It may be almost impossible to devolve this country into a nation of slaveholders, but the Trump administration and all of its MAGA buddies are working hard to make sure a white person’s vote counts more than a vote cast by anyone else.

These bigots recently got an assist from the Supreme Court, which decided minorities can have their votes rendered meaningless so long as the people doing the gerrymandering don’t actually say the quiet part loud. Redistricting for the sole purpose of excluding as many non-whites as possible is perfectly legal if politicians never affirmatively state that the only reason they’re doing this is to make sure minorities can’t vote against their racist asses.

This is all part of what the state of South Dakota is doing now. Governor Larry Rhoden was never elected to his post. He was elevated after Kristi Noem was selected to head the DHS by Donald Trump. (Since she’s about as unemployed as any Trump appointee ever gets, I’m sure she wishes she was back running the state of South Dakota… into the ground.) His most recent brush with the electoral process saw him losing handily to Mike Rounds in the 2014 Senate race.

Rhoden actually needs to win an election if he wishes to remain South Dakota’s governor. And all the MAGA fellatio in the world doesn’t mean much when plenty of other MAGA acolytes are running against him.

So, there’s a mixture of things going on here. There’s Rhoden’s (and the state GOP’s) desire to engage with Trump’s election conspiracies — ones that claim (with zero facts in evidence) that a whole lot of undocumented immigrants are voting in state and local elections.

There’s also a nationwide attempt to deter voting by mail, because these votes more often side with the other team.

In response to completely made-up problems, the GOP passed a bill that Rhoden signed that says state residents must prove their citizenship to engage in local elections. If they can’t, they’re only allowed to participate in federal elections.

According to Rhoden and other GOP alarmists, that’s because too many people who aren’t citizens were granted permission to vote, thanks to what was likely nothing more than a clerical error. South Dakota may be small state in terms of population (~950,000 residents as of 2025), but the “problem” this vaguely written law supposedly addressed was even smaller.

Soulek said only one of the 273 noncitizens had ever cast a ballot. That was during the 2016 general election.

Those are the words of the Director of Elections Rachel Soulek, who works out of the Secretary of State’s office. The Secretary of State blamed this on clerical errors by the Department of Public Safety. The DPS provided the data that Governor Rhoden claims to evidence of widespread election fraud by non-citizens.

One illegal ballot. And that was likely an honest misunderstanding, rather than the criminal intent Rhoden and GOP buddies want to pretend it is.

But the law is on the books. Citizenship must be demonstrated to participate in state and local elections. The problem is that no one running these elections seems to agree what is or isn’t acceptable proof of citizenship.

Hughes County Finance Officer Thomas Oliva, who acts as that county’s auditor, said his office is requiring new voters to show the physical driver’s license.

“The main reasoning behind that is because it’s the back of the license. There’s no other identifying information on the back we can tie back to that person, so we felt it’s in the best interest to see the physical card,” Oliva told News Watch.

Haakon County Auditor Stacy Pinney said she has not run into any issues yet with voter registration but also will require new applicants to physically show the driver’s license.

“I’m going to make it a policy in my office that I want to see the actual card. If I have to verify it, I want to see the real deal,” Pinney told News Watch.

Meanwhile, Harding County Auditor Kathy Glines said her office will accept a photocopy of the driver’s license.

“They would have to send a front and back,” Glines told News Watch.

“I hope they would call before sending it by mail,” she added, referring to the limited hours the office is open.

Everyone appears to be making up their own rules because the law — and the Secretary of State’s office — are being deliberately vague about these requirements, especially in relation to absentee voting. And many people in the state may not know that the law only applies to people who have registered to vote after July of last year, so lots of people are going to be presenting IDs to precinct staffers even if they’re not legally required to do so.

This all adds up to exactly what Governor Rhoden and the GOP want: confusion over who is or isn’t allowed to vote, blended with another law passed by Rhoden that allows pretty much anyone to challenge someone else’s eligibility to vote.

The state could offer much-needed clarification. But it won’t.

As early and absentee voting for the primary election gets underway, Scott-Stoltz hopes officials in Pierre can provide more certainty on the registration process for new voters.

“We’re hoping for more clarification from the secretary’s office before the primary and are looking forward to working with the election board,” she said.

The secretary of state’s office didn’t respond to a request for comment by News Watch.

That’s a feature, not a bug. Those in power definitely prefer incumbent voters over new ones, much like incumbent voters prefer incumbents. They want to keep the jobs they have, rather than allow new voters to upset the incumbent apple cart. They all pretend they love the democratic system, but when it’s time latch onto another 2-4 years in power, they work together to reduce the electorate to the votes they can count on.

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California recently passed a law that will, in practice, cause AI chatbots to respond to any hint of emotional distress by spamming users with 988 crisis line numbers, or by cutting off the conversation entirely. The law requires chatbot providers to implement “a protocol for preventing the production of suicidal ideation” if they’re going to engage in mental health conversations at all, with liability waiting for any provider whose conversation is later linked to harm. New York is considering going further, with a bill that would simply ban chatbots from engaging in discussions “suited for licensed professionals.” Similar proposals are moving in other states.

If you’ve been reading Techdirt for any length of time, you know exactly what’s happening here. It’s the same moral panic playbook we’ve seen deployed against cyberbullying, then against social media, and now against generative AI. Something terrible happens. A handful of tragic stories emerge. Lawmakers, desperate to show they’re doing something, reach for the most visible technology in the room and start passing laws designed to stop it from doing whatever it was supposedly doing. The possibility that the technology might actually be helping more people than it’s hurting, or that the proposed fix might make things worse, rarely enters the conversation.

Professor Jess Miers and her student Ray Yeh had a terrific piece at Transformer last month that actually engages with the data and the incentive structures here, and their central argument may seem counterintuitive to many: the way to make AI chatbots safer for people in mental health distress might be to reduce liability for providers. For many people, I’m sure, that will sound backwards. That is, until you actually think through how the current liability regime shapes behavior — as well as reflect on what we know about Section 230’s liability regime in a different context.

First, though, the empirical reality that rarely makes it into the moral panic coverage. People are using AI chatbots for mental health support at massive scale, and a lot of them say it’s helping:

A small number of tragic stories have spurred lawmakers into regulating how chatbots should help people who are dealing with mental health issues. Yet chatbots have emerged as first aid for people experiencing mental health issues, providing genuine benefit to those who aren’t in crisis but are not OK either. Heavy-handed legislation risks derailing this breakthrough in support, creating more problems than it solves.

Over a million people are using general-purpose chatbots for emotional and mental health support per week. In the US, those that use chatbots in this way primarily seek help with anxiety, depression, relationship problems, or for other personal advice. As conversational systems, chatbots can sustain coherent exchanges while conveying apparent empathy and emotional understanding. Many chatbots also draw on broad knowledge of psychological concepts and therapeutic approaches, offering users coping strategies, psychoeducation, and a space to process difficult experiences.

In a study of more than 1,000 users of Replika — a general-purpose chatbot with some cognitive behavioral therapy-informed features — most described the chatbot as a friend or confidant. Many reported positive life changes, and 30 people said Replika helped them avoid suicide. Similar patterns appear among younger chatbot users. In a study of 12–21-year-olds — a group for whom suicide is the second leading cause of death — 13% of respondents used chatbots for some kind of mental health advice, of which more than 92% said the advice was helpful.

There are, obviously, some limits to the Replika study, including that the data is from a few years ago, and it involves self-reporting, which can always lead to some wacky results. But it is notable that this study was done by Stanford academics (i.e., not Replika itself) and was good enough to get published in Nature. And it does seem notable that even with the methodological limitations, so many people self-reported that the service helped them avoid suicide. For all the attention-grabbing stories of chatbots being blamed for encouraging suicidal ideation, that seems important. Same with the claim of 92% that the mental health advice was helpful.

It feels like these kinds of numbers should be at the center of any serious policy conversation. Instead, they’re almost entirely absent from the legislative discussion, which focuses exclusively on the (very real, very tragic, but still somewhat rare) cases where things went wrong.

A big part of the reason chatbots are filling this gap is that the traditional mental health system isn’t remotely equipped to meet existing demand. Nearly half of Americans with a known mental health condition never seek professional help. There are plenty of reasons for this, ranging from the cost of mental health treatment, to the general stigma of being seen as needing such help, not to mention potential professional and social consequences.

As Miers and Yeh put it: “many stay silent, waiting to see if things get worse.”

Chatbots, whatever their limitations, offer something the professional system largely cannot: they’re always available in a form many people feel more comfortable talking with:

By contrast, chatbots offer low-friction, low-stakes, and always-available support. People are often more willing to speak candidly with computers, knowing that there is no human on the other side to judge or feel burdened. Some people even find chatbots to be more compassionate and understanding than human healthcare providers. AI users may feel more comfortable sharing embarrassing fears, or questions they might otherwise hold back. For clinicians, discussing these interactions can surface insights into patients’ thoughts and emotions that were once difficult to access. For now, chatbot providers generally refrain from contacting law enforcement, leading to more candid conversations.

So what does the California-style regulatory approach actually do to this ecosystem? Faced with liability for any conversation later linked to harm, and unable to reliably predict which conversations those will be (in part because, as we covered recently, even clinicians who specialize in suicide prevention admit they often can’t predict it), providers will default to the behavior that minimizes legal exposure whether or not it helps users. That means reflexively pushing 988 at any mention of distress, or cutting off conversations entirely, or simply refusing to engage with mental health topics at all.

And that kind of defensive posturing can be actively harmful to those most at risk:

Suicide prevention is about connecting people to the right support. Sometimes that means crisis care like hotlines or immediate medical treatment. But blunt, impersonal responses can backfire. Pushing 988 at the first mention of distress may seem neutral, but for some, it triggers shame, and deepens hopelessness. For some, suicide prevention “signposting” causes frustration, especially for those who already know those resources exist. People often turn to the Internet, or a chatbot, because they’re looking for something else. Abruptly ending conversations can have the same effect. That’s why suicide prevention protocols like Question, Persuade, Refer(QPR) prioritize trust-building and open dialogue before offering help.

So the regulatory regime mandates behavior that can actively escalate distress, all while still leaving providers exposed to blame if tragedy follows anyway. It’s the worst of both worlds: worse outcomes for users, continued liability for providers, and a chilling effect on the research and development that might actually improve things.

We don’t need to speculate about whether this dynamic plays out in practice. We’ve already watched it happen with social media:

The social media ecosystem has already shown this dynamic. In response to regulatory pressure, major online services heavily moderate, or outright prohibit, suicide-related discussions, sometimes hiding content that could otherwise destigmatize mental health. That merely displaces the conversations, and the people having them, often into spaces with less oversight and support.

If this sounds familiar, it’s because it is. It’s the same pattern that emerges whenever policymakers try to make sensitive topics go away through platform liability: the topics don’t go away, they just migrate to darker corners where nobody is watching at all. A mental health crisis doesn’t magically disappear just because Instagram or TikTok hid the conversation. Those in need of help are more likely to then end up somewhere with fewer guardrails, fewer resources, and fewer people equipped to help.

This leads directly back to the core of the argument, which may feel a bit backwards at first. If we want chatbot providers to build genuinely better systems for handling mental health conversations — systems that can identify distress patterns, offer appropriate triage, connect users to professional care when that’s what’s needed, and sustain helpful conversation when it isn’t — we need a liability environment that doesn’t punish the attempt.

This is, incidentally, exactly the logic that produced Section 230 in the first place. Before Section 230, the Stratton Oakmont v. Prodigy ruling created a perverse situation where platforms that tried to moderate content faced more liability than platforms that did nothing. The obvious result, had that stood, would have been less moderation, not more, because the smart legal advice would have been “don’t touch anything.” Section 230 fixed that by ensuring that the act of moderation itself didn’t create liability, which in turn made it possible for platforms to actually invest in moderation systems. Contrary to the widespread belief among the media and politicians, Section 230 didn’t eliminate accountability — it smartly redirected incentives toward the behavior we actually wanted.

The same logic applies here. A targeted liability shield for AI providers engaged in mental health support could give them the space to invest in building better suicide detection, better triage pathways, and better handoffs to human professionals. But that won’t happen if every such attempt turns into a potential lawsuit. The research to enable this is already happening despite the hostile incentive environment:

Meanwhile, emerging research suggests chatbots show real promise for mental health support. Trained on large-scale data and refined with clinical input, large language models are getting better at spotting patterns of distress and responding to suicidal ideation in nuanced, personalized ways. In a recent UCLA study, researchers found that LLMs can detect forms of emotional distress associated with suicide that existing methods often miss—opening the door to earlier, more effective intervention. According to another study, the most promising approach may be a hybrid where AI flags risk in real time, and trained humans step in with targeted support.

That hybrid model — AI identifying risk, trained humans providing targeted intervention — is exactly the kind of system you’d want chatbot providers racing to build. Instead, the current regulatory trajectory is telling them: build that, and you’re just creating a liability sinkhole. Every time your system engages with a mental health conversation, you’ve created a potential future lawsuit. Better to just block the conversation entirely and hope the user finds help somewhere else.

I get that some people will reasonably worry that “less liability” sounds like a giveaway to AI companies that are already acting irresponsibly. But Miers and Yeh aren’t arguing that chatbots should be able to impersonate licensed therapists, or that there should be no accountability for products designed to be used by vulnerable users. The American Psychological Association’s approach — prevent chatbots from posing as licensed professionals, limit designs that mimic humans, expand AI literacy — is perfectly compatible with a liability shield for thoughtful, helpful mental health support. The point is to stop punishing the specific behavior we want more of: chatbots that try to actually help people who are struggling, including by building better pathways to professional care for those who need it.

Simply putting liability on the companies is unlikely to do that.

And for people in acute crisis, professional intervention is still a necessity. Nobody serious is arguing chatbots should wholly replace crisis lines or psychiatric care. The argument is that the vast majority of people using chatbots for mental health support are not in acute crisis — they’re anxious, lonely, depressed, processing a breakup, working through stress, looking for someone to talk to at 3am when their therapist isn’t available and calling 988 feels like overkill. For that population — which is the overwhelming majority — the regulatory regime being built assumes the worst and mandates responses that often make things worse.

The deeper problem, as we’ve written before, is that the entire framing of “AI causes suicide” relies on a confidence about the mechanics of suicide that clinicians themselves don’t have. About half of people who die by suicide deny suicidal intent to their doctors in the weeks or month before their death. Experts who have spent decades studying this admit they often cannot predict it even when treating patients directly. The idea that we can identify which chatbot conversation “caused” which outcome, and design liability around that identification, assumes a causal clarity that doesn’t exist anywhere in the actual science.

Good policy here would look very different from what’s being proposed. Miers and Yeh point to a Pennsylvania proposal that would fund development of AI models designed to identify suicide risk factors among veterans — incentivizing the research we actually need rather than punishing it. They suggest liability shields modeled on Section 230 that would encourage continued investment in safer, more responsive systems. They warn specifically against imposing a clinical regulatory framework (with its mandatory reporting requirements) onto general-purpose chatbots, because doing so would replicate exactly the barriers that already keep many people from seeking professional help.

None of this is as emotionally satisfying as “ban the thing that hurt people.” Moral panics rarely are, because moral panics are fundamentally about finding something to blame rather than about the harder work of actually understanding what’s happening and designing interventions that might help. But for the over one million people per week currently turning to chatbots for mental health support — a group that includes at least the thirty Replika users who credit the chatbot with keeping them alive — the difference between a regulatory regime that punishes thoughtful engagement and one that incentivizes it is the difference between having somewhere to turn at 3am or running into a wall of “please call 988” followed by a terminated conversation.

We’ve watched this movie before with social media. We know how it ends. The conversations just move somewhere worse, with fewer resources and less oversight. The tragedies keep happening — they just stop being visible to anyone who might be in a position to help. And the technology gets worse at the thing we want it to be better at, because the legal environment has made getting better into a liability.

If lawmakers are serious about mental health outcomes rather than political theater, they should be asking how to make chatbots better at this — how to build the hybrid human-AI triage systems the research is pointing toward, how to turn these tools into genuine funnels toward professional care when that’s what’s needed, how to preserve the candid, low-stakes space that people clearly find valuable. That project requires a liability regime that rewards trying to be better rather than punishing it. The alternative is what California just passed, and what New York is considering, and what we’ll keep getting until someone in the policy conversation is willing to notice that the intuitive answer here is producing the exact opposite of the intended outcome.

It’s a counterintuitive approach. It’s also the only one that has any chance of actually working.

Last week the Trump FCC quietly announced that it was cooking up a new ban on any labs that have testing offices in China from testing electronic ‌devices such as smartphones, cameras and computers for sale in the United States.

That’s going to create some major issues given that roughly 75% of all U.S.-bound electronics are currently tested in Chinese facilities. Many of these operations are owned by U.S. or European companies that have testing facilities in China because that’s where the lion’s share of technology is manufactured, so it’s simply more efficient for testing evolving iterations of new product.

That these companies have offices in China doesn’t inherently mean the testing labs are somehow all magically compromised and in dutiful service to the Chinese government, though that’s certainly the implication the xenophobic Trump administration is making (and has made before in previous, similar announcements).

One major problem outside of the raw logistics of it all: Carr’s planned cybersecurity fix would be significantly more expensive, driving up costs for everyone:

“27 of the affected facilities are Chinese subsidiaries of major Western testing firms, including Intertek, SGS, TUV Rheinland, and Bureau Veritas. Those companies operate labs in the U.S., Europe, and Taiwan that can absorb redirected work, but the shift won’t be seamless. Basic FCC certification testing runs between $400 and $1,300 at Chinese labs, compared with $3,000 to $4,000 at U.S. equivalents.”

Who is going to eat the difference in those costs? You are, of course. In addition to the higher costs from the AI boom, the tariffs, and Trump’s pointless war in Iran. Whatever companies lobbied Carr and Trump will do great. You probably won’t.

Given the terrible nature of smart IOT home security standards (more a byproduct of unregulated crony capitalism than China-based testing locations), having a more direct line of control over the testing of U.S. bound hardware makes superficial sense.

But then you have to remember that this is Brendan Carr, who does nothing authentically in the public interest, and is likely just looking to drive more business to a handful of U.S. companies that lobbied for his attention. And you have to remember that these folks, as you saw when they talked about shifting smartphone production to the States, don’t actually know what the fuck they’re doing.

The other major problem: Trump and Carr’s rabid deregulatory, anti-governance zealotry on other fronts has repeatedly worked to undermine U.S. cybersecurity, making these sorts of fixes leaky and highly performative, even if they were to be successful (which they won’t be).

While Carr and Trump profess to be super worried about Chinese threats to national security, with their other hand the Trump administration has gutted government cybersecurity programs (including a board investigating the biggest Chinese hack of U.S. telecom networks in history), dismantled the Cyber Safety Review Board (CSRB) (responsible for investigating significant cybersecurity incidents), and fired oodles of folks doing essential work at the Cybersecurity and Infrastructure Security Agency (CISA).

Brendan Carr is also engaged in a massive effort to destroy whatever’s left of the FCC’s consumer protection and corporate oversight authority, despite the fact that the recent historic Chinese Salt Typhoon hack (caused in large part because major telecoms were too incompetent to change default administrative passwords) was a direct byproduct of this exact type of mindless deregulation.

The Trump administration’s stacked courts are also making it extremely difficult to hold telecoms accountable for literally anything (see the Fifth Circuit’s recent reversal of a fine against AT&T for spying on customer movement), which also undermines consumer privacy and national security, and ensures zero real repercussions for companies that fail to secure their networks and sensitive data.

So, with one hand you have Carr claiming he’s “fixing cybersecurity” with stuff like this or his recent foreign router “ban” (which as we’ve noted is really a lazy extortion scheme), while with the other he’s doing everything in his power to ensure that domestic telecoms don’t really have anything even vaguely resembling meaningful privacy and security oversight.

Here’s where I’ll remind you that because the U.S. is too corrupt to pass even a basic modern privacy law, we also have a vast and largely unregulated data broker industry that hoovers up your every movement and online habit, then sells access to it to any random asshole (including foreign and domestic government intelligence agencies).

Here too, weird zealots like Trump and Carr have rolled back efforts to regulate data brokers or do anything about it. As authoritarian racists, they’re too blinded by personal self-enrichment and racism to have any genuine understanding of how any of this stuff actually works.

As with the TikTok “ban” (which basically involved shoveling ownership to Trump’s billionaire buddies), so much of this is heavily xenophobic, nationalistic, transactional, self-serving, and performatively detached from any actual reality. By the time the check comes due, guys like Carr and Trump will already be off to the next grift.

While we’ve taken some issues with his approach to copyright laws and enforcement in the past, there is no doubting that Steven Soderbergh is a filmmaking legend. This is a man who directed films like Traffic and Ocean’s 11. He talks about, and cares about, the art of filmmaking. And he’s apparently beginning to use AI in some limited ways.

You really have to pay attention to Soderbergh’s specific comments on how he’s using it, because I would argue that it’s exactly the right artistic approach to the conversation: limited, targeted uses that help achieve the artist’s vision rather than replace everything in a film with garbage slop. Interestingly, articles like this one from Salon still frame all of this as some betrayal of art on Soderbergh’s part. Here’s how Soderbergh describes how he’s using AI as part of an upcoming film about John Lennon and Yoko Ono.

“AI has been helpful in creating thematically surreal images that occupy a dream space rather than a literal space,” Soderbergh said. “And it’s been really fun because you need a Ph.D. in literature to tell it what to do.” Soderbergh relented that generative programs require “very close human supervision,” before going on to admit that he’s also using “a lot of AI” for an upcoming film about the Spanish-American War, to generate images of archaic warships and God knows what else.

I very much understand Soderbergh’s description of how he’s using this tool for his films, but I have no idea what the hell the commentary from Salon around the quote is on about. “And God knows what else” is perhaps the silliest comment in the post, because that statement only works if Soderbergh himself happens to be God.

I don’t believe he is, to be clear. And I think an artist like this one who finds the tool useful in achieving his overall artistic vision is something we should be paying attention to, not dismissing out of hand. The Salon piece notes that Soderbergh has routinely been a director who has embraced the use of new technology before launching into this diatribe.

But just because Soderbergh jumping at AI could be seen from a mile away doesn’t make it any less disappointing, nor does it excuse his reluctance to thoughtfully engage with others’ criticisms about the technology. If “The Christophers” is to be believed, art that tries to imitate a certain style is little more than hollow, emotionless posturing. Generative AI is the same: mere mimicry, devoid of the humanity that makes art . . . well, art. And by being so willfully averse to acknowledging the ways AI and art conflict — not to mention its ramifications for others in his industry — Soderbergh’s take on an artist losing his touch in “The Christophers” is disappointingly apt.

Of course the art that AI “creates” is mimicry and devoid of humanity. That’s definitionally how the tool works. And anyone who thinks they’re going to rely on an AI tool to “create art” is on a fool’s mission. It simply won’t work because it’s not designed to work that way. Instead, it’s a tool to get you some components of what you need to create an overall artistic vision, which is still led by a very human artist. Will there be work done by an AI on the margins in filmmaking that would normally have been done via paid workers in the industry. Perhaps. Likely, even. But will the limited use of these tools also lower the barrier of entry in terms of skill set needed and budget to produce films, thereby creating even more output of films overall? I’m struggling to see how that would not be the case.

And at the end of the day, there’s still an artist calling the shots. Perhaps fewer overall total artists involved in a single movie, but the limited use of AI tools doesn’t somehow suck the entire soul from a film anymore than the ease of digital footage editing over the use of film does. And just like a movie that is almost nothing other than pretty CGI graphics, but which otherwise sucks, lazy people trying to create entire films with AI are going to fail. And fail hard.

Say it with me now: there is more nuance to this conversation than the hardliners and evangelists are bothering to acknowledge.

In a follow-up chat with Variety, Soderbergh expanded on his initial comments about using AI in future films. “I’m just not threatened by it . . . Ten years ago, I would have needed to engage a visual effects house at an unbelievable cost to come up with this stuff,” he said. “No longer. My job is to deliver a good movie, period. And this tool showed up at a moment when I needed it. I don’t think it’s the solution to everything, and I don’t think it’s the death of everything . . . There are some people that I have absolute love and respect for that refuse to engage with it. That’s their privilege. But I’m not built that way. You show me a new tool, I want to get my hands on it and see what’s going on.”

That’s an artist saying that, folks, not some Silicone Valley tech bro. And, to be clear, he might get it wrong. He may use the tool and his product might suck out loud. But to try to abort the use of a tool before it’s even been explored seems silly.