Key insights:

• • • Unauthorized practice of law doctrine is a poor fit for regulating AI and legal technology — UPL remains important when people represent others in court or affect legal proceedings, but it does not translate cleanly to software. Extending UPL to software moves the doctrine away from its original purpose and toward regulating the existence of tools rather than the risk of harm.

    • Legal technology should be regulated through consumer protection principles, not tool-based restrictions — Rather than asking whether an AI product or software platform “practices law,” regulators should focus on whether the tool misleads users, performs as advertised, provides adequate transparency, or causes demonstrable consumer harm.

    • A harm-based framework can protect consumers while expanding access to justice — Because most legal needs remain unmet, AI and justice tech can provide meaningful support to people who would otherwise receive no legal help. Safe harbors, disclosures, and accountability for fraud, negligence, or false advertising would better balance innovation with consumer protection.

This is the second of a two-part blog series examining how regulators, the legal profession, and individual litigants are looking at the unauthorized practice of law (UPL). We first looked at the history of UPL, and now this installment suggests a consumer protection-based method of regulation to replace today’s supplier-based regulations.

The legal industry has reached an inflection point in which the unauthorized practice of law (UPL) doctrine is no longer the right framework for regulating modern legal services. As technology reshapes how legal help is delivered, the focus must shift from policing who can provide legal support to ensuring that consumers are protected from harm.

This does not mean dismantling the doctrine entirely. UPL continues to serve an important function in which individuals represent others in court or otherwise engage in conduct that affects the integrity of legal proceedings — because courts need enforceable boundaries around who may appear before them.

Those considerations, however, do not translate cleanly to today’s AI-driven advanced technology. Extending UPL to software may shift the doctrine away from its original purpose and toward regulating the existence of tools rather than the risk of harm. A more effective approach is to apply existing consumer protection principles — such as fraud, negligence, and false advertising — to evaluate whether legal technologies are delivering accurate, transparent, and reliable support for users.

UPL continues to serve an important function in which individuals represent others in court or otherwise engage in conduct that affects the integrity of legal proceedings — because courts need enforceable boundaries around who may appear before them.

Over the past several decades, we have bent UPL law to fit emerging models of legal assistance, but with AI we have reached the point at which we should not attempt to stretch it further. AI has expanded the capabilities of legal technology beyond document automation to include research, summarization, and guided analysis. These tools are now widely available and are being used by individuals who would otherwise navigate legal issues without assistance.

At the same time, familiar regulatory arguments are being applied to these new tools. Assertions that such systems constitute UPL rely on assumptions that are increasingly difficult to reconcile with how these technologies function and are used.

Users generally understand that these systems are not lawyers. Engagement with AI tools is driven by accessibility, cost, and convenience, particularly in a landscape in which a substantial portion of legal needs go unmet. The more relevant inquiry is whether these tools provide a meaningful improvement compared to having no assistance at all.

Shifting from UPL to consumer protection

When consumers turn to technology, outcomes will vary, as they do across all forms of legal support. When issues arise, existing legal frameworks already provide mechanisms for accountability. Questions of fraud, negligence, and misleading representations can be addressed through established consumer protection laws without relying on an expanded interpretation of UPL.

Focusing on demonstrable harm rather than the mere existence of a tool aligns regulatory efforts with their intended purpose. It also reduces the risk of limiting innovation that could address persistent gaps in access to legal services encountered by so many individuals today. When liability is tied to the mere provision of technology, rather than to harmful conduct, the result is often reduced investment and slower development of potentially beneficial solutions.

Some jurisdictions have begun to adopt approaches that reflect this distinction. Non-prosecution policies, disclosure requirements, and clearly defined safe harbors for AI-driven tools can provide a framework in which innovation can proceed alongside appropriate safeguards. Indeed, these models emphasize transparency and consumer awareness while allowing for continued experimentation and improvement.

Legal doctrine in transition

Whether state regulators drive the change or watch from the sidelines, there are broader legal considerations on the horizon. On the federal level, the U.S. Federal Trade Commission (FTC) has already signaled that a change towards harm-based regulation as opposed to tool-centered regulation is coming.

In his concurrence in , which had billed itself to consumers as “the world’s first robot lawyer,” :

“My vote should not be taken as support for the State Bar of California’s claim that DoNotPay was engaged in the unauthorized practice of law. The Commission does not enforce state occupational-licensing laws like California’s unauthorized-practice-of-law prohibition. And if a company were to create a computer system capable of giving accurate legal advice and drafting effective legal documents, or honestly advertise a system that provides something less, I doubt that the aggressive enforcement of lawyers’ monopoly on legal service would serve the public interest.”

This aligns with remarks from U.S. Supreme Court Justice Neil Gorsuch’s confirmation hearing when he stated: “Why is it that every time certain companies that provide online legal services for basic things get sued every time they move into a new State?”

While approaching it from different angles, courts are arriving at similar positions. In , an Oregon court of appeals case about fabricated citations, the court stated: “Regardless of provider, a generative artificial intelligence program is not, itself, a lawyer.” While perhaps not intended, the logical extension of this is that a tool cannot be engaged in UPL — only the human using it can.

Finally, recent judicial reasoning, such as in the Supreme Court case of , suggests a closer examination of attempts to regulate speech by categorizing it as professional activity. The Court found professional speech protected by an 8-1 vote, suggesting bipartisan questions about whether professional licensing can continue to restrict speech.

Aligning regulation with reality

Within this evolving landscape, the central policy question is how best to protect consumers while enabling meaningful improvements in access to legal support. Frameworks designed for earlier models of service delivery can be difficult to apply effectively to new forms of technology without producing unintended consequences.

Instead, a consumer-focused approach can direct attention to the quality, accuracy, and transparency of services. It can evaluate whether users are misled, whether tools perform as described, and whether harm can be identified and addressed.

While AI-driven technology offers a way to extend the reach of legal support systems and to develop solutions that operate at a scale not previously achievable, the concept of UPL is still a valid one, albeit within a more limited and clearly defined scope.

As the legal system rapidly evolves, aligning regulatory approaches with current realities allows for both the protection of consumers and the development of the tools that expand access to justice in practical and sustainable ways.

You can find more about the challenges around issues of access justice here

Key highlights:

• • • How AI-native firms redefine the lawyer’s role — AI-native firms like Paralex are gravitating toward a “technician” archetype, which puts less emphasis on the trusted-advisor dynamic that has long defined the attorney-client relationship.

    • The profession may be heading toward a two-tier split — As AI-native firms grow and normalize this operating model for a new generation of attorneys, the legal profession may bifurcate into a smaller cohort of relationship-driven advisors who provide deep, context-rich counsel; and a larger pool of proficient, AI-assisted technicians working at high volume.

    • AI firms can highlight how future lawyers learn — AI-native law firms are elevating a long-standing mentorship gap that threatens to erode how the next generation of lawyers develop independent judgment; and addressing it will require both creative AI-assisted solutions and more deliberate frameworks for deciding which cognitive tasks should remain done by humans.

The opportunity of starting a native AI law firm to test an idea is intriguing to some lawyers, especially those with an entrepreneurial instinct and determination to see the idea through. When founded , he aspired to democratize legal services for small businesses and leveraged AI to do so. His 29 years of practicing law had shown him the inefficiency and costly downsides of the billable hour; and he hypothesized that if the workflow could be automated with an attorney in the loop and could charge one-tenth of what it normally cost, demand would follow.

The reality has been more complicated and more instructive for the future of legal practice, Candelmo explains, as he offered a candid accounting of what Paralex has learned in practice.

Building for underserved small business owners

Paralex was built around a tiered service model covering everything from verified legal Q&A to AI-assisted contract drafting. AI handles the intake and first drafts at every stage, and the attorney handles the judgment. The small business transactional law vertical was a deliberate bet because the practice area is most amenable to pattern recognition and workflow automation. In addition, small business represents one of the largest pools of underserved legal clients.

Candelmo has learned that affordability alone does not unlock demand. The long-cited statistic that “60% of small businesses never use a lawyer because of cost” overstates how much of that gap is price-driven. Indeed, a meaningful portion of business owners appear to not want legal counsel at any price. Free AI tools have compounded this learning because ChatGPT, Claude, and Gemini can produce a plausible contract or answer a legal question at zero cost. “People feel that maybe it’s just good enough,” Candelmo says.

How AI-native firms redefine concept of a lawyer

AI-native firms like Paralex are discovering they need to develop exclusively the “technician archetype” among its lawyers. The attorneys who thrive in Paralex’s workflow are those most comfortable operating at volume, untroubled by the absence of ongoing client relationships, and motivated by clean execution rather than the slower cultivation of client relationships. Candelmo describes them as comfortable with gig work because they want to be paid for what they produce rather than chasing invoices.

Young attorneys need to master the tools but not outsource their judgment to them. And they should seek out senior attorneys and cultivate human relationships that will make them more than a technician.

Candelmo shares that the trusted-advisor attorney who deeply knows a client’s business, anticipates problems before they arise, and provides counsel grounded in years of accumulated context is largely absent from the Paralex experience. He describes AI-native firms’ role as taking out the unnecessary back-and-forth that occurs in traditional law firms’ practices. At the same time, AI-native firms start out narrowly servicing a vertical by providing legal services that are optimizing for efficiency and relatively less complex.

The implication is significant for lawyers and their professional identity. As native AI firms grow and attract a generation of attorneys for whom this model is normal, the profession might be more likely to bifurcate between a smaller cohort of relationship-driven advisors on the one hand, and a larger pool of technically proficient, AI-assisted attorneys working at volume on another.

A generation of lawyers with no one to learn from

What Candelmo says he worries most about is who will teach the next generation of lawyers how to think. In AI-native environments, a junior attorney working at high throughput may review AI-generated output quickly, trust it, and move on. The output looks complete — but there is no obvious signal that something important was missing and no senior attorney to say why it matters.

Candelmo’s proposed solution is a second layer of AI tools, such as simulation tools, that can function like a senior lawyer. It reviews the initial output, flags gaps, and provides the kind of annotated feedback that would have come from a partner review in a traditional law firm.

His advice to young attorneys is to master the tools, but do not outsource your judgment to them. And they should seek out senior attorneys and cultivate human relationships that will make them more than a technician, Candelmo adds. “Ensure that your humanness, your human relationship skills make you stand apart.”

As native AI firms grow and attract a generation of attorneys for whom this model is normal, the profession might be more likely to bifurcate between a smaller cohort of relationship-driven advisors on the one hand, and a larger pool of technically proficient, AI-assisted attorneys working at volume on another.

In addition, , Partner at Foley and Gardner and adjunct professor at the teaches at the University of Wisconsin Law School, goes one step further and advocates for adding a conscious step before instinctively turning to AI tools. He suggests each lawyer first ask themselves, “What cognitive function is being delegated to GenAI at each step in the workflow?”

In the current state, the AI conversation within the legal ecosystem continues in a good-or-bad binary rather than simply asking when AI use is beneficial and when it is risky, which is increasingly what law students are asking for. For example, the announced a policy that bans students from using AI for class assignments and during exams, although students can still use AI for research to identify sources.

The experiences of Candelmo and Paralex, alongside the broader debate playing out across the legal ecosystem, make it clear that the legal profession is being forced to make deliberate choices about what lawyers are for, which cognitive tasks should remain human, and how professional judgment is developed and passed on.

The law firms and legal institutions that build thoughtful frameworks for when and how AI should be used will create a profession that is both more efficient and more capable of producing the kinds of lawyers that clients and society will continue to need.

You can find more about

Key highlights:Ěý

• • • The scale of risk demands urgent attention — The World Cup’s five-week span across three nations creates a human trafficking risk profile far beyond any previous North American sporting event.

    • Geographic exposure extends far beyond host cities — Unlike the Super Bowl, where risk is concentrated in one metro area, the World Cup’s national identity-driven fan engagement means every city in the US, Canada, and Mexico is effectively a participant city.

    • Cross-sector preparation is the most critical investment — Cutting down siloed operations among law enforcement, financial institutions, and NGOs is required, that means establishing financial institution task forces, training frontline bank branch employees to recognize trafficking indicators, sharing cross-sector information, and amplifying public awareness campaigns before the tournament begins is crucial.

The 2026 FIFA World Cup will be the largest sporting event ever hosted on North American soil, a tournament with 104 matches spanning more than five weeks across three nations and drawing an estimated 6.5 million visitors from around the world. While the United States hosts large sporting events like the Super Bowl each year, the World Cup brings with it the unique challenges of length of time, fan influx from around the globe, and geographic expansion.

Assessing the scale of human trafficking risk

To understand the magnitude of the human trafficking risk involved in events such as this, it is useful to apply a framework that accounts for three variables: i) the likelihood of a trafficking event; ii) the potential extent of damage; and iii) the duration of exposure. When that framework is applied to the 2026 World Cup, the human trafficking risk associated with the event registers high due to numerous factors.

For more on this, tune into the Thomson Reuters Institute’s latest “Clarity” podcast

The most significant differentiating factor of the World Cup is its time duration. The Super Bowl is a single-day event, and the Olympics run approximately two weeks. The 2026 World Cup spans more than five weeks across three nations, a duration that has no modern sporting equivalent. The last three World Cups, held in Brazil, Russia, and Qatar, offer limited comparative value given the substantial differences in legal frameworks, cultural contexts, and infrastructure. For purposes of risk assessment, this is why the Super Bowl represents the most relevant domestic benchmark, even though it falls considerably short as a true comparison.

Human trafficking evidence from the most recent Super Bowl

The most recent Super Bowl, held in the San Francisco Bay Area in February 2026, illustrates the scale of the human trafficking challenge. A coordinated anti-trafficking campaign conducted across 11 Bay Area counties resulted in the recovery of 73 sex trafficking victims, including 10 minors, and 29 arrests, all in connection with a single-day event.

Sex advertisement data from that period further substantiates the scale of human trafficking concern. In the months preceding the event, advertisement volume rose steadily before spiking dramatically during Super Bowl weekend and declining sharply in the days that followed. Analysis that was restricted to advertisements referencing the Super Bowl by name showed trend lines that remained essentially flat until the event itself, at which point volume surged significantly.

Likewise, examination of phone numbers associated with those advertisements revealed organized and purposeful movement. Nearly 500 unique numbers that had posted sex advertisements in other states in the preceding weeks appeared in San Francisco during the event.

The risk of human trafficking expanding beyond the host city is one additional insight uncovered during the anti-trafficking operation during the Super Bowl. Advertisements referencing the Super Bowl spiked simultaneously in Boston and Seattle, the home cities of the two competing teams. In the context of the World Cup, every city in the United States, Mexico, and Canada is effectively a participant city, and national identity rather than team affiliation drives fan engagement. The geographic distribution of risk is therefore exponentially greater than anything observed around the Super Bowl.

Hotspots of sex ads

What anti-trafficking partners should do now

Those organizations and institutions that take action in advance of the World Cup will be substantially better positioned to detect exploitation and protect vulnerable individuals. More specifically, these organizations should:

• Establish financial institution task forces in advance of the event — Convening local financial institutions to align on existing practices and identify gaps will aid in ensuring all parties are on the same page. It also establishes relationships and procedures that cannot be built effectively during a five-to-six-week surge in cross-border transactions. Activating established information-sharing mechanisms, such as the processes supporting the filing of and the , will be essential for detection and pattern recognition.
• Institute branch-level employee training at local financial institutions — Frontline employees possess local knowledge that no centralized system can replicate. A branch employee in a high-traffic urban location understands the patterns of their customer base and is often the first to recognize when something is amiss. What they frequently lack is the context in which to interpret that instinct and the guidance to act upon it. Addressing that training gap before the World Cup represents one of the highest-value preparedness investments available to financial institutions at this time.
• Dismantle institutional silos — Siloed operations, in which law enforcement, financial institutions, and non-governmental organizations (NGOs) each operate independently, represent the least effective organizational posture for an event of this scale. Institutions that establish cross-sector relationships and information-sharing commitments in advance will be meaningfully better equipped to respond.
• Develop and amplify public awareness campaigns — Research demonstrates that sustained public awareness campaigns and visible law enforcement presence reduce demand. Host cities, law enforcement agencies, and NGOs should treat this as actionable guidance in planning their response strategies.

The 2026 FIFA World Cup is not simply another major sporting event. The institutions, agencies, and organizations that approach it as such will find themselves unprepared for a scale of human trafficking risk that North America has never previously encountered.

You can find more about the resources, tools, and information that cities and organizations need to addressĚýhuman trafficking around large-scale sporting events atĚýthe Thomson Reuters Institute’s Large-Scale Public Events Toolkit here

Key insights:

• • • AI can improve officer safetyĚý— By helping them prepare for high-risk situations and make better decisions under pressure, advanced technology can enhance officer safety.

    • AI can increase operational efficiencyĚý— AI can reduce administrative burdens and improve efficiency overall, allowing officers to spend more time on police work.

    • Responsible implementation is essentialĚý— To ensure AI strengthens public trust while protecting civil liberties, proper guardrails and oversight need to be enacted.

Each year, during , we pause to honor the brave men and women in law enforcement who have made the ultimate sacrifice in service to their communities. As we pay tribute to those we have lost, we are reminded of the inherent dangers officers face every day.

In recognition of the importance of reflection and advancement, it is imperative that we examine the responsible application of emerging technologies, especially AI, to enhance officer safety, support their objectives, and reinforce overall public safety.

AI is already being integrated into public safety systems in meaningful, measurable ways. When guided by strong ethical principles, transparency, and commitment to community trust, AI can serve as a force multiplier and a protective partner for members of law enforcement. The goal is not to replace officers, of course, but to equip them with better tools, that allow them to reduce risk and return home safely after every shift.

Improving situational awareness and operational readiness

One of the most immediate benefits of AI in law enforcement is its ability to enhance situational awareness. When officers respond to a call, the first minutes on scene are often the most critical — and the most dangerous. AI can help reduce uncertainty by providing rapid access to relevant information.

For example, AI-powered systems can analyze incident data, criminal records, and community reports to give officers a clearer picture of what to expect when they arrive on scene. This includes identifying patterns of violence, recognizing repeat offenders, or flagging locations that may have a history of high-risk activity. Such insights allow for better preparation, smarter deployment, and more informed decision-making under pressure.

Additionally, AI can assist in public records and open-source searches, pulling critical data from comprehensive databases, the internet, and connected devices in seconds rather than hours. This immediate access to information enables faster, more effective responses. In short, AI can save valuable time when seconds count.

Streamlining administrative work to focus on the mission

Law enforcement officers spend a significant portion of their time on administrative duties, such as writing incident reports and managing court schedules and citations. These tasks, while necessary, take officers away from community engagement and proactive policing.

AI can help reduce this administrative burden by automating routine documentation. Natural language processing tools can draft reports based on officer input, ensuring consistency and freeing up time for frontline duties. Similarly, AI-driven scheduling systems can optimize shift assignments, account for court appearances, and manage on-call rotations. This AI-enabled administrative assistance goes a long way in ensuring that staffing levels are appropriate and that officers are not overburdened.

When guided by strong ethical principles, transparency, and commitment to community trust, AI can serve as a force multiplier and a protective partner for members of law enforcement.

By reducing the administrative load, AI allows officers to focus on what they do best — serving and protecting their communities. This not only improves job satisfaction among officers themselves but also increases operational efficiency and public safety outcomes.

Building guardrails for responsible AI use

As with any powerful advanced technology, the integration of AI into law enforcement must be guided by clear policies, oversight, and accountability. The goal is not to deploy AI indiscriminately, but rather to ensure its use enhances safety without compromising civil liberties or public trust.

This requires proactive collaboration between technologists, law enforcement agencies, policymakers, and the communities they serve. Standards must be developed for data privacy, algorithmic transparency, and bias mitigation. AI-enabled systems should undergo rigorous testing and independent review before deployment. Further, officers must be trained not only on how to use these tools, but also on the limitations and ethical implications of using these tools as well.

Finally, public trust is essential. Members of the community need to know that AI is being used to protect their safety and that of law enforcement — it is not a tool to surveil them without cause. Communicating transparently how the AI systems are designed, what data they use, and how decisions are made will be key to maintaining legitimacy and trust with the public.

A future of safer streets and stronger trust

The integration of AI into law enforcement is not about replacing human judgment — rather, it’s about augmenting officers’ judgment. When used responsibly, AI can reduce risk, improve preparedness, and support officers in carrying out their duties more safely and effectively.

In the years ahead, we can expect to see broader adoption of drone first responders, real-time language translation tools, and predictive systems that further help enhance officer and community safety measures. However, technology alone is not the answer. Success will depend on how thoughtfully these tools are implemented, how well citizens’ rights are safeguarded, and how deeply communities are involved in the process.

This week, as we honor those officers who have fallen in the line of duty, let us also commit to doing everything we can to protect those who serve today. AI, when applied with care, can be a powerful ally in their mission, keeping officers safe, allowing them to make better decisions, and together, building stronger, safer communities for all.

The data provided to you may not be used as a factor in establishing a consumer’s eligibility for credit, insurance, employment, or for any other purpose authorized under the Fair Credit Reporting Act.

You can find more on the challenges facing law enforcement here

Key insights:

• • • AI as a design decision, not just a tech add-on — AI gives us a chance to rethink the “machinery of justice” and redesign it for today’s needs rather than simply automating existing systems and processes.

    • AI to expand access and usability, without replacing judgment — The most promising value is in reducing friction for litigants and helping people navigate the process.

    • Progress requires disciplined, court-by-court experimentation — We can start small, build AI literacy, set leadership tone, invite diverse perspectives, and address legal and ethical issues as design constraints, not deal-breakers.

Today, interest in AI across the judiciary is clearly growing, but most discussions are still constrained by certain fears:

• • • Fear that AI will replace human judgment — This concern is legitimate, but it focuses almost entirely on endpoints. Judging (and the systems around it) involve far more than final decisions. Focusing only on high-stakes endpoints misses much of what judges and courts do day-to-day.
    • Fear of hallucinations, errors, and bias — These are also legitimate fears, but there are ways to mitigate these risks, which are not new. The source may be different, but we have long needed to protect against errors, bias, and misstated law.
    • Fear of change — This is a difficult one to overcome, but a desire to protect the status quo sometimes presupposes that the system as it exists today is working exactly as it should. It isn’t. At least not for everyone.

I’d like to see the narrative shift from fear of AI in courts, to the possibilities of AI in courts. AI presents a rare opportunity to upgrade the machinery of justice.

Justice as machinery

Most of us were taught to think about justice as an outcome, something the system delivers. However, justice is also the machinery we use to deliver it, and that machinery is a set of design choices. Rules, procedures, forms, hearings, briefs — we crafted these frameworks to manage conflict and produce decisions that feel fair and legitimate. Like most frameworks, they reflect the era in which they were built.

Once we start thinking about justice as something to be designed rather than simply delivered, the access-to-justice problem looks different. The question is no longer how to get more of the current system to more people; rather, it’s whether the machinery itself is still fit for its purpose.

Reimagining the machinery

The machinery has been redesigned before. Justice was once deeply human because it had to be: Law lived in minds, judges traveled from town to town, decisions were announced aloud. That system was more human and personal, but it was limited, exclusionary, and fickle. It was dependent on local norms and personal relationships. It yielded uneven outcomes.

The first great upgrade was writing, and more importantly, the printing press. It brought stability and protected litigants from arbitrary local power. But it also entrenched a new kind of authority. Yet, understanding it required literacy, training, and expertise. A professional bar emerged and ordinary people were pushed further from the center of their own disputes. Then came the digital age. It optimized the process and made more information available. But many people feel overwhelmed by the deluge of information and experience modern justice as a series of obstacles.

Does AI present a different kind of opportunity? Could it deliver an upgrade that finally closes the gap rather than widens it? I’m optimistic that the answer is yes, but our design choices matter and we have to be willing to reimagine justice from the ground up.

What if every litigant had access to an AI agent that could help them navigate forms, understand the process, and translate legalese? What if AI could take messy human stories and translate them into structured information for the court? What if courts offered AI-assisted dispute resolution in the early stages of litigation or at key milestones during the litigation? Can AI make navigating the legal system feel less like data entry and more like a conversation?

We’re not ready for giant leaps, and we can’t ignore the open questions: Unauthorized practice of law issues, privilege and work product implications, the reliability of AI-assisted work product, and more — but these are not dead ends. They’re current design constraints to account for, and they shouldn’t keep us from reimagining what’s possible.

Where do we start?

The institution of justice will not be redesigned overnight, and there is no central authority to drive change. Rather, it will be redesigned court by court. The principles below apply broadly and reflect a starting point for thinking about AI as a design decision, not just a technology decision.

Set the tone from the topĚý

Fear can be paralyzing, and in courts it often is. If judges and court staff are afraid to experiment, nothing moves. We need environments in which thoughtful, controlled experimentation is encouraged and supported. When more people are engaged in testing ideas and thinking about how to improve their processes, the likelihood of meaningful innovation and redesign increases.

Court leadership can create that space by setting a vision, encouraging responsible experimentation, and supporting innovative mindsets.

Build AI literacy

Encouraging experimentation is an important first step, but it can create risk if not paired with the right training and education. AI requires new competencies in prompting, guardrail development, output verification, bias awareness, iteration, context framing, documentation for audibility, fit-for-purpose judgment, and more. As tools evolve, education should evolve, too. Agentic AI, for example, will require a different set of skills and a different type of supervision than we’re accustomed to now.

For more information about toolkits and resources around AI in courts, visit

Judges and court staff do not need to become technologists, but they need enough training and education to ask the right questions, spot the right issues, and use the tools responsibly.

Rethink the systems, not just the tools

This one is critical. Currently, most conversations about AI focus on use cases, such as whether AI can assist with research or automate certain workflows. These are good questions, but the tougher questions will lead to bigger rewards. Where are our pain points? What can we do better? Which policies and processes are essential, and which have never been re-examined? Which parts of the machinery were built for a different era and have outlived their usefulness? And perhaps most importantly, who is the system failing?

We shouldn’t start with the technology and look for places to apply it. We should start with the people we serve and ask how the technology can help us serve them better.

Invite diverse perspectives

The strongest ideas emerge from the push and pull of different viewpoints. Court leadership can form committees that bring together innovators and skeptics, technologists and traditionalists, those who are excited and those who are concerned. We also need perspectives across different court functions. AI is not something to hand off to IT departments. They are essential partners, but the questions AI raises go far beyond any one department.

Outside perspectives are helpful, too. Many people across the country are already approaching this work with a multidisciplinary lens, and courts can draw on that experience.

Finally, remember to start small

It’s easy to create so much process and deliberation that progress slows. We need concrete steps that move us forward, however incrementally. Start with policies and data governance, then move to small, targeted pilots that can address low-hanging fruit. Small adjustments can help teams become comfortable with change; and early wins build confidence and create momentum.

Closing thoughts

Justice has been redesigned before, and it is on the brink of being redesigned again. AI will reshape courts whether or not we participate. However, as the people who know the system from the inside and want it to work for everyone, we may be in the best position to guide the next upgrade. The chance to build something more equitable, more accessible, and better designed for today’s world does not come around often, let’s not miss it.

You can find more insights from Judge Braswell here

Key insights:

• • • AI augments judicial judgment without replacing it — Used thoughtfully it clarifies reasoning and improves access.

    • Strict guardrails are needed — These can include structured prompts, anonymized data, and rule-based outputs helps interrupt bias and maintain integrity.

    • Judges should lead — They can do this through peer learning and education, which fosters responsible use while preserving public trust.

The integration of AI in the judiciary is gaining momentum, offering a promising solution to the growing caseloads, access-to-justice gaps, and public trust challenges faced by courts across the United States. And as the judiciary explores the potential of AI, a crucial conversation is emerging — one that highlights the importance of responsible and thoughtful adoption.

A recent webinar, , presented by theĚý — a joint effort by the National Center for State CourtsĚý(NCSC) and the Thomson Reuters Institute (TRI) — shed light on the experiences of early adopters of generative AI (GenAI) in the judiciary. In the webinar, Prof. Amy Cyphert of West Virginia University and U.S. Magistrate Judge Maritza Dominguez Braswell of the District of Colorado shared their insights from their own use of AI, emphasizing the need for a deliberate and informed approach.

The role of AI in judicial decision-making

A common fear is that AI will somehow take over the position of final arbiter in court proceedings. However, judges are not interested in having AI displace their judgment; rather, they see AI as a tool that augments and helps advance justice, not a tool that replaces decision-making or human judgment.

Judges also are not rushing into AI use. Instead, they are approaching it with a deep commitment to responsible use and a desire to increase, not decrease, public trust. “Everybody on that spectrum — from ‘I’m just learning’ to ‘I want to be a power user’ — says, ‘But I want to do it right,’” says Judge Braswell.

AI can also help judges close communication gaps. By taking decisions that judges have already reasoned through and converting them into accessible explanations, AI can help all litigants clearly understand the relevant legal framework, rule, or process behind the decision. This is even more impactful in cases involving self-represented litigants.

Leveraging AI to enhance judicial communication

Judge Braswell understands this well. In every case with at least one self-represented litigant, she offers a plain language summary of her written decisions. Although she does not use AI to draft those, she does use AI to translate complex legal reasoning when delivering information from the bench.

“If I have 15 minutes for a hearing and want to explain to a self-represented litigant something complex, I use AI to help me translate legal jargon into plain and simple language,” she explains. “I want the self-represented litigant to understand what I’m doing and why I’m doing it — and AI helps me translate lawyer-speak into plain-speak, quickly.”

You can explore the white paperĚý here

This capability is particularly valuable for judges who often struggle to find the time to connect with litigants. By leveraging AI, they can provide more personalized and informative interactions, ultimately enhancing litigants’ judicial experiences. In addition, some judges are using AI to create engaging content, such as avatars and videos on YouTube, to make themselves more relatable and accessible to the public; while others are using AI to help litigants navigate court processes, helping to demystify the system and reduce anxiety.

Guardrails for responsible AI use

Of course, Judge Braswell doesn’t use AI casually. She has strict policies and protocols in place, including segregation of work and personal accounts, prompt anonymization, and prohibiting her clerks from uploading sensitive information or delegating core functions and judgment to any AI tool. She also trains her chambers on high-risk and low-risk cases and emphasizes the importance of proper AI use through structured prompts, appropriate settings, standing instructions, and deliberate guardrails.

For example, Judge Braswell describes a dedicated project in which she uploaded her district’s local rules, the Federal Rules of Civil Procedure, and standing orders. She queries that project any time she needs to refresh on an applicable rule or procedure. She gave the AI tool clear instructions, such as: Don’t answer unless grounded in a rule. Cite the rule with every response. If you don’t know, say so.

While these types of practices do not make the tools risk-free, Judge Braswell notes, they do offer guardrails to help support, rather than undermine, judicial integrity.

Addressing risks and challenges

While , the deeper risks in AI use in the courts are bias, cognitive deskilling, and erosion of public trust. Judge Braswell warns that bias is harder to detect than any made-up case citation. “If you ask for a legal framework in an employment discrimination case, the system may pull more from defense-side articles because larger firms publish more content,” she explains. “The result is a subtle tilt in perspective.”

To counter this, she prompts her AI tools deliberately asking for diverse perspectives, asking the tool to gather contrary views, or telling the tool to answer only after asking follow-up questions that could identify user bias. Without this intentionality, bias can go undetected.

For judges ready to engage, visitĚýĚýto join the conversation

On the webinar, Prof. Cyphert echoed concerns about the next generation. “I worry that younger lawyers may skip critical learning processes if they rely too heavily on AI for drafting or research,” Prof. Cyphert says. “Is there a cognitive benefit to writing that we’re losing?”

The path forward through education, experimentation & transparency

During the webinar, both speakers rejected mandatory disclosure rules as counterproductive.

“It creates a chilling effect,” Judge Braswell says. “And we need people to engage for learning purposes.” Instead, she notes that she advocates for voluntary transparency — judges explaining their use of AI in ways that build public understanding and confidence.

Prof. Cyphert agrees. “You can’t assess risks and benefits if you don’t understand the technology,” she says, adding that she encourages judges to attend webinars, read research, and talk to peers. Similarly, Judge Braswell co-founded the , a judge-only, peer-led forum for candid discussion that exists as a safe space to share challenges, test ideas, and learn together.

As the webinar notes, the future of justice isn’t just about whether courts and judges are using advanced AI technology, it’s about how that technology should be used — with care, purpose, and always with people at the center.

For more on the impact of AI in courts, visit theĚý

Key insights:

• • • Well-being is a professional necessity — Judges experience decision fatigue, emotional stress, and personal biases that can affect their rulings, making mental and physical well-being a judicial duty.

    • Community engagement builds better judgment — Staying connected to the communities they serve helps judges develop empathy, recognize bias, and deliver fairer decisions.

    • Diverse experience strengthens the judiciary — Varied backgrounds and ongoing education in areas like restorative justice make courts more responsive, inclusive, and publicly trusted.

Judges play a unique and essential role in society. They are tasked with interpreting the law, resolving disputes, and upholding justice — often under intense scrutiny and pressure. Their decisions shape lives, influence public policy, and reinforce the rule of law.

Indeed, judicial rulings may be the most visible part of the job, but they are not the only measure of a judge’s effectiveness — or of the judiciary’s overall health.

To truly understand and support a robust legal system, it is vital to look beyond the courtroom and examine the broader context in which judges operate. A judiciary that is fair, empathetic, and resilient depends not only on legal expertise, but also on balance, self-awareness, and active engagement with the communities it serves.

The weight of the robe & the value of connection

Despite the solemnity of the judicial office, judges also carry personal experiences, cognitive biases, and emotional responses. The weight of responsibility in adjudicating complex, often emotionally charged cases can lead to stress, burnout, and decision fatigue. that judicial decisions can be influenced by factors such as time of day, caseload volume, and even personal well-being.

When judges prioritize their own well-being through physical health, mental resilience, and time away from the bench, they are better equipped to render fair and consistent decisions. Judicial wellness is not a personal luxury; rather, it is a professional imperative.

Equally important is the role of community engagement. The law does not exist in a vacuum but is shaped by social norms, economic realities, and cultural shifts. Judges who remain isolated from the communities that are affected by their rulings risk losing touch with the lived experiences of the people before them.

Judicial rulings may be the most visible part of the job, but they are not the only measure of a judge’s effectiveness — or of the judiciary’s overall health.

Engagement with the public helps judges better understand how the law impacts and operates in people’s lives. It also builds the empathy and contextual awareness needed for interpreting statutes or imposing sentences.

For example, a judge who volunteers with youth programs or participates in community forums on public safety may develop a more nuanced understanding of cases involving juvenile offenders or policing practices. Similarly, a judge who attends local cultural events or listens to community leaders may be better positioned to recognize implicit biases or systemic inequities that may be inherent in the justice system.

Community involvement also strengthens public trust. When citizens see judges as accessible and engaged, rather than distant or aloof, confidence in the judiciary increases. And these ideas of transparency and connection are key to maintaining citizens’ trust in the courts.

These themes are explored more in depth in the Thomson Reuters Institute’s video series,ĚýBeyond the Bench. For example, in the episodeĚý,ĚýAssociate Justice Tanya R. Kennedy shares her experience educating youth, participating in civic organizations, and leading legal reform initiatives. The episode also highlights how service beyond judicial duties enhances judges’ decision-making and strengthens community ties.

Another episode of the series,Ěý,Ěýexamines the personal and professional challenges faced by judges and attorneys alike. It features a candid interview with Judge Mark Pfiffer, who emphasizes the importance of mindfulness, peer support, and institutional policies that promote mental health and sustainable work practices.

A judiciary that reflects society

The same principle applies at the institutional level. A judiciary is strongest when it reflects the range of experiences and perspectives present in the society it serves.

Beyond individual judges, the judiciary can benefit from diversity and inclusion. A bench that reflects the full spectrum of society is more likely to deliver balanced and equitable justice. But diversity is not just about representation — it’s also about perspective.

Judges who have worked in public defense, civil rights advocacy, or rural legal services bring different insights to the bench than those who have spent their careers in corporate law or prosecution. These varied experiences enrich judicial deliberation and help ensure that decisions are informed by a broad understanding of justice.

Encouraging judges and court personnel to engage in lifelong learning, mentorship, and cross-sector collaboration further strengthens the judiciary. Programs that support judicial education on topics like implicit bias, trauma-informed practices, or restorative justice are essential to modern, responsive courts.

Improving judges’ well-being

The quality of justice depends not only on what happens in the courtroom, of course, but on what happens outside of it. Judges who maintain personal balance, engage with their communities, and remain open to diverse perspectives are better equipped to serve the public good.

Legal professionals, court administrators, and policymakers should support the kinds of initiatives that promote judicial wellness, community outreach, and professional development. By fostering a judiciary that looks beyond the bench, we ensure a justice system that is not only legally sound, but also humane, inclusive, and trusted.

In the end, judges and the justice they mete out are not defined by court rulings alone. It also depends on relationships, context, and public trust. Recognizing that reality is essential to preserving the well-being of the judiciary and the integrity of the law.

TheĚý“Beyond the Bench”Ěývideo series is available on

Key takeaways:

• • • AI frameworks need to keep up with implementation — While AI governance frameworks are being developed and enacted globally, their effectiveness depends on enforceable mechanisms within domestic justice systems.

    • Access to justice is essential for trustworthy AI regulation — Rights and protections are only meaningful if individuals can understand, challenge, and seek remedies for AI-driven decisions. Without operational access, governance frameworks risk remaining theoretical.

    • People-centered justice and human rights must anchor AI governance — Embedding human rights standards and ensuring equal access to justice in AI regulation strengthens public trust, accountability, and the credibility of both public institutions and private companies.

AI governance is accelerating across global, national, and local levels. As public investment in AI infrastructure expands, new oversight bodies are emerging to assess safety, risk, and accountability. The global policy conversation has from principles to the implementation of meaningful guardrails and AI governance frameworks, which legislators now are drafting and enacting.

These developments reflect growing recognition that AI systems demand structured oversight and a shift from voluntary safeguards and standards to institutionalized governance. One critical dimension remains underdeveloped, however: how do these frameworks function in practice? Are they enforceable? Do they provide accountability? Do they ensure equal access?

AI governance will not succeed on the strength of international declarations or regulatory design alone; rather, domestic justice systems will determine whether it works. At this intersection, the connection between AI governance and access to justice becomes real.

In early February, leaders across government, the legal sector, international organizations, industry, and civil society convened for an expert discussion. The following reflections attempt to build on that dialogue and its urgency.

From principles to enforcement

Over the past decade, AI governance has evolved from hypothetical ethical guidelines to voluntary commitments, binding regulatory frameworks, and risk-based approaches. Due to these game-changing advancements, however, many past attempts to provide structure and governance have been quickly outpaced by technology and are insufficient without enforcement mechanisms. As Anoush Rima Tatevossian of The Future Society observed: “The judicial community should have a role to play not only in shaping policies, but in how they are implemented.”

Frameworks establish expectations, while courts and dispute resolution mechanisms interpret rules, test rights, evaluate harm, assign responsibility, and determine remedies. If individuals are not empowered to safeguard their rights and cannot access these mechanisms, governance frameworks remain theoretical or are casually ignored.

This challenge reflects a broader structural constraint. Even without AI, legal systems struggle to meet demand. In the United States alone, 92% of people do not receive the help they need in accessing their rights in the justice system. Introducing AI into this environment without strengthening access can risk widening, rather than narrowing, the justice gap.

There’s growing recognition that AI systems demand structured oversight and a shift from voluntary safeguards and standards to institutionalized governance.

Justice systems serve as the operational core of AI governance. By inserting the rule of law into unregulated areas, they provide the infrastructure that enables accountability by interpreting regulatory provisions in specific cases, assessing whether AI-related harms violate legal standards, allocating responsibility across public and private actors, and providing accessible pathways for redress.

These frameworks also generate critical feedback. Disputes involving AI systems expose gaps in transparency, fairness, and accountability. Legal professionals see where governance frameworks first break down in real-world conditions, often long before policymakers do. As a result, these frameworks function as an early signal of policy effectiveness and rights protections.

Importantly, AI governance does not require entirely new legal foundations. Human rights frameworks already provide standards for legality, non-discrimination, due process, and access to remedy, and these standards apply directly to AI-enabled decision-making. “AI can assist judges but must never replace human judgment, accountability, or due process,” said Kate Fox Principi, Lead on the Administration of Justice at the United Nations (UN) Office of the High Commissioner for Human Rights (OHCHR), during the February panel.

Clearly, rights are only meaningful when individuals can exercise them — this constraint is not conceptual, it’s operational. Systems must be understandable, affordable, and responsive, and institutions should be capable of evaluating complex, technology-enabled disputes.

Trust, markets & accountability

Governance frameworks that do not account for these dynamics risk entrenching inequities rather than mitigating them. An individual’s ability to understand, challenge, and seek a remedy for automated decisions determines whether governance is credible. A people-centered justice approach, as established in the , asks whether individuals can meaningfully engage with the system, not just whether rules exist. For example, women face documented barriers to accessing justice in any jurisdiction. AI systems trained on biased data can replicate or amplify existing disparities in employment, financial services, healthcare, and criminal justice.

“Institutional agreement rings hollow when billions of people experience governance as remote, technocratic, and unresponsive to their actual lives,” said Alfredo Pizarro of the Permanent Mission of Costa Rica to the UN. “People-centered justice becomes essential.”

AI systems already shape outcomes across employment, financial services, housing, and justice. Entrepreneurs, law schools, courts, and legal services organizations are already building AI-enabled tools that help people navigate legal processes and assert their rights more effectively. Governance design will determine whether these tools help spread access to justice and or introduce new barriers.

Private companies play a central role in developing and deploying AI systems. Their products shape economic and social outcomes at scale. For them, trust is not abstract; it is a success metric. “Innovation depends on trust,” explained Iain Levine, formerly of Meta’s Human Rights Policy Team. “Without trust, products will not be adopted.” And trust, in turn, depends on enforceability and equal access to remedy.

AI governance will succeed or fail based on access

As Pizarro also noted, justice provides “normative continuity across technological rupture.” Indeed, these principles already exist within international human rights law and people-centered justice; although they precede the advent of autonomous systems, they provide standards for evaluating discrimination, surveillance, and procedural fairness, and remain durable as new challenges to upholding justice and the rule of law emerge.

People-centered justice was not designed for legal systems addressing AI-related harms, but its outcome-driven orientation remains durable as new justice problems emerge.

The current stage presents an opportunity to align AI governance with access to justice from the outset. Beyond well-drafted rules, we need systems that people can use. And that means that any effective governance requires coordination between policymakers, legal professionals, and the public.

You can find other installments ofĚýour Scaling Justice blog seriesĚýhere

Key insights:

• • • AI’s greatest strength in criminal justice is pattern recognition— AI can process vast amounts of data quickly, helping law enforcement and legal professionals detect connections, reduce oversight gaps, and improve consistency across investigations and casework.

    • AI should strengthen justice, not substitute for human judgment— Legal professionals are integral to evaluating AI-generated outputs, especially when decisions affect evidence, warrants, and individuals’ constitutional rights.

    • The most effective model is human/AI collaboration— AI handles scale and speed, while judges, attorneys, and investigators provide context, accountability, and ethical reasoning needed to protect due process.

The law has always been about patterns — patterns of behavior, patterns of evidence, and patterns of justice. Now, courts and law enforcement can leverage a tool powerful enough to see those patterns at a scale at a speed no human mind could match: AI.

At its core, AI works by recognizing patterns. Rather than simply matching keywords, it learns from large amounts of existing text to understand meaning and context and uses that learning to make predictions about what comes next. In the context of law enforcement, that capability is nothing short of transformative.

These themes were front and center in a recent webinar, , from theĚý, a joint effort by the National Center for State CourtsĚý(NCSC) and the Thomson Reuters Institute (TRI). The webinar brought together voices from across the justice system, and what emerged was a clear and consistent message: AI is a powerful ally in the pursuit of justice, but only when paired with the judgment, accountability, and constitutional grounding that human professionals can provide.

AI’s pattern recognition is a gamechanger

“AI is excellent,” said Mark Cheatham, Chief of Police in Acworth, Georgia, during the webinar. “It is better than anyone else in your office at recognizing patterns. No doubt about it. It is the smartest, most capable employee that you have.”

That kind of capability, applied to the demands of modern policing, investigation, and prosecution, is a genuine gamechanger. However, the promise of AI extends far beyond the patrol car or the precinct. Indeed, it cascades through the entire arc of justice — from the moment a crime is detected all the way through prosecution and adjudication.

Each step in that chain represents not just an operational and efficiency upgrade, but an opportunity to make the system more fair, more consistent, and more protective of the rights of everyone involved.

Webinar participants considered the practical implications. For example, AI can identify and mitigate human error in decision-making, promoting greater consistency and fairness in outcomes across cases. And by automating labor-intensive tasks such as reviewing body camera footage, AI frees prosecutors and defense attorneys to focus on other aspects of their work that demand professional judgment and legal expertise.

In legal education, the potential of AI is similarly recognized. Hon. Eric DuBois of the 9th Judicial Circuit Court in Florida emphasizes its role as a tool rather than a substitute. “I encourage the law students to use AI as a starting point,” Judge DuBois explained. “But it’s not going to replace us. You’ve got to put the work in, you’ve got to put the effort in.”

AI can never replace the detective, the prosecutor, the judge, or the defense attorney; however, it can work alongside them, handling the volume and velocity of data that no human team could process alone.

Judge DuBois’ perspective aligns with broader judicial sentiment on the responsible integration of AI. In fact, one consistent theme across the webinar was the necessity of maintaining human oversight. The role of the legal professional remains central, participants stressed, because that ensures accuracy, accountability, and ethical judgment. The appropriate placement of human expertise within AI-assisted processes is essential to ensuring a fair and effective legal system.

That balance between leveraging AI and preserving human judgment is not just good practice, rather it’s a cornerstone of justice. While Chief Cheatham praises AI’s pattern recognition, he also cautions that it “will call in sick, frequently and unexpectedly.” In other words, AI is a powerful but imperfect tool, and those professionals who rely on it must always be prepared to intervene in those situations in which AI falls short. Moreover, the technology is improving extremely rapidly, and the models we are using today will likely be the worst models we ever use.

Naturally, that readiness is especially critical when individuals’ rights are on the line. “A human cannot just rely on that machine,” said Joyce King, Deputy State’s Attorney for Frederick County in Maryland. “You need a warrant to open that cyber tip separately, to get human eyes on that for confirmation, that we cannot rely on the machine.” Clearly, as the webinar explained, AI does not replace constitutional obligations; rather, it operates within them, and the professionals who use AI are still the guardians of due process.

The human/AI partnership is where justice is served

Bob Rhodes, Chief Technology Officer for ¶¶ŇőłÉÄę Special Services (TRSS) echoed that sentiment with a principle that cuts across every application of AI in the justice system. “The number one thing… is a human should always be in the loop to verify what the systems are giving them,” Rhodes said.

This is not a limitation of AI; instead, it’s the design of a system that works. AI identifies the patterns, and trained, experienced professionals evaluate them, act on them, and are accountable for them.

That partnership is where the real opportunity lives. AI can never replace the detective, the prosecutor, the judge, or the defense attorney. However, it can work alongside them, handling the volume and velocity of data that no human team could process alone. So that means the humans in the room can focus on what they do best: applying judgment, upholding the law, and protecting an individual’s rights.

For judicial and law enforcement professionals, this is the moment to lean in. The patterns are there, the technology to read them is here, and the opportunity to use both in service of rights — not against them — has never been greater.

You can find out more about the webinars from the AI Policy Consortium here

Key takeaways:

• • • Violence against judges is escalating — Targeted shootings, coordinated harassment campaigns, and threats that now routinely follow judges to their homes and families.

    • The rhetoric driving the escalation is coming from the highest levels of government — The absence of any public denunciation from the Department of Justice is highlighting the source of the problem.

    • Will the violence itself become part of judicial rulings? — The endgame of judicial intimidation isn’t that judges stop ruling, it’s that the threat of violence becomes a silent presence in the deliberation itself.

NEW YORK — Those attendees who came to the recentĚý to talk about AI, agentic workflows, and the business of legal technology, also were treated to a session that will likely stay with attendees and had nothing to do with AI.

In that session, four federal judges took the stage; but they were not there to talk about pricing models or AI adoption. They were there to talk about staying alive.

Setting the stage

Jason Wareham, CEO of IPSA Intelligent Systems and a former U.S. Marine Corps judge advocate, introduced the session — a panel of four sitting United States District Court judges — by speaking of how the rule of law once seemed resolute, yet how that faith in that has been shaken, year after year. He worked hard to frame his observations as nonpartisan, a matter of institutional fragility rather than political allegiance. It was a generous framing, but it was one that would not survive the weight of the ensuing discussion.

The Honorable Esther Salas of the District of New Jersey said that the reason she was there has a name. On July 19, 2020, a disgruntled, extremist attorney who had a case before her court arrived at her home during a birthday celebration. He shot and killed her twenty-year-old son, Daniel Anderl. He shot and critically wounded her husband. She has spent the years since on a mission to protect her judicial colleagues from the same fate.

The new normal

Next, the Honorable Kenly Kiya Kato of the Central District of California described what has changed. Judges’ rulings are still based on the Constitution, on precedent, and on the facts; but what’s different is the small voice in the back of a judge’s head. That voice, often coming after a judge issued a decision that they now have to fight against, asks: What will happen after this? It is now expected, Judge Kato explained, that a high-profile order will bring threats. When two colleagues in her district issued prominent decisions, her first thought was for their safety. That is not how it has been historically.

The Honorable Mia Roberts Perez of the Eastern District of Pennsylvania asked how we got here, pointing to language from the highest levels of government: judges called monsters, a U.S. Department of Justice declaring war on rogue judges, and recently politicians bringing justice’s families into the conversation.

Judge Salas pushed even further. She acknowledged the instinct to frame the problem as bipartisan, but said the current moment is not apples to apples. It is apples to watermelons. The spike in threats since 2015, she argued, traces directly to rhetoric from political leaders using language never before deployed against the bench.

The federal judiciary is looking to break annual records for threats [against judges], and there is an absence of any public denunciation from the Attorney General or the DOJ.

The evidence is not abstract, nor are the victims, and the panel walked through it. Judge John Roemer of Wisconsin, zip-tied to a chair and assassinated in his home. Associate Judge Andrew Wilkinson of Maryland shot dead in his driveway while his family was inside. Judge Steven Meyer of Indiana and his wife Kimberly, shot through their own front door after attackers first posed as a food delivery, then returned days later claiming to have found the couple’s dog. Judge Meyer has just undergone his fifth surgery since the attack.

All of these incidents happened at the judges’ homes.

Judge Salas then played a voicemail, one of thousands that federal judges receive. It was less than 30 seconds long, but it did not need to be longer. While names had been redacted, what remained was a torrent of threats and obscenities, graphic, sexual and violent, delivered with the confidence of someone who does not expect consequences. Some judges receive hundreds of these after a single ruling, often from people with no case before them at all.

The shadow over the courts

Throughout the session, there was a presence the panelists circled but rarely named directly. A shadow that shaped every observation about escalating threats, every reference to rhetoric from the top down, every mention of language never before used by political leaders, of action or inaction the likes of which would have been unthinkable just several years ago. The specifics were spoken. The name, largely, was not.

It didn’t have to be.

Judge Kato said that what was perhaps the most disheartening aspect of all this is that these threats are getting worse. The people who know better are not doing better. Indeed, she said her children think about these problems every day. What will happen to mom today? Will someone come to the house? These are questions children should not have to carry. They did not sign up for this, and neither did the judges.

In 2026, Judge Salas noted, the federal judiciary is looking to break annual records for threats. She also noted the absence of any public denunciation from the Attorney General or the DOJ. The silence, she said, says a lot.

Not surprisingly, the implications extend beyond the judges themselves. As Judge Salas noted, if judges have to weigh their safety alongside the law, ordinary people don’t stand a chance. If one party is stronger, better funded, or more willing to threaten, then the scales tip.

That is the endgame of judicial intimidation. It’s not that judges stop ruling, but that the violent and the powerful — indeed, the people least fit to hold the scales — can tilt them at will.

That concern echoed an earlier warning from Judge Karoline Mehalchick of the Middle District of Pennsylvania. Judge Mehalchick said that judicial intimidation feeds on misunderstanding. When the public no longer grasps why judges must be insulated from pressure or conversely, mistakes independence for partisanship, the threat environment becomes easier to justify, easier to ignore, and harder to reverse.

What is perhaps the most disheartening aspect of all this is that these threats are getting worse, and the people who know better are not doing better.

In his 2024 year-end report, U.S. Supreme Court Chief Justice John Roberts identified four threats to judicial independence: violence, intimidation, disinformation, and threats to defy lawfully entered judgements. The panel discussed this report as prophecy fulfilled. Public confidence in the judiciary has plummeted since 2021, and the reasons are complex. The judges insisted they are still doing their jobs the right way, but the violence is spreading anyway.

What survives

Judge Salas asked the audience to watch their thoughts. Are they negative and destructive, or positive and uplifting? Can we start loving more? She ended by sending love and light to everyone in the room.

The judges were visibly emotional on the stage.

The words were beautiful. They were also, in the context of everything that had just been described — the killings, the voicemails, the zip ties, the pizza deliveries masking a threat under a murdered son’s name — resting in a shadow that no amount of love and light could fully dispel on their own.

The room responded with a standing ovation.

Thousands of people came to Legalweek 2026 to talk about the future of legal technology. For one morning, four judges reminded them that none of it matters if the people charged with administering justice cannot do so safely.

So, while the billable hour may survive and the associate will adapt, the harder question, the one that should keep the legal industry awake at night, is whether the bench will hold.

You can find more ofĚýour coverage of Legalweek eventsĚýhere