The impact of generative artificial intelligence on socioeconomic inequalities and policy making

Generative artificial intelligence (AI) 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 potential impacts of generative AI on (mis)information and three information-intensive domains: work, education, and healthcare. Our goal is to highlight how generative AI could worsen existing inequalities while illuminating how AI may help mitigate pervasive social problems. In the information domain, generative AI can democratize content creation and access but may dramatically expand the production and proliferation of misinformation. In the workplace, it 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 might improve diagnostics and accessibility, but could deepen pre-existing inequalities. In each section, we cover a specific topic, evaluate existing research, identify critical gaps, and recommend research directions, including explicit trade-offs that complicate the derivation of a priori hypotheses. We conclude with a section highlighting the role of policymaking to maximize generative AI's potential to reduce inequalities while mitigating its harmful effects.

Advances in generative artificial intelligence (AI) represent a shift in the capability of these systems to solve problems previously thought unsolvable. Techno-optimists predict a utopian future where machines can perform an ever-increasing number of tasks—but humans remain in control, the gains from prosperity are shared throughout society, and we all enjoy lives with less work and more leisure. In contrast, pessimists forecast a dystopian future where machines not only replace humans in the workplace but also surpass human capability and oversight, destabilize institutions, and destroy livelihoods—and perhaps even cause the downfall of humanity. Melvin Kranzberg, a prominent scholar in the history of technology, defined "Kranzberg's Laws," the first of which states that "Technology is neither good nor bad; nor is it neutral." This principle suggests that technologies like generative AI will likely have negative and positive impacts on society, though they are not inherently predestined toward either.

Both optimists and pessimists agree that generative AI represents a qualitative departure from previous automation processes, such as microelectronics, information technology, and the Internet. Unlike traditional automation, which primarily focuses on replicating predefined tasks, generative AI introduces the ability to create new, original output. The implications have the potential to reshape foundational values and skills. For instance, while generative AI might facilitate written communication, especially for non-native speakers, it could devalue foundational language learning. The incentives to master syntax, vocabulary, and grammar might wane as generative AI begins to exceed the skill level of humans. This shift reflects a broader theme: generative AI does not merely alter practices but fundamentally transforms the valuation of knowledge and skills.

We have focused on the socioeconomic inequalities that are likely to be impacted—for better or worse—by the advent of generative AI. This technology has profound implications in the domain of information, where it has the potential to offer more tailored, efficient, and democratic ways to process information. Yet it also poses several challenges, including anticompetitive market advantages, data misuse and abuse, and misinformation. These mixed outcomes will certainly affect a very wide range of social organization and decision making. We have outlined several research questions that urgently require answers to address these issues effectively. Additionally, we have observed that current regulatory approaches in the European Union, United States, and United Kingdom sometimes fail to adequately address these challenges. There is a need for a dynamic regulatory framework that can keep pace with the rapid advancements in AI technology. As we stand at the cusp of this new era of human–machine interactions, it is crucial that we engage in thoughtful and inclusive discussions about the role of AI in shaping our society, because the decisions we make today will have lasting impacts on generations to come.