Category: The Conversation – USA

Source: The Conversation – USA (2) – By Janice Mak, Assistant Director and Clinical Assistant Professor, Arizona State University

Generative artificial intelligence technology is rapidly reshaping education in unprecedented ways. With its potential benefits and risks, K-12 schools are actively trying to adapt teaching and learning.

But as schools seek to navigate into the age of generative AI, there’s a challenge: Schools are operating in a policy vacuum. While a number of states offer guidance on AI, only a couple of states require local schools to form specific policies, even as teachers, students and school leaders continue to use generative AI in countless new ways. As a policymaker noted in a survey, “You have policy and what’s actually happening in the classrooms – those are two very different things.”

As part of my lab’s research on AI and education policy, I conducted a survey in late 2025 with members of the National Association of State Boards of Education, the only nonprofit dedicated solely to helping state boards advance equity and excellence in public education. The survey of the association’s members reflects how education policy is typically formed through dynamic interactions across national, state and local levels, rather than being dictated by a single source.

But even in the absence of hard-and-fast rules and guardrails on how AI can be used in schools, education policymakers identified a number of ethical concerns raised by the technology’s spread, including student safety, data privacy and negative impacts on student learning.

They also expressed concerns over industry influence and that schools will later be charged by technology providers for large language model-based tools that are currently free. Others report that administrators in their state are very concerned about deepfakes: “What happens when a student deepfakes my voice and sends it out to cancel school or bomb threat?”

At the same time, policymakers said teaching students to use AI technology to their benefit remains a priority.

Local actions dominate

Although chatbots have been widely available for more than three years, the survey revealed that states are in the early stages of addressing generative AI, with most yet to implement official policies. While many states are providing guidance or tool kits, or are starting to write state-level policies, local decisions dominate the landscape, with each school district primarily responsible for shaping its own plans.

When asked whether their state has implemented any generative AI policies, respondents said there was a high degree of local influence regardless of whether a state issued guidance or not. “We are a ‘local control’ state, so some school districts have banned (generative AI),” wrote one respondent. “Our (state) department of education has an AI tool kit, but policies are all local,” wrote another. One shared that their state has a “basic requirement that districts adopt a local policy about AI.”

Like other education policies, generative AI adoption occurs within the existing state education governance structures, with authority and accountability balanced between state and local levels. As with previous waves of technology in K-12 schools, local decision-making plays a critical role.

Yet there is generally a lack of evidence related to how AI will affect learners and teachers, which will take years to become more clear. That lag adds to the challenges in formulating policies.

States as a lighthouse

However, state policy can provide vital guidance by prioritizing ethics, equity and safety, and by being adaptable to changing needs. A coherent state policy can also answer key questions, such as acceptable student use of AI, and ensure more consistent standards of practice. Without such direction, districts are left to their own devices to identify appropriate, effective uses and construct guardrails.

As it stands, AI usage and policy development are uneven, depending on how well resourced a school is. Data from a RAND-led panel of educators showed that teachers and principals in higher-poverty schools are about half as likely to AI guidance provided. The poorest schools are also less likely to use AI tools.

When asked about foundational generative AI policies in education, policymakers focused on privacy, safety and equity. One respondent, for example, said school districts should have the same access to funding and training, including for administrators.

And rather than having the technology imposed on schools and families, many argued for grounding the discussion in human values and broad participation. As one policymaker noted, “What is the role that families play in all this? This is something that is constantly missing from the conversation and something to uplift. As we know, parents are our kids’ first teachers.”

Introducing new technology

According to a Feb. 24, 2025, Gallup Poll, 60% of teachers report using some AI for their work in a range of ways. Our survey also found there is “shadow use of AI,” as one policymaker put it, where employees implement generative AI without explicit school or district IT or security approval.

Some states, such as Indiana, offer schools the opportunity to apply for a one-time competitive grant to fund a pilot of an AI-powered platform of their choosing as long as the product vendors are approved by the state. Grant proposals that focus on supporting students or professional development for educators receive priority.

In other states, schools opt in to pilot tests that are funded by nonprofits. For example, an eighth grade language arts teacher in California participated in a pilot where she used AI-powered tools to generate feedback on her students’ writing. “Teaching 150 kids a day and providing meaningful feedback for every student is not possible; I would try anything to lessen grading and give me back my time to spend with kids. This is why I became a teacher: to spend time with the kids.” This teacher also noted the tools showed bias when analyzing the work of her students learning English, which gave her the opportunity to discuss algorithmic bias in these tools.

One initiative from the Netherlands offers a different approach than finding ways to implement products developed by technology companies. Instead, schools take the lead with questions or challenges they are facing and turn to industry to develop solutions informed by research.

Core principles

One theme that emerged from survey respondents is the need to emphasize ethical principles in providing guidance on how to use AI technology in teaching and learning. This could begin with ensuring that students and teachers learn about the limitations and opportunities of generative AI, when and how to leverage these tools effectively, critically evaluate its output and ethically disclose its use.

Often, policymakers struggle to know where to begin in formulating policies. Analyzing tensions and decision-making in organizational context – or what my colleagues and I called dilemma analysis in a recent report – is an approach schools, districts and states can take to navigate the myriad of ethical and societal impacts of generative AI.

Despite the confusion around AI and a fragmented policy landscape, policymakers said they recognize it is incumbent upon each school, district and state to engage their communities and families to co-create a path forward.

As one policymaker put it: “Knowing the horse has already left the barn (and that AI use) is already prevalent among students and faculty … (on) AI-human collaboration vs. outright ban, where on the spectrum do you want to be?”

Janice Mak receives funding from Google, National Science Foundation, and the Spencer Foundation. She is affiliated with the Association for Computing Machinery’s Education Advisory Committee.

– ref. When it comes to developing policies on AI in K-12, schools are largely on their own – https://theconversation.com/when-it-comes-to-developing-policies-on-ai-in-k-12-schools-are-largely-on-their-own-268272

Source: The Conversation – USA (2) – By Murugan Anandarajan, Professor of Decision Sciences and Management Information Systems, Drexel University

Businesses are acting fast to adopt agentic AI – artificial intelligence systems that work without human guidance – but have been much slower to put governance in place to oversee them, a new survey shows. That mismatch is a major source of risk in AI adoption. In my view, it’s also a business opportunity.

I’m a professor of management information systems at Drexel University’s LeBow College of Business, which recently surveyed more than 500 data professionals through its Center for Applied AI & Business Analytics. We found that 41% of organizations are using agentic AI in their daily operations. These aren’t just pilot projects or one-off tests. They’re part of regular workflows.

At the same time, governance is lagging. Only 27% of organizations say their governance frameworks are mature enough to monitor and manage these systems effectively.

In this context, governance is not about regulation or unnecessary rules. It means having policies and practices that let people clearly influence how autonomous systems work, including who is responsible for decisions, how behavior is checked, and when humans should get involved.

This mismatch can become a problem when autonomous systems act in real situations before anyone can intervene.

For example, during a recent power outage in San Francisco, autonomous robotaxis got stuck at intersections, blocking emergency vehicles and confusing other drivers. The situation showed that even when autonomous systems behave “as designed,” unexpected conditions can lead to undesirable outcomes.

This raises a big question: When something goes wrong with AI, who is responsible – and who can intervene?

Why governance matters

When AI systems act on their own, responsibility no longer lies where organizations expect it. Decisions still happen, but ownership is harder to trace. For instance, in financial services, fraud detection systems increasingly act in real time to block suspicious activity before a human ever reviews the case. Customers often only find out when their card is declined.

So, what if your card is mistakenly declined by an AI system? In that situation, the problem isn’t with the technology itself – it’s working as it was designed – but with accountability. Research on human-AI governance shows that problems happen when organizations don’t clearly define how people and autonomous systems should work together. This lack of clarity makes it hard to know who is responsible and when they should step in.

Without governance designed for autonomy, small issues can quietly snowball. Oversight becomes sporadic and trust weakens, not because systems fail outright, but because people struggle to explain or stand behind what the systems do.

When humans enter the loop too late

In many organizations, humans are technically “in the loop,” but only after autonomous systems have already acted. People tend to get involved once a problem becomes visible – when a price looks wrong, a transaction is flagged or a customer complains. By that point, the system has already been decided, and human review becomes corrective rather than supervisory.

Late intervention can limit the fallout from individual decisions, but it rarely clarifies who is accountable. Outcomes may be corrected, yet responsibility remains unclear.

Recent guidance shows that when authority is unclear, human oversight becomes informal and inconsistent. The problem is not human involvement, but timing. Without governance designed upfront, people act as a safety valve rather than as accountable decision-makers.

How governance determines who moves ahead

Agentic AI often brings fast, early results, especially when tasks are first automated. Our survey found that many companies see these early benefits. But as autonomous systems grow, organizations often add manual checks and approval steps to manage risk.

Over time, what was once simple slowly becomes more complicated. Decision-making slows down, work-arounds increase, and the benefits of automation fade. This happens not because the technology stops working, but because people never fully trust autonomous systems.

This slowdown doesn’t have to happen. Our survey shows a clear difference: Many organizations see early gains from autonomous AI, but those with stronger governance are much more likely to turn those gains into long-term results, such as greater efficiency and revenue growth. The key difference isn’t ambition or technical skills, but being prepared.

Good governance does not limit autonomy. It makes it workable by clarifying who owns decisions, how systems function is monitored, and when people should intervene. International guidance from the OECD – the Organization for Economic Cooperation and Development – emphasizes this point: Accountability and human oversight need to be designed into AI systems from the start, not added later.

Rather than slowing innovation, governance creates the confidence organizations need to extend autonomy instead of quietly pulling it back.

The next advantage is smarter governance

The next competitive advantage in AI will not come from faster adoption, but from smarter governance. As autonomous systems take on more responsibility, success will belong to organizations that clearly define ownership, oversight and intervention from the start.

In the era of agentic AI, confidence will accrue to the organizations that govern best, not simply those that adopt first.

Murugan Anandarajan does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. Companies are already using agentic AI to make decisions, but governance is lagging behind – https://theconversation.com/companies-are-already-using-agentic-ai-to-make-decisions-but-governance-is-lagging-behind-272792

Source: The Conversation – USA (2) – By Ahmed Elgammal, Professor of Computer Science and Director of the Art & AI Lab, Rutgers University

Generative AI was trained on centuries of art and writing produced by humans.

But scientists and critics have wondered what would happen once AI became widely adopted and started training on its outputs.

A new study points to some answers.

In January 2026, artificial intelligence researchers Arend Hintze, Frida Proschinger Åström and Jory Schossau published a study showing what happens when generative AI systems are allowed to run autonomously – generating and interpreting their own outputs without human intervention.

The researchers linked a text-to-image system with an image-to-text system and let them iterate – image, caption, image, caption – over and over and over.

Regardless of how diverse the starting prompts were – and regardless of how much randomness the systems were allowed – the outputs quickly converged onto a narrow set of generic, familiar visual themes: atmospheric cityscapes, grandiose buildings and pastoral landscapes. Even more striking, the system quickly “forgot” its starting prompt.

The researchers called the outcomes “visual elevator music” – pleasant and polished, yet devoid of any real meaning.

For example, they started with the image prompt, “The Prime Minister pored over strategy documents, trying to sell the public on a fragile peace deal while juggling the weight of his job amidst impending military action.” The resulting image was then captioned by AI. This caption was used as a prompt to generate the next image.

After repeating this loop, the researchers ended up with a bland image of a formal interior space – no people, no drama, no real sense of time and place.

As a computer scientist who studies generative models and creativity, I see the findings from this study as an important piece of the debate over whether AI will lead to cultural stagnation.

The results show that generative AI systems themselves tend toward homogenization when used autonomously and repeatedly. They even suggest that AI systems are currently operating in this way by default.

The familiar is the default

This experiment may appear beside the point: Most people don’t ask AI systems to endlessly describe and regenerate their own images. The convergence to a set of bland, stock images happened without retraining. No new data was added. Nothing was learned. The collapse emerged purely from repeated use.

But I think the setup of the experiment can be thought of as a diagnostic tool. It reveals what generative systems preserve when no one intervenes.

This has broader implications, because modern culture is increasingly influenced by exactly these kinds of pipelines. Images are summarized into text. Text is turned into images. Content is ranked, filtered and regenerated as it moves between words, images and videos. New articles on the web are now more likely to be written by AI than humans. Even when humans remain in the loop, they are often choosing from AI-generated options rather than starting from scratch.

The findings of this recent study show that the default behavior of these systems is to compress meaning toward what is most familiar, recognizable and easy to regenerate.

Cultural stagnation or acceleration?

For the past few years, skeptics have warned that generative AI could lead to cultural stagnation by flooding the web with synthetic content that future AI systems then train on. Over time, the argument goes, this recursive loop would narrow diversity and innovation.

Champions of the technology have pushed back, pointing out that fears of cultural decline accompany every new technology. Humans, they argue, will always be the final arbiter of creative decisions.

What has been missing from this debate is empirical evidence showing where homogenization actually begins.

The new study does not test retraining on AI-generated data. Instead, it shows something more fundamental: Homogenization happens before retraining even enters the picture. The content that generative AI systems naturally produce – when used autonomously and repeatedly – is already compressed and generic.

This reframes the stagnation argument. The risk is not only that future models might train on AI-generated content, but that AI-mediated culture is already being filtered in ways that favor the familiar, the describable and the conventional.

Retraining would amplify this effect. But it is not its source.

This is no moral panic

Skeptics are right about one thing: Culture has always adapted to new technologies. Photography did not kill painting. Film did not kill theater. Digital tools have enabled new forms of expression.

But those earlier technologies never forced culture to be endlessly reshaped across various mediums at a global scale. They did not summarize, regenerate and rank cultural products – news stories, songs, memes, academic papers, photographs or social media posts – millions of times per day, guided by the same built-in assumptions about what is “typical.”

The study shows that when meaning is forced through such pipelines repeatedly, diversity collapses not because of bad intentions, malicious design or corporate negligence, but because only certain kinds of meaning survive the text-to-image-to-text repeated conversions.

This does not mean cultural stagnation is inevitable. Human creativity is resilient. Institutions, subcultures and artists have always found ways to resist homogenization. But in my view, the findings of the study show that stagnation is a real risk – not a speculative fear – if generative systems are left to operate in their current iteration.

They also help clarify a common misconception about AI creativity: Producing endless variations is not the same as producing innovation. A system can generate millions of images while exploring only a tiny corner of cultural space.

In my own research on creative AI, I found that novelty requires designing AI systems with incentives to deviate from the norms. Without it, systems optimize for familiarity because familiarity is what they have learned best. The study reinforces this point empirically. Autonomy alone does not guarantee exploration. In some cases, it accelerates convergence.

This pattern already emerged in the real world: One study found that AI-generated lesson plans featured the same drift toward conventional, uninspiring content, underscoring that AI systems converge toward what’s typical rather than what’s unique or creative.

Lost in translation

Whenever you write a caption for an image, details will be lost. Likewise for generating an image from text. And this happens whether it’s being performed by a human or a machine.

In that sense, the convergence that took place is not a failure that’s unique to AI. It reflects a deeper property of bouncing from one medium to another. When meaning passes repeatedly through two different formats, only the most stable elements persist.

But by highlighting what survives during repeated translations between text and images, the authors are able to show that meaning is processed inside generative systems with a quiet pull toward the generic.

The implication is sobering: Even with human guidance – whether that means writing prompts, selecting outputs or refining results – these systems are still stripping away some details and amplifying others in ways that are oriented toward what’s “average.”

If generative AI is to enrich culture rather than flatten it, I think systems need to be designed in ways that resist convergence toward statistically average outputs. There can be rewards for deviation and support for less common and less mainstream forms of expression.

The study makes one thing clear: Absent these interventions, generative AI will continue to drift toward mediocre and uninspired content.

Cultural stagnation is no longer speculation. It’s already happening.

Ahmed Elgammal does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. AI-induced cultural stagnation is no longer speculation − it’s already happening – https://theconversation.com/ai-induced-cultural-stagnation-is-no-longer-speculation-its-already-happening-272488

Source: The Conversation – USA – By Saman Zonouz, Associate Professor of Cybersecurity and Privacy and Electrical and Computer Engineering, Georgia Institute of Technology

The darkness that swept over the Venezuelan capital in the predawn hours of Jan. 3, 2026, signaled a profound shift in the nature of modern conflict: the convergence of physical and cyber warfare. While U.S. special operations forces carried out the dramatic seizure of Venezuelan President Nicolás Maduro, a far quieter but equally devastating offensive was taking place in the unseen digital networks that help operate Caracas.

The blackout was not the result of bombed transmission towers or severed power lines but rather a precise and invisible manipulation of the industrial control systems that manage the flow of electricity. This synchronization of traditional military action with advanced cyber warfare represents a new chapter in international conflict, one where lines of computer code that manipulate critical infrastructure are among the most potent weapons.

To understand how a nation can turn an adversary’s lights out without firing a shot, you have to look inside the controllers that regulate modern infrastructure. They are the digital brains responsible for opening valves, spinning turbines and routing power.

For decades, controller devices were considered simple and isolated. Grid modernization, however, has transformed them into sophisticated internet-connected computers. As a cybersecurity researcher, I track how advanced cyber forces exploit this modernization by using digital techniques to control the machinery’s physical behavior.

Hijacked machines

My colleagues and I have demonstrated how malware can compromise a controller to create a split reality. The malware intercepts legitimate commands sent by grid operators and replaces them with malicious instructions designed to destabilize the system.

For example, malware could send commands to rapidly open and close circuit breakers, a technique known as flapping. This action can physically damage massive transformers or generators by causing them to overheat or go out of sync with the grid. These actions can cause fires or explosions that take months to repair.

Simultaneously, the malware calculates what the sensor readings should look like if the grid were operating normally and feeds these fabricated values back to the control room. The operators likely see green lights and stable voltage readings on their screens even as transformers are overloading and breakers are tripping in the physical world. This decoupling of the digital image from physical reality leaves defenders blind, unable to diagnose or respond to the failure until it is too late.

Historical examples of this kind of attack include the Stuxnet malware that targeted Iranian nuclear enrichment plants. The malware destroyed centrifuges in 2009 by causing them to spin at dangerous speeds while feeding false “normal” data to operators.

Another example is the Industroyer attack by Russia against Ukraine’s energy sector in 2016. Industroyer malware targeted Ukraine’s power grid, using the grid’s own industrial communication protocols to directly open circuit breakers and cut power to Kyiv.

More recently, the Volt Typhoon attack by China against the United States’ critical infrastructure, exposed in 2023, was a campaign focused on pre-positioning. Unlike traditional sabotage, these hackers infiltrated networks to remain dormant and undetected, gaining the ability to disrupt the United States’ communications and power systems during a future crisis.

To defend against these types of attacks, the U.S. military’s Cyber Command has adopted a “defend forward” strategy, actively hunting for threats in foreign networks before they reach U.S. soil.

Domestically, the Cybersecurity and Infrastructure Security Agency promotes “secure by design” principles, urging manufacturers to eliminate default passwords and utilities to implement “zero trust” architectures that assume networks are already compromised.

Supply chain vulnerability

Nowadays, there is a vulnerability lurking within the supply chain of the controllers themselves. A dissection of firmware from major international vendors reveals a significant reliance on third-party software components to support modern features such as encryption and cloud connectivity.

This modernization comes at a cost. Many of these critical devices run on outdated software libraries, some of which are years past their end-of-life support, meaning they’re no longer supported by the manufacturer. This creates a shared fragility across the industry. A vulnerability in a single, ubiquitous library like OpenSSL – an open-source software toolkit used worldwide by nearly every web server and connected device to encrypt communications – can expose controllers from multiple manufacturers to the same method of attack.

Modern controllers have become web-enabled devices that often host their own administrative websites. These embedded web servers present an often overlooked point of entry for adversaries.

Attackers can infect the web application of a controller, allowing the malware to execute within the web browser of any engineer or operator who logs in to manage the plant. This execution enables malicious code to piggyback on legitimate user sessions, bypassing firewalls and issuing commands to the physical machinery without requiring the device’s password to be cracked.

The scale of this vulnerability is vast, and the potential for damage extends far beyond the power grid, including transportation, manufacturing and water treatment systems.

Using automated scanning tools, my colleagues and I have discovered that the number of industrial controllers exposed to the public internet is significantly higher than industry estimates suggest. Thousands of critical devices, from hospital equipment to substation relays, are visible to anyone with the right search criteria. This exposure provides a rich hunting ground for adversaries to conduct reconnaissance and identify vulnerable targets that serve as entry points into deeper, more protected networks.

The success of recent U.S. cyber operations forces a difficult conversation about the vulnerability of the United States. The uncomfortable truth is that the American power grid relies on the same technologies, protocols and supply chains as the systems compromised abroad.

Regulatory misalignment

The domestic risk, however, is compounded by regulatory frameworks that struggle to address the realities of the grid. A comprehensive investigation into the U.S. electric power sector my colleagues and I conducted revealed significant misalignment between compliance with regulations and actual security. Our study found that while regulations establish a baseline, they often foster a checklist mentality. Utilities are burdened with excessive documentation requirements that divert resources away from effective security measures.

This regulatory lag is particularly concerning given the rapid evolution of the technologies that connect customers to the power grid. The widespread adoption of distributed energy resources, such as residential solar inverters, has created a large, decentralized vulnerability that current regulations barely touch.

Analysis supported by the Department of Energy has shown that these devices are often insecure. By compromising a relatively small percentage of these inverters, my colleagues and I found that an attacker could manipulate their power output to cause severe instabilities across the distribution network. Unlike centralized power plants protected by guards and security systems, these devices sit in private homes and businesses.

Accounting for the physical

Defending American infrastructure requires moving beyond the compliance checklists that currently dominate the industry. Defense strategies now require a level of sophistication that matches the attacks. This implies a fundamental shift toward security measures that take into account how attackers could manipulate physical machinery.

The integration of internet-connected computers into power grids, factories and transportation networks is creating a world where the line between code and physical destruction is irrevocably blurred.

Ensuring the resilience of critical infrastructure requires accepting this new reality and building defenses that verify every component, rather than unquestioningly trusting the software and hardware – or the green lights on a control panel.

Saman Zonouz receives funding from the Department of Energy Office of Cybersecurity, Energy Security, and Emergency Response (DOE CESER) and the National Science Foundation (NSF).

– ref. Hacking the grid: How digital sabotage turns infrastructure into a weapon – https://theconversation.com/hacking-the-grid-how-digital-sabotage-turns-infrastructure-into-a-weapon-272874

Source: The Conversation – USA – By Micah Altman, Research Scientist, MIT Libraries, Massachusetts Institute of Technology (MIT)

A growing distrust of expertise is reshaping the terrain of science in the United States.

Since the pandemic, the partisan divide over science has widened dramatically. While 77% of Americans have at least a fair amount of confidence that scientists act in the best interests of the public, that breaks down to 90% of Democrats and 65% of Republicans.

If people think scientists are trying to impose their political beliefs rather than expressing honest scientific judgments in the pursuit of truth, public trust in expert consensus will continue to erode.

With recent events, such as Robert F. Kennedy Jr. replacing the expert vaccine panel at the Department of Health and Human Services, and the Trump administration threatening to withdraw research funding from universities that don’t follow its ideological dictates, the political divide in public perception may grow even deeper.

As social scientists who study the role of science in society, we are deeply concerned about the decline of public trust in expertise, which is often fueled by politicians who manipulate people’s suspicions about experts. Skepticism is sometimes justified, of course. But a system based on expertise is the best one modern democracies have come up with to offer guidance on the various complex issues they face.

Who is an expert?

Before you can place your trust in a community of experts, you need a way to determine who counts as an expert. Modern societies usually do this through a sequence of training within accredited schools and universities – institutions whose reputations depend on their ability to train reliable and trustworthy experts.

Unlike the ancient alchemists’ guilds or modern elites, science is not secret, nor gated by family descent or social ties. Today anyone is permitted to become a scientific expert by attaining academic degrees and certifications and establishing a public track record of published research, teaching and contributions to one’s field.

The government also plays a critical role by requiring doctors or engineers to hold certain degrees or by granting universities formal quality certifications, such as accreditation. As an individual, you can’t evaluate the trustworthiness of every person claiming to have expertise – whether a heart surgeon or an electrician. The governmental license carried by these professionals makes that unnecessary.

In any field of knowledge, there is a web of legitimacy, knotted together by visible signals of trust, such as degrees, publications, affiliations and accreditations. Expertise is a team sport.

What is expert consensus?

The most reliable guidance is based on a rigorous group decision-making process, in which people with diverse training and experience contribute their expertise to a dialogue aimed at reaching consensus. The scientific approach to consensus is transparent and deliberate: Scientific consensus processes – such as the National Academies consensus study process, or a PRISMA review – are systematic in incorporating the credible evidence that is available and synthesizing different expert judgments.

The system, honed over decades, is based on the theory that better decisions can be achieved by systematically aggregating many independent opinions – if the group is well trained, draws from a common body of evidence, relies on a common understanding of research practices, and each of its members are able to independently weigh the evidence.

Such communities of experts arise in many settings, from engineers recommending building codes to epidemiologists proposing policies to contain a viral epidemic.

An expert community doesn’t need everyone to be right – or even to agree – in every case for the process to generate useful results. As long as each person is usually right and the community deliberates systematically on the basis of reason and evidence, the resulting consensus will be the best that can be achieved within the limits of current knowledge.

In short, expert consensus requires trained experts, common evidence and systematic deliberation.

Professional consensus vs. individual opinion

Expert consensus doesn’t mean that experts agree on everything, or that everyone must agree with the experts. In a democracy, expert advice is valuable, but it’s not the last word.

The U.S. Bill of Rights enshrines the idea that freedom of speech is fundamental to good government and to leading good lives. But there’s a distinction between speaking one’s mind and speaking from authority. Experts have a right to express their personal opinions and also a duty to exercise care when speaking in areas of their expertise.

This distinction is at issue in the Chiles vs Salazar case before the Supreme Court. It centers on a Colorado state law that prohibits so-called “conversion therapy” for gay or trans children.

Does doing so violate the free speech rights of therapists? It’s not illegal to believe trans children can be talked out of being trans, it’s just illegal to pursue that practice as a licensed professional, because medical experts have reached a consensus that conversion therapy is both useless and harmful.

Expert consensus is necessary to make sound decisions based on science and evidence, but that doesn’t mean experts must abstain from politics or refrain from expressing dissenting opinions. In fact, political restrictions on scientific debate weaken science, as seen in repressive societies.

What does expert consensus provide?

In our fractious political climate, people sometimes think divergent expert opinions mean that consensus does not exist, or no experts can be trusted. Some people say, “Do your own research,” which often leads to rejecting consensus and falling victim to conspiracies and disinformation.

In practice, consensus is compatible with substantial disagreement. In many fields, scientific consensus deals with broad patterns rather than individual cases. For example, medical experts may agree on the nature of a specific condition, and the average efficacy of a given treatment, yet make different predictions about the benefits for a specific patient.

Society faces pressing questions about the behavior of complex and uncertain systems: How much is climate likely to change if CO₂ emissions continue at the current rate – and what ecological changes should we expect? What accounts for changing cancer rates – and what are the most promising paths to develop a broad “cure”? Are AIs developing intelligence and self-awareness – and how can they be designed to be behave safely? What social institutions are essential for human flourishing – and how can they be preserved?

It’s the fundamental role of democratic government to determine which goals we as a society pursue and how to balance competing values. And when we face high-stakes issues involving complex systems and uncertain approaches, scientific expert consensus can act as an honest broker to provide a menu of possible approaches and predictions for each one’s likely consequences.

Micah Altman received research funding from the National Science Foundation and the Andrew W Mellon Foundation to conduct research related to the science of science, and related to open science.

Philip N. Cohen does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. ‘Expertise’ shouldn’t be a bad word – expert consensus guides science and society – https://theconversation.com/expertise-shouldnt-be-a-bad-word-expert-consensus-guides-science-and-society-271467

Source: The Conversation – USA (3) – By Chad Gibbs, Assistant Professor of Jewish Studies, College of Charleston

Joe Engel was and remains an icon in Charleston, South Carolina. Born in Zakroczym, Poland, he survived Auschwitz and several other concentration camps and fought with the resistance before landing on American shores as a refugee in 1949.

After retirement from his dry-cleaning business, Engel focused his later years on Holocaust education. As part of these efforts, he took to sitting on downtown park benches wearing a name tag that read “Joe Engel, Holocaust Survivor: Ask me questions” – becoming the city’s first public memorial to the victims of Nazi genocide. Knowing he would not be here to impart his message forever, Engel and his friend and fellow survivor Pincus Kolender led a drive to install the permanent memorial that now stands in Charleston’s Marion Square park.

In 2021, I moved to the city to take up my role as a professor and director of Holocaust studies at the College of Charleston. I arrived just in time to meet Engel and to teach many local students who had met him. He died the following year, at age 95.

For years, historians, educators and Jewish groups have been considering how to teach about the Holocaust after the survivors have passed on. Few of today’s college students have ever met a Holocaust survivor. Those who have likely met a child survivor, with few personal memories before 1945. American veterans of the war are almost entirely unknown to our present students; many know nothing of their own family connections to World War II.

Time marches on, distance grows, and what we call “common knowledge” changes. One alarming study from 2018 revealed that 45% of American adults could not identify a single one of the over 40,000 Nazi camps and ghettos, while 41% of younger Americans believe that Nazi Germany killed substantially less than 6 million Jews during the Holocaust.

According to a 2025 study by the Claims Conference, there are somewhat more than 200,000 survivors still alive, though their median age is 87. It is sadly expected that 7 in 10 will pass away within the next decade. With their absence near, how can educators and community members bring this history home, decreasing the perceived distance between the students of today and the lessons of the Holocaust?

Bringing history home

One method that shows promise is helping students realize the connections of their own home and their own time to a genocide that might seem far away – both on the map and in the mind.

In classes on the Holocaust, I now use a set of letters sent by a family of Polish Jews to their relatives in Camden, South Carolina. The letters themselves are powerful sources demonstrating the increasing desperation of Malie Landsmann, the main writer. In 1938, she reached out to her cousin Minnie Tewel Baum, seeking help to escape Adolf Hitler’s Germany.

Even though the two had never met, Minnie tried everything to help her cousin and her family. In the end, however, she was not successful. American immigration barriers and murderous Nazi policy took their toll, with Malie, her husband, Chaim, and their two children, Ida and Peppi, all killed at Auschwitz.

These haunting letters demonstrate the connections of the war to small-town South Carolina. They give the Holocaust a real human face and a connection to places students know.

Letter collections like these are not rare. The College of Charleston holds a second, far larger group of letters, the Helen Stern Lipton Papers, which runs to over 170 pages of correspondence between family members in South Carolina, German-occupied Europe, Russia and even Central Asia. When I was a Ph.D. student, I participated in classes using the Sara Spira postcards sent from a series of ghettos in Poland to rural Wisconsin. Further archives exist all over the United States. Most communities have connections to the Holocaust, whether via artifacts, people with direct ties or both.

The important thing is to teach in ways that can break down the mental barriers created by time and space. It is indeed the same reason that the Auschwitz-Birkenau State Museum created a traveling exhibit called “Auschwitz. Not Long Ago. Not Far Away.”

Learning from descendants

As teachers and professors attempt to bridge these divides, they often invite the descendants of Holocaust survivors to their classes to speak. Descendants can retell the stories of their parents’ or ancestors’ perseverance and survival, but what is more important is their ability to put a human face on these events and show how they remain relevant in the lives of so many.

I take these short visits a step further in a class where students train as oral history interviewers, then conduct recorded conversations with a descendant of survivors. These meetings encourage discussion of family Holocaust history, but only after the student asks the descendant about how they learned about what happened to their parent, grandparent or great-grandparent, and how this might have weighed on their own life years after the war.

This is truly the point here. The most impactful parts of these recordings are almost always the discussions of legacies; of how the families that students meet still live with the enormity of Holocaust trauma.

When a descendant tells students about the past, that is important. But when a descendant speaks of what that past means for them, their family and their community, that is so much more.

Students gain firsthand knowledge of intergenerational trauma; the difficulties of rebuilding; the prevalence of anxiety, worry and depression in survivor homes; and so much more. All of this shows students in no uncertain ways how the Holocaust still has bearing on the lives of people in our communities.

History after memory: A path forward

What’s most heartening about these methods and their successes is what they reveal about what today’s students value. In the age of AI, Big Tech and omnipresent social media, I believe it is still – and maybe even more than ever – the real human connection.

Students are drawn in by the local connections and open up to the stories of real people, brought to them in person. Often, they launch their own research to better understand the letters.

One of my students even helped turn them into classroom materials, now used well beyond our own college. Another did the painstaking work to have four new Stolpersteine, or Stumbling Stone, memorials installed in Berlin to commemorate the Landsmann family.

Never having witnessed them myself, I can only imagine the impact of Joe Engel’s conversations on those park benches in downtown Charleston.

Nothing will ever truly replace the voices of the survivors, but I believe teachers and communities can carry on his work by making history feel local and personal. As everything around us seems to show each day, little could be more important than the lessons of these people, their sources and the Holocaust.

Chad Gibbs does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. Bearing witness after the witnesses are gone: How to bring Holocaust education home for a new generation – https://theconversation.com/bearing-witness-after-the-witnesses-are-gone-how-to-bring-holocaust-education-home-for-a-new-generation-272491

Source: The Conversation – USA – By Laurel Elder, Professor of Political Science, Hartwick College

Taylor Swift’s latest album, “The Life of a Showgirl,” generated a cultural whirlwind: chart-topping success, social media saturation and frenzied debate over her artistic evolution.

Nonetheless, despite this warm reception, opinions on Swift are deeply polarized by party. Democrats are far more likely to view her positively; Republicans are more likely to hold negative views. This partisan divide remains in place even after accounting for age, gender and other demographic differences.

We are political scientists who conduct research on public opinion. In our just-published study, “Mirrorball Politics,” we draw on national survey data to examine how Americans feel about Swift and what those feelings reveal about our politics. What we find is striking: Swift has become a cultural mirror, reflecting our society’s deepest social and political fault lines.

In other words, liking or disliking Swift has become yet another way Americans signal who they are politically. Young women love her, but young men don’t – and that gap matters.

This is part of a broader trend in which cultural preferences and political identity have collapsed into each other. The type of beer you drink, the kind of car you drive, the stores you shop at and now the musical artists you admire have become markers of political belonging – and difference.

Popular entertainment used to be a common space where Americans, regardless of whether they were Republicans or Democrats, could come together and have some fun. Those shared spaces are shrinking – and with them the opportunity for connection across partisan divides.

The Swifties gap

That’s why feelings toward Swift offer warning signs for the future of American politics.

One of the starkest divides we found is between young men and young women. Gen Z women – those born between 1997 and 2012 – admire Swift. Gen Z men, not so much. On a 100-point scale measuring attitudes toward Swift, young women averaged 55, while young men averaged 43 – a statistically significant difference that was not present among older Americans.

This gender gap mirrors the widening political divide among younger Americans that played a pivotal role in the 2024 presidential election. Although a modest gender gap has been a consistent, defining feature of American electoral politics since 1980, the gap among young Americans is huge.

Young women are markedly progressive in their politics. Young men, by contrast, are trending rightward.

Many young men express skepticism toward feminism, discomfort with shifts in gender norms and a growing attraction to more conservative cultural messaging.

Haters gonna hate

This yawning gender gap is also reflected in views regarding Swift.

The strongest predictor of negative views of the singer, aside from partisanship, is “hostile sexism.” This is defined as negative attitudes toward women and a sense that men should dominate.

Our study finds that individuals who believe that women’s achievements come at men’s expense, or that women have too much power, are far more likely to dislike Swift. This effect is especially strong among men and particularly among Republican men.

Swift’s enormous success, artistic autonomy and cultural influence appear to trigger anxieties about women’s power in public life. The backlash is not about her lyrics or her image. It’s about what she represents: a confident, self-directed woman at the center of American culture.

This dynamic reveals the broader challenges facing women in positions of authority, including in politics. Hostile sexism remains a force in American society and a formidable barrier for any woman aspiring to the presidency.

Swift as a visible symbol

Swift didn’t create these divisions – she is simply reflecting them back. But the intensity of the reaction to her success reveals how conflicted America remains about women’s power.

Our study also shows that people who scored high on hostile sexism were much more likely to hold negative views of Kamala Harris during the presidential election of 2024. This mirrors findings from earlier research showing that hostile sexism was one of the strongest reasons voters did not support Hillary Clinton in 2016.

That conflict is not abstract. It is shaping who we elect and whether women can lead without triggering backlash. As the United States marks its 250th anniversary as a democractic nation, we have yet to elect a woman as president, and women remain significantly underrepresented in high-level political positions.

Democracy depends on some measure of shared reality and common ground. When even pop stars become partisan litmus tests, that common ground keeps shrinking.

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

– ref. The only thing limiting Taylor Swift’s popularity is partisan polarization – https://theconversation.com/the-only-thing-limiting-taylor-swifts-popularity-is-partisan-polarization-272884

Source: The Conversation – USA – By Nicole M. Bennett, Ph.D. Candidate in Geography and Assistant Director at the Center for Refugee Studies, Indiana University

When an Immigration and Customs Enforcement agent shot and killed Renee Nicole Good in south Minneapolis on Jan. 7, 2026, what happened next looked familiar, at least on the surface. Within hours, cellphone footage spread online and eyewitness accounts contradicted official statements, while video analysts slowed the clip down frame by frame to answer a basic question: Did she pose the threat federal officials claimed?

What’s changed since Minneapolis became a global reference point for bystander video in 2020 in the wake of George Floyd’s murder is how thoroughly camera systems, especially smartphones, are now entangled with the wider surveillance ecosystem.

I am a researcher who studies the intersection of data governance, digital technologies and the U.S. federal government. The hard truth for anyone filming law enforcement today is that the same technologies that can hold the state accountable can also make ordinary people more visible to the state.

Recording is often protected speech. But recording, and especially sharing, creates data that can be searched, linked, purchased and reused.

Video can challenge power. It can also attract it.

Targeting the watchers

Documentation can be the difference between an official narrative and an evidence-based public record. Courts in much of the U.S. have recognized a First Amendment right to record police in public while they perform official duties, subject to reasonable restrictions. For example, you can’t physically interfere with police.

However, that right is uneven across jurisdictions and vulnerable in practice, especially when police claim someone is interfering, or when state laws impose distances people must maintain from law enforcement actions – practices that chill filming.

While the legal landscape of recording law enforcement is important to understand, your safety is also a major consideration. In the days after Good’s killing, Minneapolis saw other viral clips documenting immigration enforcement and protests, along with agents’ forceful engagement with people near those scenes, including photographers.

It’s difficult to know how many people have been targeted by agents for recording. In Illinois in late 2025, the U.S. Press Freedom Tracker, operated by advocacy group Freedom of the Press Foundation, documented multiple incidents in which journalists covering ICE-facility protests reported being shot with crowd-control munitions or tackled and arrested while filming.

These incidents underscore that documentation isn’t risk-free. There is an additional layer of safety beyond the physical to take into account: your increased risk of digital exposure. The legal right to record doesn’t prevent your recording from becoming data that others can use.

Both camera and tracking device

In practical terms, smartphones generate at least three kinds of digital exposure.

The first is identification risk, including through facial recognition technology. When you post footage, you may be sharing identifiable faces, tattoos, voices, license plates, school logos or even a distinctive jacket. That can enable law enforcement to identify people in your recordings through investigative tools, and online crowds to identify people and dox or harass them, or both.

That risk grows when agencies deploy facial recognition in the field. For example, ICE is using a facial recognition app called Mobile Fortify.

Facial recognition accuracy also isn’t neutral. National Institute of Standards and Technology testing has documented that the technology does not perform equally across different demographic groups, meaning the risk of misidentification is not evenly distributed across groups. For example, studies have shown lower recognition accuracy for people with darker skin color.

Second is the risk of revealing your location. Footage isn’t just images. Photos and video files often contain metadata such as timestamps and locations, and platforms also maintain additional logs. Even if you never post, your phone still emits a steady stream of location signals.

This matters because agencies can obtain location through multiple channels, often with different levels of oversight.

Agencies can request location or other data from companies through warrants or court orders, including geofence warrants that sweep up data about every device in a place during a set time window.

Agencies can also buy location data from brokers. The Federal Trade Commission has penalized firms for unlawfully selling sensitive location information.

Agencies also use specialized “area monitoring” tools: ICE purchased systems capable of tracking phones across an entire neighborhood or block over time, raising civil liberties concerns. The tools could track a phone from the time and place of a protest – for example, to a home or workplace.

There are more pathways for tracking than most people realize, and not all are constrained by the courtroom rules people picture when they think “warrant.”

The third type of potential exposure is the risk of having your phone seized. If police seize your phone, temporarily or for evidence, your exposure isn’t just the video you shot. It can include your contacts and message history, your photo roll, location history and cloud accounts synced to the device.

Civil liberties groups that publish protest safety guidance consistently recommend disabling the face and fingerprint unlocking features and using a strong passcode. Law enforcement officials can compel you to use biometrics more easily in some contexts than reveal memorized secrets.

Digital safety when recording police

This isn’t legal advice, and nothing is risk-free. But if you want to keep the accountability benefits of filming while reducing your digital exposure, here are steps you can take to address the risks.

Before you go, decide what you’re optimizing for, whether it is preserving evidence quickly or minimizing traceability, because those goals can conflict. Harden your lock screen with a long passcode, disable face and fingerprint ID, turn off message previews and reduce the risk of what you carry by logging out of sensitive accounts and removing unnecessary apps. Even consider leaving your primary phone at home if that’s realistic.

If you’re worried about having your recording deleted, plan ahead for how you’ll secure footage. You can either send it to a trusted person through an encrypted app or keep it offline until you’re safe.

While filming, keep your phone locked when possible using the camera-from-lock-screen feature and avoid livestreaming if identification risk is high, since live posts can expose your location in real time. Focus on documenting context rather than creating viral clips: Capture wide shots, key actions and clear time-and-place markers, and limit close-ups of bystanders. Assume faces are searchable, and if you can’t protect people in the moment, consider waiting to share until you can edit safely.

Afterward, back up securely and edit for privacy before posting by blurring faces, tattoos and license plates, removing metadata, and sharing a privacy-edited copy instead of the raw file. Think strategically about distribution because sometimes it’s safer to provide footage to journalists, lawyers or civil rights groups who can authenticate it without exposing everyone to mass identification. And remember the “second audience” beyond police, including employers, trolls and data brokers.

A new reality

Recording law enforcement in public is often a vital democratic check, especially when official narratives and reality conflict, as they have in Minneapolis since Jan. 7, 2026.

But the camera in your pocket is also part of a maturing surveillance ecosystem, one that links video, facial recognition and location data in ways most people never consented to and often don’t fully recognize.

In 2026, filming still matters. The challenge is ensuring the act of witnessing doesn’t quietly become a new form of exposure.

Nicole M. Bennett is affiliated with the Center for Refugee Studies at Indiana University.

– ref. Filming ICE is legal but exposes you to digital tracking – here’s how to minimize the risk – https://theconversation.com/filming-ice-is-legal-but-exposes-you-to-digital-tracking-heres-how-to-minimize-the-risk-273566

Source: The Conversation – USA – By Timothy Joseph, Professor of Classics and the Director of Peace and Conflict Studies, College of the Holy Cross

In a week filled with news about President Donald Trump’s aggressive moves to take control of Greenland, the world got a window into his thinking about the concept of “peace.”

“Considering your Country decided not to give me the Nobel Peace Prize for having stopped 8 Wars PLUS, I no longer feel an obligation to think purely of Peace, although it will always be predominant, but can now think about what is good and proper for the United States of America,” Trump said in the message to Norway’s prime minister, Jonas Gahr Støre.

Trump has long coveted the Nobel Peace Prize. In his second term as president, he has styled himself as a peacemaker, as his message to Støre demonstrates. But as I have learned from my work as a scholar of Roman history and rhetoric, the word “peace” can mean something entirely different when used by those wielding power.

In the year 98 CE, the Roman historian Tacitus wrote, “With lying names they call theft, slaughter, and plunder ‘control,’ and when they make a wasteland, they call it ‘peace.’”

This line, said of the Romans by an enemy of Rome in Tacitus’ work “Agricola,” has had a long and varied afterlife among those commenting on imperialism.

Nearly 2,000 years after Tacitus’ time, U.S. Sen. Robert Kennedy used the phrase in a 1968 speech questioning the U.S. war in Vietnam; the Irish poet Seamus Heaney echoed it in a 1974 poem figuring his homeland’s centuries of desolation; more recently still, the HBO series “Succession” reworked the words into a critique of the show’s despotic central character.

The quotation has had staying power because it cuts to the core of how talk of peace can be used as a tool of war and power acquisition.

At the one-year mark of the second Trump administration, these words from two millennia ago speak as presciently as ever.

Time and again over the last year, Trump has branded acts of war with the language of peace. More broadly, his administration’s persistent styling of Trump as a “President of Peace” and his continuous claims of entitlement to the Nobel Peace Prize have moved in tandem with a growing agenda of military aggression, both foreign and domestic.

‘War is peace’

Tacitus, who lived from c. 55 to c. 120 CE, places his critique of Roman imperial rhetoric into the mouth of Calgacus, the possibly fictionalized chief of the Caledonians in northern Britain. The words, delivered in a speech before the Battle of Mons Graupius in 83 CE, anticipated what was to come: a crushing Roman victory and the devastation of the Caledonian people.

Calgacus’ aphorism gets at something fundamental about Roman imperial propaganda, which presented the cessation of war – on their terms – as “peace.” A physical representation of this is the Altar of Augustan Peace, from 9 BCE, which was built after the warlord Augustus’ victories in foreign and civil wars. A reconstruction of one of the monument’s friezes includes the personified goddess Roma sitting atop war spoils. Peace for Rome was tantamount to victory for Rome – or, as in this case, for one of Rome’s strongmen.

And while Tacitus, an accomplished Roman politician and provincial governor, was himself no opponent of Roman imperialism, it is significant that he crafts a speech for an enemy of Rome that gives the lie to the Roman rhetoric of peace. The non-Roman’s perspective on Romans’ “lying names” cuts through the posturing of the imperialist.

Calgacus’ critique thus puts into relief the jarring juxtapositions the world has seen and heard from Trump over the last year.

On Dec. 31, 2025, Trump declared that his New Year’s resolution for 2026 was “peace on Earth.” Three days later, he invaded Venezuela and captured President Nicolás Maduro, a military action that left 100 dead and a humanitarian crisis looming. Apart from claiming control of some $2.5 billion of Venezuela’s oil reserves, Trump has provided few details about how he will personally “run the country.”

A similarly striking disconnect between rhetoric and reality came earlier in 2025 with the U.S.’s June 21 bombing of Iran, which the White House X account celebrated with the declaration “CONGRATULATIONS WORLD, IT’S TIME FOR PEACE!” Some seven months later, as the Iranian regime violently suppresses broad protests, Trump is weighing additional acts of war, saying that “the military is looking at it and we’re looking at some strong options.”

In Gaza, Trump is chairing a “Board of Peace” to oversee the ceasefire between Israel and Hamas and to implement a new government. The Israel/Hamas War is one of eight wars Trump claims credit for ending.

As with the seven other cases, the claim to have brought peace in Gaza lacks substantiation.

From the announcement of the ceasefire on Oct. 10, 2025, through Dec. 30, 2025, 414 Palestinians have been killed and 1,145 injured by Israeli attacks. That is, the war rages on.

Now Trump, apparently out of resentment at not being award the Nobel, declares that he will seize Greenland “one way or the other” and that Cuba must accept his terms on Venezuelan oil shipments “before it is too late.”

At home, Trump ramps up the presence of ICE, whose violent approach to enforcement has had deadly consequences for 32 people in custody and one woman protester.

All this as FIFA, the international governing body for soccer, awards Trump its first-ever Peace Prize; and as he stamps his name on – after defunding – the U.S Institute of Peace.

Spread of ‘peace’ rhetoric

Today’s dizzying clashes in word and deed are illuminated by Calgacus’ searing words, which show how easily the rhetoric of peace can be used to cover for or distract from acts of war.

At the same time, Tacitus points readers to the prevalence and thus the normalization and commonness of this rhetoric, which can become an inseparable corollary of a program of making war.

Indeed, Tacitus presents similar indictments of Roman imperial rhetoric twice elsewhere in his writing, again from the perspectives of those threatened by Rome.

For both the Batavians, of modern-day Netherlands, in the “Histories” and another group of Britons in the “Annals,” the great menace to their peoples is Roman “peace.”

Timothy Joseph does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. From ancient Rome to today, war-makers have talked constantly about peace – https://theconversation.com/from-ancient-rome-to-today-war-makers-have-talked-constantly-about-peace-273095

Source: The Conversation – USA (2) – By Hélène Nguemgaing, Assistant Clinical Professor of Critical Resources & Sustainability Analytics, University of Maryland

Across Appalachia, rust-colored water seeps from abandoned coal mines, staining rocks orange and coating stream beds with metals. These acidic discharges, known as acid mine drainage, are among the region’s most persistent environmental problems. They disrupt aquatic life, corrode pipes and can contaminate drinking water for decades.

However, hidden in that orange drainage are valuable metals known as rare earth elements that are vital for many technologies the U.S. relies on, including smartphones, wind turbines and military jets. In fact, studies have found that the concentrations of rare earths in acid mine waste can be comparable to the amount in ores mined to extract rare earths.

Scientists estimate that more than 13,700 miles (22,000 kilometers) of U.S. streams, predominantly in Pennsylvania and West Virginia, are contaminated with acid mine discharge.

We and our colleagues at West Virginia University have been working on ways to turn the acid waste in those bright orange creeks into a reliable domestic source for rare earths while also cleaning the water.

Experiments show extraction can work. If states can also sort out who owns that mine waste, the environmental cost of mining might help power a clean energy future.

Rare earths face a supply chain risk

Rare earth elements are a group of 17 metals, also classified as critical minerals, that are considered vital to the nation’s economy or security.

Despite their name, rare earth elements are not all that rare. They occur in many places around the planet, but in small quantities mixed with other minerals, which makes them costly and complex to separate and refine.

China controls about 70% of global rare earth production and nearly all refining capacity. This near monopoly gives the Chinese government the power to influence prices, export policies and access to rare earth elements. China has used that power in trade disputes as recently as 2025.

The United States, which currently imports about 80% of the rare earth elements it uses, sees China’s control over these critical minerals as a risk and has made locating domestic sources a national priority.

Although the U.S. Geological Survey has been mapping potential locations for extracting rare earth elements, getting from exploration to production takes years. That’s why unconventional sources, like extracting rare earth elements from acid mine waste, are drawing interest.

Turning a mine waste problem into a solution

Acid mine drainage forms when sulfide minerals, such as pyrite, are exposed to air during mining. This creates sulfuric acid, which then dissolves heavy metals such as copper, lead and mercury from surrounding rock. The metals end up in groundwater and creeks, where iron in the mix gives the water an orange color.

Expensive treatment systems can neutralize the acid, with the dissolved metals settling into an orange sludge in treatment ponds.

For decades, that sludge was treated as hazardous waste and hauled to landfills. But scientists at West Virginia University and the National Energy Technology Laboratory have found that it contains concentrations of rare earth elements comparable to those found in mined ores. These elements are also easier to extract from acid mine waste because the acidic water has already released them from the surrounding rock.

Experiments have shown how the metals can be extracted: Researchers collected sludge, separated out rare earth elements using water-safe chemistry, and then returned the cleaner water to nearby streams.

It is like mining without digging, turning something harmful into a useful resource. If scaled up, this process could lower cleanup costs, create local jobs and strengthen America’s supply of materials needed for renewable energy and high-tech manufacturing.

But there’s a problem: Who owns the recovered minerals?

The ownership question

Traditional mining law covers minerals underground, not those extracted from water naturally running off abandoned mine sites.

Nonprofit watershed groups that treat mine waste to clean up the water often receive public funding meant solely for environmental cleanup. If these groups start selling recovered rare earth elements, they could generate revenue for more stream cleanup projects, but they might also risk violating grant terms or nonprofit rules.

To better understand the policy challenges, we surveyed mine water treatment operators across Pennsylvania and West Virginia. The majority of treatment systems were under landowner agreements in which the operators had no permanent property rights. Most operators said “ownership uncertainty” was one of the biggest barriers to investment in the recovery of rare earth elements, projects that can cost millions of dollars.

Not surprisingly, water treatment operators who owned the land where treatment was taking place were much more likely to be interested in rare earth element extraction.

West Virginia took steps in 2022 to boost rare earth recovery, innovation and cleanup of acid mine drainage. A new law gives ownership of recovered rare earth elements to whoever extracts them. So far, the law has not been applied to large-scale projects.

Across the border, Pennsylvania’s Environmental Good Samaritan Act protects volunteers who treat mine water from liability but says nothing about ownership.

This difference matters. Clear rules like West Virginia’s provide greater certainty, while the lack of guidance in Pennsylvania can leave companies and nonprofits hesitant about undertaking expensive recovery projects. Among the treatment operators we surveyed, interest in rare earth element extraction was twice as high in West Virginia than in Pennsylvania.

The economics of waste to value

Recovering rare earth elements from mine water won’t replace conventional mining. The quantities available at drainage sites are far smaller than those produced by large mines, even though the concentration can be just as high, and the technology to extract them from mine waste is still developing.

Still, the use of mine waste offers a promising way to supplement the supply of rare earth elements with a domestic source and help offset environmental costs while cleaning up polluted streams.

Early studies suggest that recovering rare earth elements using technologies being developed today could be profitable, particularly when the projects also recover additional critical materials, such as cobalt and manganese, which are used in industrial processes and batteries. Extraction methods are improving, too, making the process safer, cleaner and cheaper.

Government incentives, research funding and public-private partnerships could speed this progress, much as subsidies support fossil fuel extraction and have helped solar and wind power scale up in providing electricity.

Treating acid mine drainage and extracting its valuable rare earth elements offers a way to transform pollution into prosperity. Creating policies that clarify ownership, investing in research and supporting responsible recovery could ensure that Appalachian communities benefit from this new chapter, one in which cleanup and clean energy advance together.

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

– ref. America’s next big clean energy resource could come from coal mine pollution – if we can agree on who owns it – https://theconversation.com/americas-next-big-clean-energy-resource-could-come-from-coal-mine-pollution-if-we-can-agree-on-who-owns-it-272029