range of applications in many industries, such as education, healthcare, and advertising. In addition to increasing productivity, generative AI can create job displacement in the labor market (Zarifhonarvar, 2023). A new division of labor between humans and algorithms is likely to reshape the labor market in the coming years. Some jobs that are originally carried out by humans may become redundant, and hence, workers may lose their jobs and be replaced by algorithms (Pavlik, 2023). On the other hand, applying generative AI can create new jobs in various industries (Dwivedi et al., 2023). To stay competitive in the labor market, reskilling is needed to work with and collaborate with AI and develop irreplaceable advantages (Zarifhonarvar, 2023)."