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. 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 propose several concrete policies that could promote shared prosperity through the advancement of generative AI. This article emphasizes the need for interdisciplinary collaborations to understand and address the complex challenges of generative AI.

Endogenous testosterone is associated with increased striatal response to audience effects during prosocial choices.

The role of testosterone on cognitive functions in humans remains controversial. One recent hypothesis suggests that this steroid hormone advances social status. As being observed by others is known to modulate a range of behaviors because of image concerns, we hypothesized that such an audience effect might be an important component of status seeking that is under the control of testosterone. Thus, we investigated to which extent testosterone levels are associated with the effect of being observed during prosocial choices and the neural mechanisms underlying this effect. We enrolled twenty-four male participants, aged 22.47 ± 2.62 years, in an fMRI experiment to examine the relationship between testosterone levels and brain activity engaged in deciding whether to accept or reject monetary transfers to two types of organizations (a positively evaluated organization and a negatively evaluated organization) in presence or absence of an audience. When comparing the public to the private condition, the rate of acceptance increased for the positively evaluated organization, while the rate of rejection increased for the negatively evaluated one. Higher testosterone levels were linked to greater activation in the striatum in the public compared to the private condition, regardless of the organization type. These results indicate a relationship between testosterone levels and striatal activity induced by the audience effect. These findings provide new insights on the role of testosterone in human social behavior.

Neurocomputational mechanisms at play when weighing concerns for extrinsic rewards, moral values, and social image.

Humans not only value extrinsic monetary rewards but also their own morality and their image in the eyes of others. Yet violating moral norms is frequent, especially when people know that they are not under scrutiny. When moral values and monetary payoffs are at odds, how does the brain weigh the benefits and costs of moral and monetary payoffs? Here, using a neurocomputational model of decision value (DV) and functional (f)MRI, we investigated whether different brain systems are engaged when deciding whether to earn money by contributing to a "bad cause" and when deciding whether to sacrifice money to contribute to a "good cause," both when such choices were made privately or in public. Although similar principles of DV computations were used to solve these dilemmas, they engaged 2 distinct valuation systems. When weighing monetary benefits and moral costs, people were willing to trade their moral values in exchange for money, an effect accompanied by DV computation engaging the anterior insula and the lateral prefrontal cortex (PFC). In contrast, weighing monetary costs against compliance with one's moral values engaged the ventral putamen. Moreover, regardless of the type of dilemma, a brain network including the anterior cingulate cortex (ACC), anterior insula, and the right temporoparietal junction (TJP) was more engaged in public than in private settings. Together, these findings identify how the brain processes three sources of motivation: extrinsic rewards, moral values, and concerns for image.