PLOS Climate PhD interview: Caroline Pioger

In our latest interview with a PhD student in climate, PLOS Climate speaks to Caroline Pioger of the Ecole Normale Supérieure, Paris, France.

What did you study before your PhD, and why did you decide to go on to do a PhD?

Before starting my PhD in Cognitive Sciences, I followed a somewhat sinuous academic path. I first completed a Bachelor’s and a Master’s degree in Mathematics at University College London. Although I loved mathematics, I increasingly wanted to work on questions with a more direct connection to the real world. This led me to pursue a Master’s in Cognitive Sciences (jointly run by École normale supérieure, Université Paris Cité, and École des hautes études en sciences sociales), a field focused on studying how the mind works. I was quickly fascinated by the field and how deeply relevant it is for tackling many societal challenges such as sustainability and climate change.

However, like many students, I struggled with imposter syndrome and spent a long time convinced that I wasn’t “smart enough” to pursue a PhD, so I didn’t even consider it. It was only after spending some time outside academia that I realised how much I missed academic research. Research was the one environment where I felt stimulated and where work felt meaningful.

What ultimately drew me toward a PhD was the core idea that research contributes to a collective effort to understand the world. Academia is far from perfect: it comes with its own pressures, competition, and incentives that can be frustrating. Yet, at its core, it remains a place where people work together to build knowledge, and that is something I find deeply motivating.

Finding a PhD that combined my interests in cognitive science and sustainability was another challenge. Despite the growing importance of understanding the human dimensions of climate action, opportunities at the intersection of these fields were relatively rare in Paris, where I wanted to stay. I was fortunate to find my current supervisor, who allowed me to explore these questions through the lens of reinforcement learning and decision-making.

Could you tell us about your project? What are the key questions you’re hoping to address, and what methods/approaches are you using?

My PhD project is in Cognitive Sciences, an interdisciplinary field that seeks to understand how people perceive, learn, reason, remember, make decisions, etc. More specifically, I study learning processes and decision-making. A central question in my research is how to correct misconceptions people have about environmental matters and how these beliefs, once updated, influence their preferences and behaviour. Many people hold misconceptions about environmental information: for instance, they underestimate the effectiveness of switching to a sustainable diet, misperceive their own carbon footprint or underestimate how much other people also support climate action. One misconception we investigated concerns how accurately people estimate the environmental and health impacts of different energy sources. These misconceptions matter because people’s beliefs about the world influence the choices they make and the policies they support.

While providing accurate information may seem straightforward, decades of research show that people do not always update their beliefs in a rational way. Understanding the cognitive mechanisms behind belief updating is therefore essential for explaining how people form opinions, preferences, and ultimately make decisions that impact the environment.

To investigate these questions, I draw on reinforcement learning, a framework that models how people learn from experience and feedback. When we try a new behaviour and experience its consequences, we update our beliefs based on how rewarding or upsetting it is. For example, if I try a plant-based patty and find it delicious, I might revise my assumption that sustainable food is less enjoyable.

In my PhD, I apply these principles in an experimental intervention: We ask participants questions, present them with two choices, and reveal the correct answer after they make their selection. Although the task is simple, it allows us to study the complex ways in which learning processes shape preferences and behaviour. Using computational models, we predict which misconception corrections lead to the greatest shifts in what participants prefer or want to do. I therefore combine quantitative methods from psychology, behavioural economics, and computational modelling. These theoretical models of learning and decision-making help identify strategies that can encourage more informed and environmentally sustainable choices, as environmental transitions depend on millions of individual and collective decisions.

What excites you most about your project, and about the wider field?

What excites me most about my project is the opportunity to contribute, in a small way, to understanding one aspect of the climate challenge that deserves attention: the human side of climate action.

When we think about climate change, we often focus on physical sciences or economic policies. These are obviously essential. But ultimately, climate change is a human-created problem, so we must also understand the human side to design effective solutions. For example, by studying what prevents people from believing in climate change, how they make consumption-related decisions, what kind of scientific information they trust, how they coordinate collective actions, among many other things. My PhD project focuses on a specific aspect of how people update their incorrect beliefs about sustainability-related matters, but many other human-related projects remain to be explored. This is why I find cognitive science particularly exciting within sustainability research.

Discussions about climate action are often framed as a debate between individual responsibility and structural change. However, I don’t find that distinction particularly useful, as both should happen hand in hand. Individuals make decisions within social, economic, and political systems, and those systems are themselves shaped by human decisions. Cognitive science can help us better shed light on these interactions, while being careful not to put responsibility solely on individuals. More broadly, I find it exciting to see cognitive science increasingly engaging with real-world challenges. Understanding how people think and behave is interesting in itself, but it becomes even more meaningful when those insights can contribute to addressing societal issues (climate change, but also gender and racial discrimination, health behaviors and others).

What are you hoping to gain through the experience of doing a PhD?

As a first-year PhD student, I am still at the beginning of my research journey, and there is a lot I hope to learn and discover. On a practical level, I want to strengthen my computational skills and develop the tools needed to conduct rigorous research, as I would like to remain in academia after my PhD.

Beyond technical skills, I also see the PhD as a formative period for developing my own way of doing research. This includes learning how to communicate ideas clearly and effectively, how to collaborate efficiently with others, and how to balance focus on specific projects with a broader vision. But one aspect I’m particularly interested in is finding the right balance between intellectual humility and self-confidence. Questioning oneself is crucial in scientific work, but too much self-doubt can turn into hesitation rather than productive reflection. How can we cultivate humility without letting it paralyze us? This question may be particularly relevant for people who face social stereotypes that can undermine confidence, including many women and other underrepresented groups in academia.

So, beyond the classical scientific rigor expected in a PhD, I hope this experience will help me develop these interpersonal skills that are just as important for an academic career.

What are your thoughts on the future of climate research? 

From the perspective of cognitive science, I think one of the most important challenges for climate research is moving from understanding cognitive processes to designing interventions that can foster meaningful real-world change. Over the last decades, cognitive scientists have developed a sophisticated understanding of the mechanisms underlying human behaviour. The question now is how we can use this knowledge to design and test interventions that are effective outside the laboratory.

Known as behavioural interventions, this line of research seeks to apply insights from cognitive and behavioural sciences to address real-world challenges. Many environmental problems are not only constrained by structural and contextual factors, but also by psychological factors such as misconceptions, habits or risk perceptions. By understanding these cognitive and behavioural processes, researchers can help design and implement public policies that make sustainable choices easier and more effective.

In my PhD project, we designed and tested an intervention that improves understanding of environmental impact, but these interventions can take other forms such as shaping behavioural incentives through social norms. That said, we must also consider the social context: for example, focusing on individuals or groups with the greatest influence or impact, such as high emitters or decision-makers, who may have more opportunities to drive meaningful change.

Overall, this shift is critical because the gap between knowledge and real-world action remains one of the biggest barriers to sustainable transitions. To me, this is where cognitive science can make its most promising and meaningful contributions to climate research.