Can artificial intelligence (AI) help address the social and behavioral challenges fueling the climate crisis? At first glance, AI appears more likely to exacerbate the problem. The explosion of large-scale AI models — especially those generating human-like text and high-quality images — could strengthen the control of large corporations with little climate accountability 14, 24, the very entities responsible for a significant portion of carbon emissions 23, 54, 62. AI could be weaponized to propagate false narratives about climate change, threatening to further polarize the public 22, 30•. On top of that, training large AI models requires vast amounts of energy, contributing to carbon emissions in its own right 35, 37, 63.

In light of these challenges, are there any ways AI can help rather than harm? We believe it could — if used as a tool to better understand the psychology of climate policymaking. Understanding how people reason about climate policies raises new psychological questions and offers a high-impact opportunity for psychologists to support progress on climate change.

Psychologists have increasingly turned their attention to climate policy, making important progress in understanding what shapes public support and what drives resistance and polarization 19, 53, 67, 68. This includes factors such as political identity [19], social norms [12], elite cues [53], and perceived fairness [38]. In this article, we highlight how AI can help advance this research by: (a) improving our understanding of the psychological factors that influence responses to policy solutions, (b) enhancing public understanding by clarifying complex climate policies in accessible ways, and (c) ultimately, helping to develop more human-centric climate policies informed by how people think and behave.

Policy is one of the most powerful levers for tackling climate change, yet its success depends on understanding human behavior and public opinion [67]. For example, even though policies like carbon taxes, renewable energy subsidies, and public transportation investments are proven mechanisms for reducing emissions 10, 26, 44, they are notoriously difficult to implement. While opposition to such policies frequently stems from powerful interest groups benefiting from the status quo 23, 62, a substantial barrier lies in the public’s disagreement over the best course of action 9•, 19, 48.

Importantly, public resistance is not only driven by partisanship but also by crucial factors such as fairness and perceptions of who bears the costs of action [16]. Such concerns cut across ideological lines and can fuel backlash even against well-intentioned policies 39, 42, 59, 61. Understanding these beliefs is essential for designing policies that are not only effective but also responsive to public concerns and more likely to gain broad support.

Psychologists are well-positioned to help address this challenge. But doing so effectively requires deeper engagement with both policymakers — who shape and implement interventions — and social scientists, who can help contextualize behavioral insights in real-world settings. These collaborations can inform strategies to improve policy acceptance and increase the chances of successful implementation [21]. In the remainder of this article, we examine how AI tools can advance this interdisciplinary effort. Rather than replacing existing psychological research, we argue that AI can enhance it by identifying patterns in public reasoning at scale, generating and testing new policy framings, and aiding deliberative processes that can reveal common ground.