Pope Leo deploys linguistic advantage to anger Trump with direct criticism: report

Travis Gettys
April 20, 2026

ALTERNET

Pope Leo XIV holds an audience with representatives of the media in Paul VI hall at the Vatican, May 12, 2025. REUTERS/Eloisa Lopez

Escalating tensions between Pope Leo XIV and President Donald Trump are being shaped by an unusual factor: the pope's native fluency in English, which eliminates traditional Vatican diplomatic buffers and amplifies his political impact in the United States.

Unlike previous popes who relied on translation, Leo speaks culturally attuned English that mirrors American political discourse, and this linguistic advantage removes what Vatican officials historically used as a diplomatic tool — ambiguity in translation that softened or reframed controversial papal statements after they sparked backlash, reported Axios.

Leo has emerged as an outspoken critic of the Trump administration's military operations in Iran and immigration policies, and Trump has responded by calling Leo a "very liberal person" who is "weak on crime" and "terrible on foreign policy," while maintaining that he respects the pope's right to speak, even as he disagrees with him.

The pope's remarks have seamlessly integrated into cable news coverage, social media, and campaign messaging, directly reaching American Catholics — a constituency comprising roughly 20 percent of the U.S. population and concentrated in battleground states.

Vincent J. Miller, professor of Catholic Theology and Culture at the University of Dayton, emphasized the significance of Leo's linguistic advantage. "Leo understands the entanglements of religion and politics in the U.S.," Miller said, contrasting Leo with Pope Francis, who could generate headlines with provocative statements but lacked the cultural fluency to target them to American audiences.

Leo, born Robert Prevost in Chicago, spent decades as a missionary and bishop in Peru before his election. His background in Latin American social and political realities, combined with his American upbringing and fluent English, enables him to engage directly in U.S. political debates.

Some church officials argue Leo's English fluency is less significant than his precision and theological commitment. Allen Sánchez, executive director of the New Mexico Conference of Catholic Bishops, stated that Leo's gift is accuracy rather than linguistic ability, noting that the Gospel — not media strategy — drives his messaging.

Papal messaging is entering U.S. electoral politics in unprecedented ways, with Leo's direct communication style potentially reshaping how Vatican positions influence American partisan dynamics.

 

AI tracks motor heat in real time – enabling more efficient electric drives without extra sensors

At the Hannover Messe, Matthias Nienhaus’s research team will be showcasing the new technology

Saarland University

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To estimate the temperature distribution in an electric motor in real time using AI methods, PhD student Saeed Farzami (front) from Professor Matthias Nienhaus’s team (standing) at Saarland University recorded vast amounts of data on a test bench. The data was gathered from sensors placed at those critical points inside the motor where temperature matters: at various locations in the windings, in the rotor and on the housing.

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Credit: Credit: Oliver Dietze

Electric motors are getting smaller, lighter and more powerful – and that makes overheating a growing risk. A research team led by Professor Matthias Nienhaus at Saarland University has developed an AI-assisted method of determining the temperature distribution inside a running electric motor in real time – and without the need for additional hardware. The team will be showcasing the technology at the Hannover Messe (20–24 April) and is looking for industry partners to transfer it into practical and commercial applications. Hall 11, Stand D41

As manufacturers strive to reduce material use and keep their devices compact, any electric motors they contain must also become smaller and lighter – while still delivering high performance. But when motors generate high power within a tight motor housing, they heat up. Crucially, the temperature inside a motor does not rise uniformly. Different components reach different temperatures, and hotspots accelerate ageing, shortening service life and reducing performance.

‘The ability to operate an electric drive safely and, in particular, to control it efficiently depends on power losses and thermal processes within the motor,’ explains Matthias Nienhaus, professor of drive systems engineering at Saarland University. Ideally, the temperature inside the motor should be monitored continuously so that it can run as efficiently as possible without reaching critical limits. However, integrating temperature sensors into an electric motor is far from straightforward. The smaller the drive, the less space there is for additional measurement hardware. Moreover, the most relevant readings are needed when the motor is running under high load and at high speeds – conditions that make sensor deployment even more challenging. ‘Conventional methods for measuring temperature inside the motor tend to be complex and expensive, particularly when trying to assess the temperature of motor parts that are moving at high speeds. So, in practice, these methods are often not used,’ says Matthias Nienhaus. 

Nienhaus and his team on Saarland University’s Saarbrücken campus are developing a method that addresses exactly this challenge: deriving temperature information from electric motors without requiring extensive additional instrumentation. Using only a small set of signals already available from the motor, the team is able to continuously determine the temperatures of key components while the motor is running. ‘We’re developing a monitoring and control system that shows us how temperatures inside the motor change during operation, and this enables precise and efficient power regulation,’ explains Matthias Nienhaus. The benefit is twofold. The system could warn of thermal overload and reduce power early enough to prevent overheating. Conversely, if the temperatures are within their permissible limits, the system could safely increase motor power – helping to get the best out of these compact drives.

AI-supported temperature diagnostics – the motor becomes its own sensor

Nienhaus’s research group specializes in using the motor itself as a sensor by extracting motor-condition data directly from the drive’s electromagnetic fields. With their new approach, they are able to determine motor temperatures during operation – including the temperatures of rotating components. ‘We estimate the temperatures in real time using artificial intelligence methods,’ says Saeed Farzami, a doctoral researcher in Nienhaus’s team. To do this, he had to collect vast amounts of electrical, mechanical and thermal data on a test bench he designed himself. The data was gathered from sensors that Farzami placed at those critical points inside the motor where temperature matters: at various locations in the windings, in the rotor and on the housing.

He recorded signals from the motor across a wide range of operating scenarios – from low to high rotational speeds – and then used the resulting dataset to train a neural network. Artificial neural networks are inspired by the human brain: they learn from ‘experience’ – in this case, from exposure to vast quantities of training data. And much like its biological counterpart, an AI model can be trained to recognize and evaluate complex patterns by processing large datasets and iteratively correcting errors. ‘With our thermal AI models, we’re now able to estimate the temperature distribution across the various motor components using only a few measurement values,’ explains Saeed Farzami.

At the Hannover Messe, Matthias Nienhaus’s research team will be showcasing the new technology on an electric-motor test bench. The group is seeking industrial partners to further develop their AI-assisted monitoring and control system for real-time temperature estimation in electric drives and to translate this technology into practical and commercial applications.
Joint stand ‘Germany’s Saarland’, Hall 11, Stand D41.

 

Assistance dogs interpret needs of the person they assist non-verbally

University of Turku

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An assistance dog at work.

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Credit: Suvi Satama

A recent study shows that assistance dogs do not only help people with practical tasks, but actively contribute to their care, based on mutual trust and continuous interpretation of each other.

Assistance dogs are active caregivers, according to a new study by the University of Turku and Aalto University in Finland. The study examined the collaborative interaction between humans and assistance dogs. Dogs perform invisible care work by, for example, anticipating their human's health status, providing mobility assistance, and offering emotional support in ways that neither a human nor a robot could replace.

The key finding of the study is that the care provided by an assistance dog is based on mutual trust and constant reading of the person being cared for, often without the need for speech. Humans and dogs learn to interpret each other’s subtle gestures, movements, and reactions non-verbally.

“Care work is the results of bodily interaction, meaning small gestures and the working dog’s sensitivity to interpreting people and responding to the needs of those who require assistance”, explains Suvi Satama, Assistant Professor of Management and Organisation at the University of Turku.

The study was conducted by Satama and Astrid Huopalainen from Aalto University, who have been collaborating for 15 years. According to them, the bodily nature of interspecies care work brings to light the subtle dimensions of care and subtle power dynamics that are often overlooked in interpersonal care.

The study analysed the everyday lives of 13 assistance dogs and their human companions through interviews, ethnographic observations, and photographs.

People rely on their assistance dogs

The study shows that assistance dogs act as kind of care professionals, whose instructions humans must follow. In some situations, people have to rely on their dog’s judgement more than their own.

“For example, a person with diabetes must rely on the dog when the dog detects changes in blood sugar. When the person responds to the dog’s signal and checks their blood sugar or follows the dog’s alert to take the necessary medication in time, serious situations can be avoided”, says Satama.

According to the researchers, this dynamic turns the traditional care relationship between humans and dogs on its head: the care is not one-sided or something in which humans take care of dogs.

“Assistance dogs care for humans, and humans also do their best to care for their assistance dogs. In this way, vulnerability becomes relational, and both parties give and receive care”, says Satama.

Researchers hope to spark conversation on the role of animals in society

The researchers challenge the human-centred view where animals are seen as passive agents. In the research material, the assistance dogs are portrayed as active, intelligent, and sentient individuals with their own, entirely unique roles at the workplace and in society.

According to Satama, it was interesting to observe during the study how the working dogs know when they are off duty and sometimes use their agency to play tricks on their humans or otherwise do things their own way from time to time.

“For example, I was observing a meeting of people with visual impairments, at which their assistance dogs were also present. The dogs had been told to stay on the floor next to their people. Suddenly, one of the assistance dogs started crawling towards another dog and some scents, and the person did not notice this due to their visual impairment. I thought that the dog was carrying out their own agency”, Satama says.

The researchers hope that the study would spark a discussion about the diverse roles of animals and their well-being at work in different organisations.

“When we recognise animals as agential caregivers, we can also better understand the care work between humans and its various dimensions”, Satama emphasises.

The study is part of the PAWWS – People and Animal Wellbeing at Work and in Society research project (2023–2027), funded by the Research Council of Finland. Astrid Huopalainen serves as the consortium Principal Investigator of the project. The project examines collaboration and mutual wellbeing between humans and animals in the workplace. The aim of the project is to understand how animals contribute at work, what type of roles they take in society, and what ethical issues this involves.

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Journal

Human Relations

DOI

10.1177/00187267261428980 

Article Title

“He gives me everything all the time, and I feel bad that I can’t even throw him the ball”: Relational care agency in interspecies care work.

 

The importance of data for crowd safety in public spaces

A study published in JSTAT reveals that inconsistent data measurement in crowd models may compromise safety predictions, proposing new methods to better capture the complex dynamics of human movement in public spaces.

Sissa Medialab

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Crowd view from stage featuring carnival dancers on stage. The Awakening, LEEDS 2023, Headingley Stadium

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Credit: LEEDS 2023

How can public spaces remain safe when large crowds move through them? Engineers and researchers who study these environments often rely on physical models borrowed from fluid dynamics — a branch of physics that describes the collective motion of fluids, whose behaviour emerges from the interactions of many particles.
But a new study published in the Journal of Statistical Physics: Theory and Experiment (JSTAT) highlights a crucial issue: the way data are collected and measured within these models lacks standardisation and may overlook important features of human collective behaviour. Unlike particles, people are living agents with individual decisions and complex interactions, making their movement harder to capture with traditional approaches.

In their study, the authors propose and experimentally test new methods to address these limitations, comparing them with more established techniques. Their results point the way toward clearer methodological guidelines and the development of more reliable tools for those involved in the design and management of public spaces.
Humans as physical particles (or not?)

“Our field of research is pedestrian dynamics,” explains Juliane Adrian, researcher at the Institute for Advanced Simulation 7: Civil Safety Research, Forschungszentrum Jülich (Germany), and first author of the study. “We want to understand when a situation turns from normal to dangerous,” Adrian says. “But humans are not physical particles. They have free will.”
Traditionally, the analysis starts from the so-called flow equation, which combines the density of people and their speed. Based on this relationship, researchers build a “fundamental diagram” of a given space, used to assess under which conditions congestion or dangerous crowding may occur.
“There is a certain point where you have an optimum flow at an optimum density,” Adrian explains. “But at some point, this tips over: if the density increases further, the flow decreases because people can no longer move freely. They need to stop, take detours, and adjust their speed because there are so many other people around.”
For this reason, obtaining a realistic fundamental diagram is crucial for correctly interpreting crowd dynamics and designing safer spaces. But this is also where the problem lies.

How data are measured matters

“The flow equation and the fundamental diagram are not problematic in themselves,” Adrian explains. “The real issue is how we measure quantities like speed, density and flow.”
By reviewing the existing literature, Adrian and colleagues found what she describes as “a general lack of consensus” in measurement approaches — something that can lead to significant differences in how even very similar situations are interpreted.

Traditional methods tend to work well in simple scenarios, for instance when everyone moves in the same direction. But real crowds are rarely that simple. “There might be inhomogeneities in the crowd. There might be counter movement,” Adrian says. “For example, in a bidirectional stream, some people walk in one direction while others move in the opposite one. And people may also change their mind, turn around, or move back and forth. On top of that, pedestrian crowds can reach very high densities.”

In these more complex situations, standard approaches can become unreliable — and may even detect movement where there is effectively none. “If it’s really dense, even if people stand still, there might still be movement in the crowd,” Adrian explains. “People might lean or move slightly, so if you measure their speed, it can appear as motion in different directions — even in the opposite one.”

The experiments

In their experiments, Adrian and colleagues recorded groups of people walking in controlled environments — such as corridors or open spaces — using overhead video cameras. Dedicated software was then used to reconstruct the individual trajectories of each participant, treated in a simplified way as moving points.

Starting from these trajectories, the researchers calculated key quantities such as speed, density and flow. The novelty, however, lies in how these quantities are defined and measured.
To describe crowd movement consistently, Adrian and colleagues adopted an approach based on Voronoi cells — dividing space so that each person is assigned the area closest to them. This makes it possible to define quantities like density, speed and flow consistently at the same point in space. “We divide the space into regions to define these quantities consistently,” Adrian explains.

A crucial aspect of the method is that all quantities are measured at the same place and at the same moment. This avoids a key limitation of traditional approaches, where density, speed and flow are calculated in different ways — for instance, density over an area and flow over time — making them difficult to compare directly. “We can have measurements at the same location, same time point,” Adrian explains.

On this basis, the researchers build continuous fields similar to those used in fluid physics and apply the continuity equation — a “conservation law that ensures that no pedestrian simply appears or disappears,” as Adrian puts it — to describe how people are distributed and move through space.

Finally, Adrian and colleagues compared their approach with traditional methods using experimental data, showing that the differences become particularly significant at high densities, when crowds are more prone to congestion and complex collective behaviours.

A more accurate description of collective motion

Based on their work, Adrian and colleagues conclude that how density, speed and flow are measured in crowds matters far more than previously assumed — especially in critical situations.
In particular, they show that traditional methods — which combine averages taken over space (for density) and over time (for flow) — can produce inconsistent or even misleading results, especially when crowds become dense or start to congest. Under these conditions, the different quantities are no longer fully compatible, and the so-called fundamental diagram — the relationship between density, speed and flow — can become distorted.

Their approach instead provides a more reliable description of collective motion, capturing effects that are often hidden by standard methods, such as local slowdowns, oscillations, or even complete crowd standstills.

The paper “Pedestrian Flow Analysis in High-Density Crowds: Continuity Equation with Voronoi-Based Fields” by Juliane Adrian, Ann Katrin Boomers, Sarah Paetzke and Armin Seyfried is now available in JSTAT.
 

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Journal

Journal of Statistical Mechanics Theory and Experiment

Method of Research

Experimental study

Article Title

Pedestrian Flow Analysis in High-Density Crowds: Continuity Equation with Voronoi-Based Fields

4PROFIT HEALTHCARE

Millions of Americans now consult AI before, after — and sometimes instead of — seeing a doctor

Over half of recent AI users say they research health questions before or after seeing a doctor, though most still prefer a provider for sensitive conversations

West Health Institute

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WASHINGTON, D.C. — April 15, 2026 — One in four U.S. adults — the equivalent of over 66 million Americans — report having used artificial intelligence tools or chatbots for physical or mental healthcare information or advice, according to new research released today from the West Health-Gallup Center on Healthcare in America. Rather than replacing traditional care, more than half say they turn to AI to supplement their healthcare experiences, using the technology before or after seeing a doctor.

The findings are based on a nationally representative survey of more than 5,500 U.S. adults conducted from October through December 2025.

In the past 30 days, did you use an AI tool or chatbot for health-related information or advice for any of the following reasons?

% Yes, among adults who have used AI tools or chatbots for health-related information or advice in the past 30 days

Category	Reason	U.S. adult AI health users
Speed and self-directed research	I wanted answers quickly	71%
	I wanted additional information	71%
	I was curious about what AI would say	67%
	I prefer to research on my own before seeing a doctor	59%
	I prefer to research on my own after seeing a doctor	56%
Cost barriers	I didn’t want to pay for a doctor’s visit	27%
	I was unable to pay for a doctor’s visit	14%
Access barriers	I didn’t have time to make an appointment	21%
	I couldn’t access a doctor or provider	16%
	I wanted help outside normal business hours	42%
Quality and stigma barriers	I felt dismissed or ignored by a provider in the past	21%
	I was too embarrassed to talk to a person	18%

Note. Categories are for descriptive purposes only and were not shown on the survey.             

Among Americans who have used AI for health-related information or advice in the past 30 days, the most frequently cited motivations are wanting answers quickly (71%) and wanting additional information (71%). Nearly seven in 10 (67%) say they were curious about what AI would say, and roughly six in 10 report using AI to do research on their own before (59%) or after (56%) seeing a doctor.

Regardless of the reason, almost half (46%) of Americans who used AI for healthcare information say the AI tool or chatbot made them feel more confident talking with or asking questions of a provider. Others say it helped them identify issues earlier (22%) or avoid unnecessary medical tests or procedures (19%).

“Artificial intelligence is already reshaping how Americans seek health information, make decisions and engage with providers, and health systems must keep pace,” said Tim Lash, President, West Health Policy Center, a nonprofit and nonpartisan organization focused on aging and healthcare affordability. “The risk isn’t that AI is moving too fast — it’s that health systems may move too slowly to guide its use in healthcare responsibly.”

A Smaller Share Turn to AI in Place of a Provider

While self-directed research is the primary driver of AI health use, a smaller but notable share of recent users report turning to AI instead of seeing a healthcare provider, particularly when faced with cost, access or quality barriers. Among recent AI health users, 27% say they didn't want to pay for a doctor's visit and 14% say they were unable to pay. One in five (21%) say they didn't have time to make an appointment, and 16% say they couldn't access a doctor or provider. Another 21% say they felt dismissed or ignored by a provider in the past, and 18% say they were too embarrassed to talk to a person.

 

In the past 30 days, did you use an AI tool or chatbot for health-related information or advice for any of the following reasons?

% Yes, among adults who have used AI for health-related information and advice in the past 30 days

I was unable to pay for a doctor’s visit

Household Income	% Yes, Among adults who have used AI for health-related information and advice in the past 30 days
<$24k	32%
$24k - <$48k	21%
$48k - <$90k	14%
$90k - <$120k	9%
$120k - <$180k	8%
$180k+	2%

Among recent AI health users, 84% still saw a healthcare provider, but 14% report not seeing a provider they otherwise would have seen because of information or advice they received from AI. When projected to the full U.S. adult population, this represents roughly 14 million Americans who did not see a provider after receiving AI-generated health information.

Trust in that AI-generated health information, however, remains divided. Among those who consulted it in the past 30 days, roughly one-third say they trust it (33%), one-third neither trust nor distrust it (33%), and about one-third distrust it (34%). However, only 4% say they strongly trust the accuracy, indicating that many Americans are making healthcare decisions based on AI-generated information without full confidence in its accuracy.

About one in 10 (11%) who report using AI for health information or advice in the past 30 days say that AI recommended healthcare information or advice they believed was unsafe.

"This data indicates that while some Americans may be using artificial intelligence as a substitute for going to the doctor's office, many see it as a tool to complement their healthcare, helping them understand symptoms they might be feeling and clarify any diagnosis they receive from their doctors," said Joe Daly, Global Managing Partner at Gallup.

Motivations Vary by Age and Income

While information-seeking is the dominant reason Americans turn to AI for health purposes, use patterns differ by demographics. Younger adults are more likely than older adults to use AI for self-directed research — 69% of adults aged 18 to 29 say they do research before seeing a doctor, compared with 43% of those 65 and older.

Income differences are most visible in barrier-driven motivations. Among adults earning less than $24,000 annually, 32% say they used AI because they could not pay for a doctor's visit, compared with just 2% among those earning $180,000 or more.

Everyday Health Questions Top the List of AI Use Cases

Americans who used AI for health information or advice in the past 30 days most often report using it to gather information about everyday health concerns, including physical symptoms (58%) and nutrition or exercise (59%). But AI use extends beyond symptom-checking — Americans who used AI in the past 30 days also report using AI to understand medication side effects (46%), interpret medical information (44%), or research a diagnosis or medical condition (38%). Nearly one in four (24%) report using AI to explore mental health or emotional concerns.

Methodology

West Health-Gallup Center on Healthcare, October-December 2025

Results are based on a Gallup Panel study conducted Oct. 27-Dec. 22, 2025, with a sample of 5,660 adults aged 18 and older who are members of the Gallup Panel, a nationally representative, probability-based panel of U.S. adults. Gallup uses random selection methods to recruit Panel members, including random-digit-dial (RDD) phone interviews that cover landlines and cellphones and address-based sampling (ABS) methods. Respondents with internet access completed the questionnaire as a web survey, and those without regular internet access were sent a printed questionnaire to complete and return by mail. The sample for this study was weighted to be demographically representative of the U.S. adult population, using the most recent Current Population Survey figures. For results based on this sample, one can say that the maximum margin of sampling error is ±2.1 percentage points at the 95% confidence level. Margins of error are higher for subsamples. In addition to sampling error, question wording and practical difficulties in conducting surveys can introduce error and bias into the findings of public opinion polls.

About the West Health-Gallup Center on Healthcare in America

The Center on Healthcare in America is a joint initiative from West Health and Gallup dedicated to elevating the voices and experiences of Americans within the healthcare system. Through rigorous research and human-centered storytelling, the Center aims to drive actionable insights and inform policy solutions nationwide. Visit westhealth.gallup.comhttp://www.westhealth.gallup.com/.

About West Health

Solely funded by philanthropists Gary and Mary West, West Health is a family of nonprofit and nonpartisan organizations that include the Gary and Mary West Foundation and Gary and Mary West Health Institute in San Diego and the Gary and Mary West Health Policy Center in Washington, D.C. West Health is dedicated to lowering healthcare costs to enable seniors to successfully age in place with access to high-quality and affordable health and support services that preserve and protect their dignity, quality of life and independence. Learn more at westhealth.org.

About Gallup

Gallup delivers analytics and advice to help leaders and organizations solve their most pressing problems. Combining 90 years of experience with its global reach, Gallup knows more about the attitudes and behaviors of employees, customers, students and citizens than any other organization in the world.

 

New method can reduce risk of violating Sámi rights

Stockholm Environment Institute

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The graph shows the six preconditions required to ensure the rights of the Sami: Continuous and interconnected pastures, access to traditional winter pastures, traditional use of seasonal pastures, grazing peace and access to natural grazing, traditional knowledge is kept alive and Sámi youth can continue traditional livelihood. Current status at top and impact of the Per Geijer project at bottom.

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Credit: SEI

A new method developed by researchers at Stockholm Environment Institute (SEI) can help identify and reduce the risk of rights violations linked to industrial projects on the traditional lands of Sámi reindeer herding communities. Based on a case study of LKAB's planned mining project Per Geijer, the method highlights significant risks to human rights.

The report is the result of a research collaboration with the Gabna Sámi reindeer herding community, contributing knowledge on land use and insights into the cultural values linked to natural grazing-based reindeer herding, including the need for reindeer to move freely across extensive, connected grazing lands. These landscapes are essential for safeguarding Sámi rights.

The method, including the risk assessment framework and the analysis of both current impacts and future risks, was developed by SEI researchers. The study was funded by Formas, NordForsk and Mistra.

"Taken together, we see significant risks of violations of the Sámi reindeer herding community members' right to land and culture, as well as several examples of LKAB failing in its obligation to respect the Sámi community's right to effective participation. In view of the project's extensive impact, explicit consent from the Sámi community is probably needed for the project to be permissible under international Indigenous rights law," says Rasmus Kløcker Larsen, Senior Researcher at SEI.  

Previous research shows that mining and other natural resource extraction often entail risks for both the environment and people, particularly Indigenous Peoples. The new method enables companies to carry out rights-based risk assessments for industrial projects on Sámi lands, helping to prevent rights violations and ensure the protection of Sámi rights.

It identifies six key preconditions for ensuring a Sámi community's collective rights to land and culture when land is subject to competing land-use claims.

"Gabna is already extensively affected by both LKAB's and others' activities around Kiruna. We believe that the Per Geijer project would further cause major or serious impacts on virtually all preconditions examined, as the reindeer herding community’s pastures would be divided,” says Carl Österlin, Researcher at SEI.

“Before further exploitation can be considered, extensive measures are required to ensure sufficient land for reindeer to move freely around Kiruna and for coordinated seasonal migration past Kiruna." 

The method can be applied to projects affecting other Sámi herding communities but must be adapted in dialogue with those affected. There can be considerable differences between Sámi communities in terms of seasonal migration patterns and possibilities to protect or restore conditions for natural grazing-based reindeer herding.

Existing guidelines for risk assessment, current mining industry practices as regards analyses of impacts on reindeer herding and the evidence base used by licensing authorities have often been criticised. The new method offers a way forward, but further development and practical application is needed to ensure adequate assessments of human rights risks in Sápmi in line with international standards.

"Our hope is that the report can contribute to better risk assessments, better protection of Sámi rights and a fairer management of land use linked to energy and mineral policy," says Rasmus Kløcker Larsen.

The report also highlights that:

• Greater transparency is needed regarding the scope of strategic mining projects. At present, such information is not disclosed to researchers, Sámi communities or other stakeholders by either the European Commission or applicant companies.
• It must be clarified what legislative and policy measures politicians and authorities are prepared to take to ensure Sámi rights holders are guaranteed influence over land-use planning before companies apply for permits.

About the report and the case study

The report Assessing how to handle mining projects and their risks to Indigenous rights in a reindeer herding context (in Swedish) explains how a human rights impact assessment (HRIA) can be used to assess and address risks to Indigenous rights linked to reindeer herding.

The case study focuses on of the state-owned mining company LKAB's application for a mining concession for the Per Geijer deposit, one of the first extraction projects in Sweden designated by the European Commission as a strategic project under the Critical Raw Materials Act.

According to the state's ownership policy, LKAB is expected to lead the industry in corporate responsibility. The company was invited to contribute information and to conduct factchecking prior to publication but declined.

The responsibility for ensuring adequate impact assessments for the Per Geijer project rests with LKAB. The company submitted its application for a mining concession in June 2024 and must supplement it with a reindeer herding analysis by 1 May 2026. To date, no HRIA has been carried out for the project.

For more information, please contact:

Rasmus Kløcker Larsen, Senior Research Fellow, SEI, rasmus.klocker.larsen@sei.org
Carl Österlin, Research Fellow, SEI, carl.osterlin@sei.org
Ulrika Lamberth, Senior Press Officer, SEI, ulrika.lamberth@sei.org, + 46 73 801 7053
Lars-Marcus Kuhmunen, Chairman, Gabna Sámi Village, samebygabna@gmail.com

Stockholm Environment Institute is an international non-profit research institute that tackles climate, environment and sustainable development challenges. We empower partners to meet these challenges through cutting-edge research, knowledge, tools and capacity building. Through SEI’s HQ and seven centres around the world, we engage with policy, practice and development action for a sustainable, prosperous future for all. www.sei.org