Thursday, September 12, 2024

An exit for even the deepest rabbit holes: Personalized conversations with chatbot reduce belief in conspiracy theories

Summary author: Walter Beckwith

American Association for the Advancement of Science (AAAS)

Personalized conversations with a trained artificial intelligence (AI) chatbot can reduce belief in conspiracy theories – even in the most obdurate individuals – according to a new study. The findings, which challenge the idea that such beliefs are impervious to change, point to a new tool for combating misinformation. “It has become almost a truism that people ‘down the rabbit hole’ of conspiracy belief are almost impossible to reach,” write the authors. “In contrast to this pessimistic view, we [show] that a relatively brief conversation with a generative AI model can produce a large and lasting decrease in conspiracy beliefs, even among people whose beliefs are deeply entrenched.” Conspiracy theories – beliefs that some secret but influential malevolent organization is responsible for an event or phenomenon – are notoriously persistent and pose a serious threat to democratic societies. Yet despite their implausibility, a large fraction of the global population has come to believe in them, including as much as 50% of the United States population by some estimates. The persistent belief in conspiracy theories despite clear counterevidence is often explained by social-psychological processes that fulfill psychological needs and by the motivation to maintain identity and group memberships. Current interventions to debunk conspiracies among existing believers are largely ineffective.

Thomas Costello and colleagues investigated whether Large Language Models (LLMs) like GPT-4 Turbo can effectively debunk conspiracy theories by using their vast information access and by using tailored counterarguments that respond directly to specific evidence presented by believers. In a series of experiments encompassing 2,190 conspiracy believers, participants engaged in several personalized interactions with an LLM, sharing their conspiratorial beliefs and the evidence they felt supported them. In turn, the LLM responded by directly refuting these claims through tailored, factual and evidence-based counterarguments. A professional fact-checker hired to evaluate the accuracy of the claims made by GPT-4 Turbo reported that, of these claims, 99.2% were rated as “true,” 0.8% as “misleading,” and 0 as “false”; and none were found to contain liberal or conservative bias. Costello et al. found that these AI-driven dialogues reduced participants’ misinformed beliefs by an average of 20%. This effect lasted for at least 2 months and was observed across various unrelated conspiracy theories, as well as across demographic categories. According to the authors, the findings challenge the idea that evidence and arguments are ineffective once someone has adopted a conspiracy theory. They also question social-psychological theories that focus on psychological needs and motivations as the main drivers of conspiracy beliefs. “For better or worse, AI is set to profoundly change our culture,” write Bence Bago and Jean-François Bonnefon in a related Perspective. “Although widely criticized as a force multiplier for misinformation, the study by Costello et al. demonstrates a potential positive application of generative AI’s persuasive power.”

A version of the chatbot referenced in this paper can be visited at https://www.debunkbot.com/conspiracies.

***A related embargoed news briefing was held on Tuesday, 10 September, as a Zoom Webinar. Recordings can be found at the following links:

The passcode for both is &M67bgdd

Journal

Science

DOI

10.1126/science.adq1814

Article Title

Durably reducing conspiracy beliefs through dialogues with AI

Article Publication Date

13-Sep-2024

Can AI talk us out of conspiracy theories?

New MIT Sloan research shows that conversations with large language models can successfully reduce belief in conspiracy theories

Peer-Reviewed Publication

MIT Sloan School of Management

Have you ever tried to convince a conspiracy theorist that the moon landing wasn’t staged? You likely didn’t succeed, but ChatGPT might have better luck, according to research by MIT Sloan School of Management professor David Rand and American University professor of psychology Thomas Costello, who conducted the research during his postdoctoral position at MIT Sloan.

In a new paper “Durably reducing conspiracy beliefs through dialogues with AI” published in Science, the researchers show that large language models can effectively reduce individuals’ beliefs in conspiracy theories — and that these reductions last for at least 2 months — a finding that offers new insights into the psychological mechanisms behind the phenomenon as well as potential tools to fight the spread of conspiracies.

Going down the rabbit hole

Conspiracy theories — beliefs that certain events are the result of secret plots by influential actors — have long been a subject of fascination and concern. Their persistence in the face of counter-evidence has led to the conclusion that they fulfill deep-seated psychological needs, rendering them impervious to facts and logic. According to this conventional wisdom, once someone “falls down the rabbit hole,” it’s virtually impossible to pull them back out.

But for Rand, Costello, and their co-author professor Gordon Pennycook from Cornell University, who have conducted extensive research on the spread and uptake of misinformation, that conclusion didn’t ring true. Instead, they suspected a simpler explanation was at play.

“We wondered if it was possible that people simply hadn’t been exposed to compelling evidence disproving their theories,” Rand explained. “Conspiracy theories come in many varieties — the specifics of the theory and the arguments used to support it differ from believer to believer. So if you are trying to disprove the conspiracy but haven’t heard these particular arguments, you won’t be prepared to rebut them.”

Effectively debunking conspiracy theories, in other words, would require two things: personalized arguments and access to vast quantities of information — both now readily available through generative AI.

Conspiracy conversations with GPT4

To test their theory, Costello, Pennycook, and Rand harnessed the power of GPT-4 Turbo, OpenAI’s most advanced large language model, to engage over 2,000 conspiracy believers in personalized, evidence-based dialogues.

The study employed a unique methodology that allowed for deep engagement with participants' individual beliefs. Participants were first asked to identify and describe a conspiracy theory they believed in using their own words, along with the evidence supporting their belief.

GPT-4 Turbo then used this information to generate a personalized summary of the participant's belief and initiate a dialogue. The AI was instructed to persuade users that their beliefs were untrue, adapting its strategy based on each participant’s unique arguments and evidence.

These conversations, lasting an average of 8.4 minutes, allowed the AI to directly address and refute the specific evidence supporting each individual’s conspiratorial beliefs, an approach that was impossible to test at scale prior to the technology’s development.

A significant — and durable — effect

The results of the intervention were striking. On average, the AI conversations reduced the average participant's belief in their chosen conspiracy theory by about 20%, and about 1 in 4 participants — all of whom believed the conspiracy beforehand — disavowed the conspiracy after the conversation. This impact proved durable, with the effect remaining undiminished even two months post-conversation.

The AI conversation’s effectiveness was not limited to specific types of conspiracy theories. It successfully challenged beliefs across a wide spectrum, including conspiracies that potentially hold strong political and social salience, like those involving COVID-19 and fraud during the 2020 U.S. presidential election.

While the intervention was less successful among participants who reported that the conspiracy was central to their worldview, it did still have an impact, with little variance across demographic groups.

Notably, the impact of the AI dialogues extended beyond mere changes in belief. Participants also demonstrated shifts in their behavioral intentions related to conspiracy theories. They reported being more likely to unfollow people espousing conspiracy theories online, and more willing to engage in conversations challenging those conspiratorial beliefs.

The opportunities and dangers of AI

Costello, Pennycook, and Rand are careful to point to the need for continued responsible AI deployment since the technology could potentially be used to convince users to believe in conspiracies as well as to abandon them.

Nevertheless, the potential for positive applications of AI to reduce belief in conspiracies is significant. For example, AI tools could be integrated into search engines to offer accurate information to users searching for conspiracy-related terms.

“This research indicates that evidence matters much more than we thought it did — so long as it is actually related to people’s beliefs,” Pennycook said. “This has implications far beyond just conspiracy theories: Any number of beliefs based on poor evidence could, in theory, be undermined using this approach.”

Beyond the specific findings of the study, its methodology also highlights the ways in which large language models could revolutionize social science research, said Costello, who noted that the researchers used GPT-4 Turbo to not only conduct conversations but also to screen respondents and analyze data.

“Psychology research used to depend on graduate students interviewing or conducting interventions on other students, which was inherently limiting,” Costello said. “Then, we moved to online survey and interview platforms that gave us scale but took away the nuance. Using artificial intelligence allows us to have both.”

These findings fundamentally challenge the notion that conspiracy believers are beyond the reach of reason. Instead, they suggest that many are open to changing their views when presented with compelling and personalized counter-evidence.

“Before we had access to AI, conspiracy research was largely observation and correlational, which led to theories about conspiracies filling psychological needs,” said Costello. “Our explanation is more mundane — much of the time, people just didn’t have the right information.”

Journal

Science

Method of Research

Experimental study

Subject of Research

People

Article Title

Durably reducing conspiracy beliefs through dialogues with AI

Article Publication Date

12-Sep-2024

‘Even the deepest of rabbit holes may have an exit’

Pathbreaking study led by American University professor reveals conversations with AI models can reduce conspiracy theory beliefs

Peer-Reviewed Publication

American University

‘Even the deepest of rabbit holes may have an exit’

Pathbreaking psychology study reveals conversations with AI models can reduce conspiracy theory beliefs

(WASHINGTON, D.C.) Sept. 12, 2024 – ‘They’re so far down the rabbit hole of conspiracy theories that they’re lost for good’ is common thinking when it comes to conspiracy theorists. This generally accepted notion is now crumbling.

In a pathbreaking research study, a team of researchers from American University, Massachusetts Institute of Technology and Cornell University show that conspiracy theorists changed their views after short conversations with artificial intelligence. Study participants believing some of the most deeply entrenched conspiracies, including those about the COVID-19 pandemic and fraud in the 2020 U.S. presidential election, showed large and lasting reductions in conspiracy belief following the conversations.

Stoked by polarization in politics and fed by misinformation and social media, conspiracy theories are a major issue of public concern. They often serve as a wedge between theorists and their friends and family members. YouGov survey results from last December show that large shares of Americans believe various conspiratorial falsehoods.

In the field of psychology, the widespread view the findings challenge is that conspiracy theorists adhere to their beliefs because of the significance to their identities, and because the beliefs resonate with underlying drives and motivations, says Thomas Costello, assistant professor of psychology at American University and lead author of the new study published in the journal Science[MOU1] . In fact, most approaches have focused on preventing people from believing conspiracies in the first place.

“Many conspiracy believers were indeed willing to update their views when presented with compelling counterevidence,” Costello said. “I was quite surprised at first, but reading through the conversations made much me less skeptical. The AI provided page-long, highly detailed accounts of why the given conspiracy was false in each round of conversation -- and was also adept at being amiable and building rapport with the participants.”

More than 2,000 self-identified conspiracy believers participated in the study. The AI conversations reduced the average participant's belief in their chosen conspiracy theory by about 20 percent, and about 1 in 4 participants — all of whom believed the conspiracy beforehand — disavowed the conspiracy after the conversation.

Until now, delivering persuasive, factual messages to a large sample of conspiracy theorists in a lab experiment has proved challenging. For one, conspiracy theorists are often highly knowledgeable about the conspiracy—often more so than skeptics. Conspiracies also vary widely, such that evidence backing a particular theory can differ from one believer to another.

AI as an intervention

The new study comes as society debates the promise and peril of AI. Large language models driving generative AI are powerful reservoirs of knowledge. Researchers emphasize that the study demonstrates one way that these reservoirs of knowledge can be used for good: by helping people have more accurate beliefs. The ability of artificial intelligence to connect across diverse topics of information within seconds makes it possible to tailor counterarguments to specific conspiracies of a believer in ways that aren’t possible for a human to do.

“Previous efforts to debunk dubious beliefs have a major limitation: One needs to guess what people’s actual beliefs are in order to debunk them – not a simple task,” said Gordon Pennycook, associate professor of psychology at Cornell University and a paper co-author. “In contrast, the AI can respond directly to people’s specific arguments using strong counterevidence. This provides a unique opportunity to test just how responsive people are to counterevidence.”

Researchers designed the chatbot to be highly persuasive and engage participants in such tailored dialogues. GPT-4, the AI model powering ChatGPT, provided factual rebuttals to participants’ conspiratorial claims. In two separate experiments, participants were asked to describe a conspiracy theory they believe in and provide evidence to support. Participants then engaged in a conversation with an AI. The AI's goal was to challenge beliefs by addressing specific evidence. In a control group, participants discussed an unrelated topic with the AI.

To tailor the conversations, researchers provided the AI with participants’ initial statement of belief and the rationale. This setup allowed for a more natural dialogue, with the AI directly addressing a participant's claims. The conversation averaged 8.4 of the participant's minutes and involved three rounds of interaction, excluding the initial setup. Ultimately, both experiments showed a reduction in participants' beliefs in conspiracy theories. When the researchers assessed participants two months later, they found that the effect persisted.

While the results are promising and suggest a future in which AI can play a role in diminishing conspiracy belief when used responsibly, further studies on long-term effects, using different AI models, and practical applications outside of a laboratory setting will be needed.

“Although much ink has been spilled over the potential for generative AI to supercharge disinformation, our study shows that it can also be part of the solution,” said David Rand, a paper co-author and MIT Sloan School of Management professor. “Large language models like GPT4 have the potential to counter conspiracies at a massive scale.”

Additionally, members of the public interested in this ongoing work can visit a website and try out the intervention for themselves.

CONTACT: For more information, please contact Rebecca Basu, AU Communications, basu@american.edu or call (202)-885-5950

About American University  

American University leverages the power and purpose of scholarship, learning, and community to impact our changing world. AU’s faculty, students, staff, and alumni are changemakers who shape the future from sustainability to social justice to the sciences. Building on our 130-year history of education and research in the public interest, we say ‘Challenge Accepted’ to addressing the world’s pressing issues.

[MOU1]Insert link to study

Journal

Science

DOI

10.1126/science.adq1814

Subject of Research

People

Article Publication Date

12-Sep-2024

New research reveals how El Nino caused the greatest ever mass extinction

University of Bristol

Mega ocean warming El Niño events were key in driving the largest extinction of life on planet Earth some 252 million years ago, according to new research.

The study, published today in Science and co-led by the University of Bristol and China University of Geosciences (Wuhan), has shed new light on why the effects of rapid climate change in the Permian-Triassic warming were so devastating for all forms of life in the sea and on land.

Scientists have long linked this mass extinction to vast volcanic eruptions in what is now Siberia. The resulting carbon dioxide emissions rapidly accelerated climate warming, resulting in widespread stagnation and the collapse of marine and terrestrial ecosystems.

But what caused life on land, including plants and usually resilient insects, to suffer just as badly has remained a source of mystery.

Co-lead author Dr Alexander Farnsworth, Senior Research Associate at the University of Bristol, said: “Climate warming alone cannot drive such devastating extinctions because, as we are seeing today, when the tropics become too hot, species migrate to the cooler, higher latitudes. Our research has revealed that increased greenhouse gases don’t just make the majority of the planet warmer, they also increase weather and climate variability making it even more ‘wild’ and difficult for life to survive.”

The Permian-Triassic catastrophe shows the problem of global warming is not just a matter of it becoming unbearably hot, but also a case of conditions swinging wildly over decades.

“Most life failed to adapt to these conditions, but thankfully a few things survived, without which we wouldn’t be here today. It was nearly, but not quite, the end of the life on Earth,” said co-lead author Professor Yadong Sun at China University of Geosciences, Wuhan.

The scale of Permian-Triassic warming was revealed by studying oxygen isotopes in the fossilised tooth material of tiny extinct swimming organisms called conodonts. By studying the temperature record of conodonts from around the world, the researchers were able to show a remarkable collapse of temperature gradients in the low and mid latitudes.

Dr Farnsworth, who used pioneering climate modelling to evaluate the findings, said: “Essentially, it got too hot everywhere. The changes responsible for the climate patterns identified were profound because there were much more intense and prolonged El Niño events than witnessed today. Species were simply not equipped to adapt or evolve quickly enough.”

In recent years El Niño events have caused major changes in rainfall patterns and temperature. For example, the weather extremes that caused the June 2024 North American heatwave when temperatures were around 15°C hotter than normal. 2023-2024 was also one of the hottest years on record globally due to a strong El Niño in the Pacific, which was further exacerbated by increased human-induced CO2 driving catastrophic drought and fires around the world.

“Fortunately such events so far have only lasted one to two years at a time. During the Permian-Triassic crisis, El Niño persisted for much longer resulting in a decade of widespread drought, followed by years of flooding. Basically, the climate was all over the place and that makes it very hard for any species to adapt,” co-author Paul Wignall, Professor of Palaeoenvironments at the University of Leeds.

The results of the climate modelling also help explain the abundant charcoal found in rock layers of that age.

“Wildfires become very common if you have a drought-prone climate. Earth got stuck in a crisis state where the land was burning and the oceans stagnating. There was nowhere to hide,” added co-author Professor David Bond, a palaeontologist at the University of Hull.

The researchers observed that throughout Earth’s history there have been many volcanic events similar to those in Siberia, and many caused extinctions, but none led to a crisis of the scale of the Permian-Triassic event.

They found Permian-Triassic extinction was so different because these Mega-El Niños created positive feedback on the climate which led to incredibly warm conditions starting in the tropics and then beyond, resulting in the dieback of vegetation. Plants are essential for removing CO2 from the atmosphere, as well as the foundation of the food web, and if they die so does one of the Earth's mechanisms to stop CO2 building up in the atmosphere as a result of continued volcanism.

This also helps explain the conundrum regarding the Permian-Triassic mass extinction whereby the extinction on land occurred tens of thousands of years before extinction in the oceans.

“Whilst the oceans were initially shielded from the temperature rises, the mega-El Nino’s caused temperatures on land to exceed most species thermal tolerances at rates so rapid that they could not adapt in time,” explained Dr Sun.

“Only species that could migrate quickly could survive, and there weren’t many plants or animals that could do that.”

Mass extinctions, although rare, are the heartbeat of the Earth’s natural system resetting life and evolution along different paths.

“The Permo-Triassic mass extinction, although devastating, would ultimately see the rise of Dinosaurs becoming the dominant species thereafter as would the Cretaceous mass extinction lead to the rise of mammals, and humans,” Dr Farnsworth concluded.

Surface temperature (°C) of the warmest month during peak-warmth for the Permian-Triassic mass extinction 252 million years ago.

Credit

University of Bristol and China University of Geosciences (Wuhan)

Journal

Science

Article Title

Mega El Niño instigated the end-Permian mass extinction.

Article Publication Date

12-Sep-2024

Dams built to prevent coastal flooding can worsen it

University of Alaska Fairbanks

image:
The Pinopolis Lock is part of the flood control infrastructure built near Charleston, South Carolina.
view more
Credit: Courtesy of Santee Cooper

The common practice of building dams to prevent flooding can actually contribute to more intense coastal flood events, according to a new study.

The study, published in the Journal of Geophysical Research: Oceans, studied the effects of dams built in coastal estuaries, where rivers and ocean tides interact. Those massive infrastructure projects are surging in popularity globally, in part to help offset intensifying storms, salt intrusion and sea-level rise fueled by climate change.

By analyzing data and measurements from Charleston Harbor, South Carolina, dating back more than a century, researchers determined that coastal dams don’t necessarily mitigate flooding. Dams can either increase or decrease flood risks, depending on the duration of a surge event and friction from the flow of water.

“We usually think about storm surges becoming smaller as you go inland, but the shape of the basin can actually cause it to become larger,” said lead author Steven Dykstra, an assistant professor at the University of Alaska Fairbanks College of Fisheries and Ocean Sciences.

Estuaries are typically shaped like a funnel, narrowing as they go inland. Introducing a dam shortens the estuary with an artificial wall that reflects storm surge waves moving inland. The narrowing channel shape also makes small reflections that change with the surge duration. Dykstra compared those storm-fueled waves to splashes in a bathtub, with certain wave frequencies causing water to slosh over the sides.

After using Charleston Harbor as a case study, researchers used computer modeling to gauge the flood response at 23 other estuaries in diverse geographic areas. Those encompassed both dammed and naturally occurring estuary systems, including Cook Inlet in Alaska.

The models confirmed that the basin shape and alterations that shorten it with a dam are the key component in determining how storm surges and tides move inland. At the right amplitude and duration, waves in dammed environments grow instead of diminishing.

The study also determined that areas far from coastal dams could still be directly influenced by human-created infrastructure. In the Charleston area, the highest storm surges routinely occurred more than 50 miles inland.

“One of the scary things with this is that sometimes people don’t realize they are in a coastal-influenced zone,” Dykstra said. “Sea-level rise is making people far inland aware that they’re not free from coastal effects — and it usually happens with a massive flood.”

Other contributors to the study included Enrica Viparelli, Alexander Yankovsky and Raymond Torres from the University of South Carolina, and Stefan Talke from California Polytechnic State University, San Luis Obispo.

Journal

Journal of Geophysical Research Oceans

DOI

10.1029/2023JC020498

Article Title

Reflection of Storm Surge and Tides in Convergent Estuaries With Dams, the Case of Charleston, USA

Article Publication Date

11-Sep-2024

Crude oil decimates sea otter buoyancy

The Company of Biologists

Sea otters are famed for their luscious pelts, but the fur almost led to their extinction. By 1938, only a tiny population of ~50 remained clinging to the central California coast. Since then, the mammals have battled back; however, the charismatic creatures are still at risk from crude oil spilled by offshore rigs. But no one knew how severely crude oil impacts the buoyancy of sea otter fur or how well it recovers after cleaning. And Kate Riordan from California Polytechnic State University San Luis Obispo (Cal Poly SLO), USA, adds that the fur of newborn sea otter pups was also believed to be particularly buoyant, but no one had checked. Curious to answer these questions, Riordan joined forces with Nicole Thometz (University of San Francisco, USA), Francesca Batac [California Department of Fish and Wildlife (CDFW), USA] and Heather Liwanag (Cal Poly SLO) to investigate. They publish their discovery in Journal of Experimental Biology that crude oil pollution dramatically reduces sea otter fur buoyancy, placing pups at particular risk thanks to their larger surface area relative to their body mass, and that the buoyancy does not fully recover, even after cleaning.

Sea otters in the wild die naturally for many reasons and are collected by the CDFW – which monitors the health of the population – so they passed on sections of a few precious pelts from southern sea otters ranging in age from tiny pups up to 9-year-old adults to Riordan, Annika Dean and Sarah Kerr (both from Cal Poly SLO). After cleaning the pelt, the team then weighed a 25 cm2 portion from each in air and in water to determine the fur’s buoyancy. However, when they compared the buoyancy of the youngsters’ pelts with that of the fully grown adults, there was no difference. All of the sea otter fur portions had a buoyancy of ~0.3 N, about the same as a 10 g piece of cork, so a sea otter pup’s fur is no more buoyant than the fur of its parents. However, when the team calculated the impact of the fur’s buoyancy on the pups’ entire bodies, the youngsters’ fur was almost three times more buoyant for their body mass than that of the adults, thanks to the pups’ relatively large surface areas for their size. This allows the pups to trap more air for their smaller body mass to make them extremely buoyant and keep them bobbing at the surface while mum’s off hunting.

But how did a dousing of crude oil affect the fur’s buoyancy? This time, the team massaged crude oil into the fur, mimicking how sea otters groom naturally – inadvertently rubbing the pollution into their pelts – before measuring the oil-sodden fur’s buoyancy. Sure enough, the fur’s buoyancy plummeted by almost 55% to 0.145 N, making it much more difficult for the animals to remain afloat. The reduction in buoyancy coupled with the loss of insulation would almost certainly prove fatal in the wild.

Fortunately, conservationists swoop in quickly in the event of major crude oil spills, drenching oil-soaked creatures in detergent to rid them of the oil, but how well does the buoyancy of sea otter fur recover after cleaning? Riordan and colleagues gently washed each oiled pelt with Dawn® Ultra Dishwashing Liquid, before rinsing thoroughly, finishing with a blow-dry and remeasuring the pelt’s buoyancy. As they had hoped, the buoyancy of the fur improved, but only by 36% to 0.197 N, still almost 40% down from the fur’s natural buoyancy.

The team suspects that living sea otters may recover better after cleaning because they groom continually, but they suggest that it is essential that detergent is thoroughly rinsed off after cleaning to ensure that oiled sea otters recover fully.

********************************************

IF REPORTING THIS STORY, PLEASE MENTION JOURNAL OF EXPERIMENTAL BIOLOGY AS THE SOURCE AND, IF REPORTING ONLINE, PLEASE CARRY A LINK TO: https://journals.biologists.com/jeb/article-lookup/doi/10.1242/jeb.247134

REFERENCE: Riordan, K., Dean, A. E., Kerr, S. J., Thometz, N. M., Batac, F. I. and Liwanag, H. E. M. (2024). A novel comparison of southern sea otter (Enhydra lutris nereis) fur buoyancy across ontogeny. J. Exp. Biol. 227, jeb247134. doi:10.1242/jeb.247134

DOI:10.1242/jeb.249406

Registered journalists can obtain a copy of the article under embargo from http://pr.biologists.com. Unregistered journalists can register at http://pr.biologists.com to access the embargoed content. The embargoed article can also be obtained from Jarren Kay (JEBNewsandViews@biologists.com)

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Journal

Journal of Experimental Biology

DOI

10.1242/jeb.249406

Method of Research

Experimental study

Subject of Research

Animals

Article Title

A novel comparison of southern sea otter (Enhydra lutris nereis) fur buoyancy across ontogeny

Article Publication Date

12-Sep-2024

Personal carbon footprint of the rich is vastly underestimated by rich and poor alike, study finds

University of Cambridge

The personal carbon footprint of the richest people in society is grossly underestimated, both by the rich themselves and by those on middle and lower incomes, no matter which country they come from. At the same time, both the rich and the poor drastically overestimate the carbon footprint of the poorest people.

An international group of researchers, led by the Copenhagen Business School, the University of Basel and the University of Cambridge, surveyed 4,000 people from Denmark, India, Nigeria and the United States about inequality in personal carbon footprints – the total amount of greenhouse gases produced by a person’s activities – within their own country.

Although it is well-known that there is a large gap between the carbon footprint of the richest and poorest in society, it’s been unclear whether individuals were aware of this inequality. The four countries chosen for the survey are all different in terms of wealth, lifestyle and culture. Survey participants also differed in their personal income, with half of participants belonging to the top 10% of income in their country.

The vast majority of participants across the four countries overestimated the average personal carbon footprint of the poorest 50% and underestimated those of the richest 10% and 1%.

However, participants from the top 10% were more likely to support certain climate policies, such as increasing the price of electricity during peak periods, taxing red meat consumption or subsidising carbon dioxide removal technologies such as carbon capture and storage.

The researchers say that this may reflect generally higher education levels among high earners, a greater ability to absorb price-based policies or a stronger preference for technological solutions to the climate crisis. The results are reported in the journal Nature Climate Change.

Although the concept of a personal carbon or environmental footprint has been used for over 40 years, it became widely popularised in the mid-2000s, when the fossil fuel company BP ran a large advertising campaign encouraging people to determine and reduce their personal carbon footprint.

“There are definitely groups out there who would like to push the responsibility of reducing carbon emissions away from corporations and onto individuals, which is problematic,” said co-author Dr Ramit Debnath, Assistant Professor and Cambridge Zero Fellow at the University of Cambridge. “However, personal carbon footprints can illustrate the profound inequality within and between countries and help people identify how to live in a more climate-friendly way.”

Previous research has shown widespread misperceptions about how certain consumer behaviours affect an individual's carbon footprint. For example, recycling, shutting off the lights when leaving a room and avoiding plastic packaging are lower-impact behaviours that are overestimated in terms of how much they can reduce one’s carbon footprint. On the other end, the impact of behaviours such as red meat consumption, heating and cooling homes, and air travel all tend to be underestimated.

However, there is limited research on whether these misperceptions extend to people’s perceptions of the composition and scale of personal carbon footprints and their ability to make comparisons between different groups.

The four countries selected for the survey (Denmark, India, Nigeria and the US) were chosen due to their different per-capita carbon emissions and their levels of economic inequality. Within each country, approximately 1,000 participants were surveyed, with half of each participant group from the top 10% of their country and the other half from the bottom 90%.

Participants were asked to estimate the average personal carbon footprints specific to three income groups (the bottom 50%, the top 10%, and the top 1% of income) within their country. Most participants overestimated the average personal carbon footprint for the bottom 50% of income and underestimated the average footprints for the top 10% and top 1% of income.

“These countries are very different, but we found the rich are pretty similar no matter where you go, and their concerns are different to the rest of society,” said Debnath.

The researchers also looked at whether people’s ideas of carbon footprint inequality were related to their support for different climate policies. They found that Danish and Nigerian participants who underestimated carbon footprint inequality were generally less supportive of climate policies. They also found that Indian participants from the top 10% were generally more supportive of climate policies, potentially reflecting their higher education and greater resources.

“Poorer people have more immediate concerns, such as how they’re going to pay their rent, or support their families,” said first author Dr Kristian Steensen Nielsen from Copenhagen Business School. “But across all income groups, people want real solutions to the climate crisis, whether those are regulatory or technological. However, the people with the highest carbon footprints bear the greatest responsibility for changing their lifestyles and reducing their footprints.”

After learning about the actual carbon footprint inequality, most participants found it slightly unfair, with those in Denmark and the United States finding it the most unfair. However, people from the top 10% generally found the inequality fairer than the general population, except in India. “This could be because they’re trying to justify their larger carbon footprints,” said Debnath.

The researchers say that more work is needed to determine the best ways to promote fairness and justice in climate action across countries, cultures and communities.

“Due to their greater financial and political influence, most climate policies reflect the interests of the richest in society and rarely involve fundamental changes to their lifestyles or social status,” said Debnath.

“Greater awareness and discussion of existing inequality in personal carbon footprints can help build political pressure to address these inequalities and develop climate solutions that work for all,” said Nielsen.

The research was supported in part by the Carlsberg Foundation, the Bill & Melinda Gates Foundation, the Quadrature Climate Foundation and the Swiss National Science Foundation.

Journal

Nature Climate Change

DOI

10.1038/s41558-024-02130-y

Article Title

Underestimation of personal carbon footprint inequality in four diverse countries

Article Publication Date

12-Sep-2024