It’s not that AI can’t be useful or helpful in certain contexts. And this is certainly not to say AI can’t take over repetitive tasks to allow people to focus on things that need more of human touch.
The problem with AI isn’t necessarily AI itself. It’s that far too many tech companies are pitching AI as a one-size-fits-all solution to pretty much everything. And far too many entities are taking tech companies at their word, with disastrous results.
Axon (formerly Taser) has cornered the body cam market and is now trying to sweep up everything else. While it still hasn’t made a foray into facial recognition tech, it’s pitching products (Draft One and Form One) that use AI to automate report writing for police officers. Draft One has been pitched as a time-saver — one capable of transcribing body cam audio to generate police reports. The company’s CEO Rick Smith thinks this add-on to its body cam products with “potentially free up 25% of an officer’s time.”
Considering a lot of officers spend most of their time engaged in pretextual stops, this isn’t really good news. It just means officers will be able to violate rights more frequently with no perceivable benefit to public safety.
An artificial intelligence that writes police reports had some explaining to do earlier this month after it claimed a Heber City officer had shape-shifted into a frog.
However, the truth behind that so-called magical transformation is simple.
“The body cam software and the AI report writing software picked up on the movie that was playing in the background, which happened to be ‘The Princess and the Frog,'” Sgt. Keel told FOX 13 News. “That’s when we learned the importance of correcting these AI-generated reports.”
Weirdly, this anecdote comes from the same law enforcement agency that claims AI-generated police reports keep this Utah city “safer.” The report doesn’t explain how this is being accomplished. Sgt. Keel simply says the tech saves him “6-8 hours a week.” Sgt. Keel does not explain what’s being done with these extra hours.
The other problem with relying on AI to generate police reports is that officers are generating a new layer of plausible deniability. If errors are found, cops can blame it on the algorithm. Beyond that, there are problems cops pretend don’t exist, like making any testimony reliant on AI-generated reports instantly suspect. If cops aren’t writing their own reports, they can’t possibly claim these statements are their own under oath.
But even if you ignore all of that and choose to focus on the things companies like Axon would prefer you to direct your focus to, we’re still not seeing the sort of improvement that would theoretically offset the downsides of relying on AI. Trial runs of Axon’s new Form One AI product haven’t exactly been a resounding success, as Thomas Brewster reports for Forbes.
[A]fter seven months of testing the technology, many of Lafayette’s officers found the tool was wasting time, not saving it. “I know it doesn’t save me time and I know it has inaccuracies that I will have to edit,” wrote one officer in a cache of emails obtained by Forbes via public records request. Form One struggled to record the right names or car plates, even when they were clearly stated in the camera footage, according to other emails. One cop said a simple form that used to take 30 seconds to fill out manually now takes three minutes with Form One because there are so many errors. “Form One dramatically increases the time it takes to finish reports,” he wrote to a colleague.
That’s just the experience of a single town of 70,000 people in Indiana. Imagine having this amount of routine failure applied to departments with hundreds of officers and thousands of daily reports. What’s worse is that Form One is far less sophisticated than Draft One, which is used to transcribe body cam footage. The software is only expected to accurately add names and addresses to relevant sections of police reports. If it can’t be trusted to do this, there’s little reason to believe Draft One can provide an accurate accounting of a police stop by transcribing audio.
Axon claims these are not indicative of whatever the final product will be. According to the Axon spokesperson, Lafayette was granted “early access” to an (apparently) unfinished AI tool. Axon implies the final product will be better, but neither the Lafayette PD or Axon itself were willing to provide any info that might allow critics to move this from implication to inference.
Manchester, New Hampshire’s police department had roughly the same experience with Draft One.
Ian Adams, a former police officer and criminology professor at the University of South Carolina, studied the Manchester Police Department in New Hampshire’s use of Draft One. Adams analyzed time stamps for when officers started a report and when they filed it. Only some had access to the software. The study found that there was no improvement in how long it took for cops to file reports because they spent a significant amount of time editing the AI system’s work: removing irrelevant information, fixing inaccuracies and adding important facts it missed. “It was just easier to type the report themselves,” says Manchester’s Lieutenant Matthew Barter, who participated in the research.
Weirdly, most officers still thought Draft One sped up report writing, despite data showing otherwise. And even if officers were convinced Draft One was more efficient that simply writing reports themselves, the PD apparently decided the data was more accurate than a bunch of subjective opinions. And it wasn’t the only beta tester (so to speak) to do so:
Even though it was the first agency to test Axon’s Draft One, Manchester ditched it in 2024. The same year, the Anchorage Police Department in Alaska also decided to stop using it, citing zero time savings.
Presumably, these agencies weren’t required to pay for this subpar tech. And while it’s safe to say the tech will continue to improve, the question is whether it will ever be worth it. With fewer courts willing to accept AI-generated court filings and becoming increasingly skeptical of the tech in this context, cop shops are going to be paying for a product that generates reports they can’t submit as testimony or evidence.
Beyond that, the tech apparently needs so much human backstopping that the job of writing reports may as well just be handed back to the humans. Even if it does improve to the point that it can actually reduce the paperwork load on officers, no police department enthused about the tech has specified what will be done with all of this new free time. If it’s just going to be more of the same old policing, the public gains nothing but additional chances to have their rights violated. If the free time is going to be used to build community relationships and route more officers to investigations that might contribute to overall public safety, some sort of trade-off might be acceptable. But from what’s been demonstrated so far, AI is just compounding errors without providing any real usefulness to the communities these law enforcement agencies serve.
Axon Enterprise’s Draft One — a generative artificial intelligence product that writes police reports based on audio from officers’ body-worn cameras — seems deliberately designed to avoid audits that could provide any accountability to the public, an EFF investigation has found.
Our review of public records from police agencies already using the technology — including police reports, emails, procurement documents, department policies, software settings, and more — as well as Axon’s own user manuals and marketing materials revealed that it’s often impossible to tell which parts of a police report were generated by AI and which parts were written by an officer.
You can read our full report, which details what we found in those documents, how we filed those public records requests, and how you can file your own, here.
Everyone should have access to answers, evidence, and data regarding the effectiveness and dangers of this technology. Axon and its customers claim this technology will revolutionize policing, but it remains to be seen how it will change the criminal justice system, and who this technology benefits most.
For months, EFF and other organizations have warned about the threats this technology poses to accountability and transparency in an already flawed criminal justice system. Now we’ve concluded the situation is even worse than we thought: There is no meaningful way to audit Draft One usage, whether you’re a police chief or an independent researcher, because Axon designed it that way.
Draft One uses a ChatGPT variant to process body-worn camera audio of public encounters and create police reports based only on the captured verbal dialogue; it does not process the video. The Draft One-generated text is sprinkled with bracketed placeholders that officers are encouraged to add additional observations or information—or can be quickly deleted. Officers are supposed to edit Draft One’s report and correct anything the Gen AI misunderstood due to a lack of context, troubled translations, or just plain-old mistakes. When they’re done, the officer is prompted to sign an acknowledgement that the report was generated using Draft One and that they have reviewed the report and made necessary edits to ensure it is consistent with the officer’s recollection. Then they can copy and paste the text into their report. When they close the window, the draft disappears.
Any new, untested, and problematic technology needs a robust process to evaluate its use by officers. In this case, one would expect police agencies to retain data that ensures officers are actually editing the AI-generated reports as required, or that officers can accurately answer if a judge demands to know whether, or which part of, reports used by the prosecution were written by AI.
One would expect audit systems to be readily available to police supervisors, researchers, and the public, so that anyone can make their own independent conclusions. And one would expect that Draft One would make it easy to discern its AI product from human product – after all, even your basic, free word processing software can track changes and save a document history.
But Draft One defies all these expectations, offering meager oversight features that deliberately conceal how it is used.
So when a police report includes biased language, inaccuracies, misinterpretations, or even outright lies, the record won’t indicate whether the officer or the AI is to blame. That makes it extremely difficult, if not impossible, to assess how the system affects justice outcomes, because there is little non-anecdotal data from which to determine whether the technology is junk.
The disregard for transparency is perhaps best encapsulated by a short email that an administrator in the Frederick Police Department in Colorado, one of Axon’s first Draft One customers, sent to a company representative after receiving a public records request related to AI-generated reports.
“We love having new toys until the public gets wind of them,” the administrator wrote.
No Record of Who Wrote What
The first question anyone should have about a police report written using Draft One is which parts were written by AI and which were added by the officer. Once you know this, you can start to answer more questions, like:
Are officers meaningfully editing and adding to the AI draft? Or are they reflexively rubber-stamping the drafts to move on as quickly as possible?
How often are officers finding and correcting errors made by the AI, and are there patterns to these errors?
If there is inappropriate language or a fabrication in the final report, was it introduced by the AI or the officer?
Is the AI overstepping in its interpretation of the audio? If a report says, “the subject made a threatening gesture,” was that added by the officer, or did the AI make a factual assumption based on the audio? If a suspect uses metaphorical slang, does the AI document literally? If a subject says “yeah” through a conversation as a verbal acknowledgement that they’re listening to what the officer says, is that interpreted as an agreement or a confession?
Ironically, Draft One does not save the first draft it generates. Nor does the system store any subsequent versions. Instead, the officer copies and pastes the text into the police report, and the previous draft, originally created by Draft One, disappears as soon as the window closes. There is no log or record indicating which portions of a report were written by the computer and which portions were written by the officer, except for the officer’s own recollection. If an officer generates a Draft One report multiple, there’s no way to tell whether the AI interprets the audio differently each time.
Axon is open about not maintaining these records, at least when it markets directly to law enforcement.
In this video of a roundtable discussion about the Draft One product, Axon’s senior principal product manager for generative AI is asked (at the 49:47 mark) whether or not it’s possible to see after-the-fact which parts of the report were suggested by the AI and which were edited by the officer. His response (bold and definition of RMS added):
“So we don’t store the original draft and that’s by design and that’s really because the last thing we want to do is create more disclosure headaches for our customers and our attorney’s offices—so basically the officer generates that draft, they make their edits, if they submit it into our Axon records system then that’s the only place we store it, if they copy and paste it into their third-party RMS [records management system] system as soon as they’re done with that and close their browser tab, it’s gone. It’s actually never stored in the cloud at all so you don’t have to worry about extra copies floating around.”
To reiterate: Axon deliberately does not store the original draft written by the Gen AI, because “the last thing” they want is for cops to have to provide that data to anyone (say, a judge, defense attorney or civil liberties non-profit).
Following up on the same question, Axon’s Director of Strategic Relationships at Axon Justice suggests this is fine, since a police officer using a word processor wouldn’t be required to save every draft of a police report as they’re re-writing it. This is, of course, misdirection and not remotely comparable. An officer with a word processor is one thought process and a record created by one party; Draft One is two processes from two parties–Axon and the officer. Ultimately, it could and should be considered two records: the version sent to the officer from Axon and the version edited by the officer.
The days of there being unexpected consequences of police departments writing reports in word processors may be over, but Draft One is still unproven. After all, every AI-evangelist, including Axon, claims this technology is a game-changer. So, why wouldn’t an agency want to maintain a record that can establish the technology’s accuracy?
It also appears that Draft One isn’t simply hewing to long–establishednorms of police report-writing; it may fundamentally change them. In one email, the Campbell Police Department’s Police Records Supervisor tells staff, “You may notice a significant difference with the narrative format…if the DA’s office has comments regarding our report narratives, please let me know.” It’s more than a little shocking that a police department would implement such a change without fully soliciting and addressing the input of prosecutors. In this case, the Santa Clara County District Attorney had already suggested police include a disclosure when Axon Draft One is used in each report, but Axon’s engineers had yet to finalize the feature at the time it was rolled out.
One of the main concerns, of course, is that this system effectively creates a smokescreen over truth-telling in police reports. If an officer lies or uses inappropriate language in a police report, who is to say that the officer wrote it or the AI? An officer can be punished severely for official dishonesty, but the consequences may be more lenient for a cop who blames it on the AI. There has already been an occasion when engineers discovered a bug that allowed officers on at least three occasions to circumvent the “guardrails” that supposedly deter officers from submitting AI-generated reports without reading them first, as Axon disclosed to the Frederick Police Department.
To serve and protect the public interest, the AI output must be continually and aggressively evaluated whenever and wherever it’s used. But Axon has intentionally made this difficult.
What the Audit Trail Actually Looks Like
You may have seen news stories or other public statements asserting that Draft One does, indeed, have auditing features. So, we dug through the user manuals to figure out what that exactly means.
The first thing to note is that, based on our review of the documentation, there appears to be no feature in Axon software that allows departments to export a list of all police officers who have used Draft One. Nor is it possible to export a list of all reports created by Draft One, unless the department has customized its process (we’ll get to that in a minute).
This is disappointing because, without this information, it’s near impossible to do even the most basic statistical analysis: how many officers are using the technology and how often.
Based on the documentation, you can only export two types of very basic logs, with the process differing depending on whether an agency uses Evidence or Records/Standards products. These are:
A log of basic actions taken on a particular report. If the officer requested a Draft One report or signed the Draft One liability disclosure related to the police report, it will show here. But nothing more than that.
A log of an individual officer/user’s basic activity in the Axon Evidence/Records system. This audit log shows things such as when an officer logs into the system, uploads videos, or accesses a piece of evidence. The only Draft One-related activities this tracks are whether the officer ran a Draft One request, signed the Draft One liability disclosure, or changed the Draft One settings.
This means that, to do a comprehensive review, an evaluator may need to go through the record management system and look up each officer individually to identify whether that officer used Draft One and when. That could mean combing through dozens, hundreds, or in some cases, thousands of individual user logs.
An example of Draft One usage in an audit log.
An auditor could also go report-by-report as well to see which ones involved Draft One, but the sheer number of reports generated by an agency means this method would require a massive amount of time.
But can agencies even create a list of police reports that were co-written with AI? It depends on whether the agency has included a disclosure in the body of the text, such as “I acknowledge this report was generated from a digital recording using Draft One by Axon.” If so, then an administrator can use “Draft One” as a keyword search to find relevant reports.
Agencies that do not require that language told us they could not identify which reports were written with Draft One. For example, one of those agencies and one of Axon’s most promoted clients, the Lafayette Police Department in Indiana, told us:
“Regarding the attached request, we do not have the ability to create a list of reports created through Draft One. They are not searchable. This request is now closed.”
Meanwhile, in response to a similar public records request, the Palm Beach County Sheriff’s Office, which does require a disclosure at the bottom of each report that it had been written by AI, was able to isolate more than 3,000 Draft One reports generated between December 2024 and March 2025.
They told us: “We are able to do a keyword and a timeframe search. I used the words draft one and the system generated all the draft one reports for that timeframe.”
We have requested further clarification from Axon, but they have yet to respond.
However, as we learned from email exchanges between the Frederick Police Department in Colorado and Axon, Axon is tracking police use of the technology at a level that isn’t available to the police department itself.
In response to a request from Politico’s Alfred Ng in August 2024 for Draft One-generated police reports, the police department was struggling to isolate those reports.
An Axon representative responded: “Unfortunately, there’s no filter for DraftOne reports so you’d have to pull a User’s audit trail and look for Draft One entries. To set expectations, it’s not going to be graceful, but this wasn’t a scenario we anticipated needing to make easy.”
But then, Axon followed up: “We track which reports use Draft One internally so I exported the data.” Then, a few days later, Axon provided Frederick with some custom JSON code to extract the data in the future.
What is Being Done About Draft One
The California Assembly is currently considering SB 524, a bill that addresses transparency measures for AI-written police reports. The legislation would require disclosure whenever police use artificial intelligence to partially or fully write official reports, as well as “require the first draft created to be retained for as long as the final report is retained.” Because Draft One is designed not to retain the first or any previous drafts of a report, it cannot comply with this common-sense and first-step bill, and any law enforcement usage would be unlawful.
Axon markets Draft One as a solution to a problem police have been complaining about for at least a century: that they do too much paperwork. Or, at least, they spend too much time doing paperwork. The current research on whether Draft One remedies this issue shows mixed results, from some agencies claiming it has no real-time savings, with others agencies extolling its virtues (although their data also shows that results vary even within the department).
In the justice system, police must prioritize accuracy over speed. Public safety and a trustworthy legal system demand quality over corner-cutting. Time saved should not be the only metric, or even the most important one. It’s like evaluating a drive-through restaurant based only on how fast the food comes out, while deliberately concealing the ingredients and nutritional information and failing to inspect whether the kitchen is up to health and safety standards.
Given how untested this technology is and how much the company is in a hurry to sell Draft One, many local lawmakers and prosecutors have taken it upon themselves to try to regulate the product’s use. Utah is currently considering a bill that would mandate disclosure for any police reports generated by AI, thus sidestepping one of the current major transparency issues: it’s nearly impossible to tell which finished reports started as an AI draft.
We do not fear advances in technology – but we do have legitimate concerns about some of the products on the market now… AI continues to develop and we are hopeful that we will reach a point in the near future where these reports can be relied on. For now, our office has made the decision not to accept any police narratives that were produced with the assistance of AI.
We urge other prosecutors to follow suit and demand that police in their jurisdiction not unleash this new, unaccountable, and intentionally opaque AI product.
Conclusion
Police should not be using AI to write police reports. There are just too many unanswered questions about how AI would translate the audio of situations and whether police will actually edit those drafts, while simultaneously, there is no way for the public to reliably discern what was written by a person and what was written by a computer. This is before we even get to the question of how these reports might compound and exacerbate existing problems or create new ones in an already unfair and untransparent criminal justice system.
EFF will continue to research and advocate against the use of this technology but for now, the lesson is clear: Anyone with control or influence over police departments, be they lawmakers or people in the criminal justice system, has a duty to be informed about the potential harms and challenges posed by AI-written police reports.
It often seems that when people have no good ideas or, indeed, any ideas at all, the next thing out of their mouths is “maybe some AI?” It’s not that AI can’t be useful. It’s that so many use cases are less than ideal.
Enter Axon, formerly Taser, which has moved from selling modified cattle prods to cops to selling them body cameras. The shift makes sense. Policy makers want to believe body cameras will create more accountability in police forces that have long resisted this. Cops don’t mind this push because it’s far more likely body cam footage will deliver criminal convictions than it will force them to behave better when wielding the force of law.
Axon wants to keep cops hooked on body cams. It hands them out like desktop printers: cheap entry costs paired with far more expensive, long-term contractual obligations. Buy a body cam from Axon on the cheap and expect to pay fees for access and storage for years to come. Now, there’s another bit of digital witchery on top of the printer cartridge-esque access fees: AI assistance for police reports.
Theoretically, it’s a win. Cops will spend less time bogged down in paperwork and more time patrolling the streets. In reality, it’s something else entirely: the abdication of responsibility to algorithms and a little more space separating cops from accountability.
AI can’t be relied on to recap news items coherently. It’s already shown it’s capable of “hallucinating” narratives due to the data it relies on or has been trained on. There’s no reason to believe that, at this point, AI is capable of performing tasks cops have been doing for years: writing up arrest/interaction reports.
The problem here is that a bogus AI-generated report causes far more real-world pain than that experienced by news agencies that endure momentary public shaming or lawyers being chastised by judges. People can lose their rights and their actual freedom if AI concocts a narrative that supports the actions taken by officers. Even at its best, AI should not be allowed to determine whether or not people have access to their rights or literal freedom.
“Police reports play a crucial role in our justice system,” ACLU speech, privacy and technology senior policy analyst and report author Jay Stanley wrote. “Concerns include the unreliability and biased nature of AI, evidentiary and memory issues when officers resort to this technology, and issues around transparency.
“In the end, we do not think police departments should use this technology,” Stanley concluded.
There’s more in this article from The Register than just some summarizing of the ACLU’s comprehensive report [PDF]. It also features input from people who’ve actually done this sort of work on the ground level who align themselves with the ACLU’s criticism, rather than the government agencies they worked for. This is from Brandon Vigliarolo, who wrote this op-ed for El Reg:
In my time as a Military Policeman in the US Army, I spent plenty of time on shifts writing boring, formulaic, and necessarily granular reports on incidents, and it was easily the worst part of my job. I can definitely sympathize with police in the civilian world, who deal with far worse – and more frequent – crimes than I had to address on small bases in South Korea.
That said, I’ve also had a chance to play with modern AI and report on many of its shortcomings, and the ACLU seems to definitely be on to something in Stanley’s report. After all, if we can’t even trust AI to write something as legally low-stakes as news or a bug report, how can we trust it to do decent police work?
The answer is we can’t. We can’t do it now. And there’s a solid chance we can’t do it ever.
Both Axon and law enforcement agencies choosing to utilize this tech will claim human backstops will prevent AI from hallucinating someone into jail or manufacturing justification for civil rights violations. But that’s obviously not true. And that’s been confirmed by Axon itself, whose future business relies on future uptake of its latest tech offering.
In an ideal world, Stanley added, police would be carefully reviewing AI-generated drafts, but that very well may not be the case. The report notes that Draft One includes a feature that can intentionally insert silly sentences into AI-produced drafts as a test to ensure officers are thoroughly reviewing and revising the drafts. However, Axon’s CEO mentioned in a video about Draft One that most agencies are choosing not to enable this feature.
This leading indicator suggests cop shops are looking for a cheap way to relieve the paperwork burden on officers, presumably to free them up to do the more important work of law enforcement. The lower cost/burden seems to be the only focus, though. Even when given something as simple as a single-click option to ensure better human backstopping of AI-generated police reports, agencies are opting out because, apparently, it might mean some reports will be rejected and/or the thin veil of plausible deniability might be pierced.
That’s part of the bargain. If a robot writes a report, officers can plausibly claim discrepancies between reports and recordings aren’t their fault. But that’s not even the only problem. As the ACLU report notes, there’s a chance AI-generated reports will decided something “seen” or “heard” in recordings supports officers’ actions, even if human review of the same footage would see clear rights violations.
The other problem is inadvertent confirmation bias. In an ideal world, any arrest or interaction that has resulted in questionable force deployment — especially when cops kill someone — cops would need to give statements before they’ve had a chance to review recordings. This would help eliminate post facto narratives that remove contradictory statements and allow officers to agree upon an exonerative narrative. Allowing AI to craft reports from uploaded footage undercuts this necessary time-and-distance factor, giving cops’ cameras the chance to tell the story before the cops have even come up with their own.
Now, it might seem that would be better. But I can guarantee you that if the AI report doesn’t agree with the officer’s report in disputed situations, the AI-generated report will be kicked to the curb. And it works the other way, too.
Even the early adopters of body cams found a way to make this so-called “accountability” tech work for them. When the cameras weren’t being turned on or off to suit narrative needs, cops were attacking compliant arrestees while yelling things like “stop resisting” or claiming the suspect was trying to grab one of their weapons. The subjective angle, coupled with extremely subjective statements in the recordings, was leveraged to provide justification for any lovely of force deployed. AI is incapable of separating cop pantomime from what’s captured on tape, which means all cops have to do to talk a bot into backing their play is say a bunch of stuff that sounds like probable cause while recording an arrest or search.
We already know most law enforcement agencies rarely proactively review body cam footage. And they’re even less likely to review reports and question officers if things look a bit off. Most agencies don’t have the personnel to handle proactive reviews, even if they have the desire to engage in better oversight. And an even larger percentage lack the desire to police their police officers, which means there will never be enough people in place to check the work (and paperwork) of law enforcers.
Adding AI won’t change this equation. It will just make direct oversight that much simpler to abandon. Cops won’t be held accountable because they can always blame discrepancies on the algorithm. And the tech will encourage more rights violations because it adds another layer of deniability officers and their supervisors can deploy when making statements in state courts, federal courts, or the least-effective court of all, the court of public opinion.
These are all reasons accountability-focused legislators, activists, and citizens should oppose a shift to AI-enhanced police reports. And they’re the same reasons that will encourage rapid adoption of this tech by any law enforcement agency that can afford it.
Axon — having apparently exhausted the market for Tasers — has moved on to hawking body cameras to police departments. The cameras are the loss leaders. The real money comes from perpetual service contracts and access fees. With every new feature added to Axon’s line of products, the difficulty level of switching manufacturers and service providers increases.
And that’s exactly why Axon decided to add some AI to the mix. It’s one more thing that, once established, would be nearly impossible to easily replace on the fly, should a law enforcement agency consider taking their business to a competitor.
The AI isn’t there to help identify objects or people captured by Axon’s body cams (although that’s likely on its way as well). Axon thinks the future of policing involves trimming the time officers spend writing reports, theoretically freeing them up to do more policing and less paperwork.
On Tuesday, Axon, the $22 billion police contractor best known for manufacturing the Taser electric weapon, launched a new tool called Draft One that it says can transcribe audio from body cameras and automatically turn it into a police report. Cops can then review the document to ensure accuracy, Axon CEO Rick Smith told Forbes. Axon claims one early tester of the tool, Fort Collins Colorado Police Department, has seen an 82% decrease in time spent writing reports. “If an officer spends half their day reporting, and we can cut that in half, we have an opportunity to potentially free up 25% of an officer’s time to be back out policing,” Smith said.
Well, given the number of debacles creating by over-reliance on AI, this hardly seems like an ideal growth market. But Axon seems pretty convinced cops will grow to love this tech tool. And they might! After all, they’re not nearly as concerned about the collateral damage AI-enhanced report writing might cause as the people who are the most likely victims of this collateral damage… which would be pretty much everyone but the cops themselves.
Fortunately, there’s already been some pushback against Axon’s shiny new toy. And it comes from kind of an unexpected source: prosecutors. Law enforcement agencies in Washington State’s most populous county are being told in no uncertain terms, AI-crafted police reports are not welcome here. (h/t EFF)
The King County Prosecuting Attorney’s Office (KCPAO) has instructed police agencies to not use Artificial Intelligence (AI) when writing reports.
In a memo to police chiefs sent this week, Chief Deputy Prosecutor Daniel J. Clark said any reports written with the assistance of AI will be rejected due to the possibility of errors.
“We do not fear advances in technology – but we do have legitimate concerns about some of the products on the market now,” Clark’s memo states. “AI continues to develop and we are hopeful that we will reach a point in the near future where these reports can be relied on. For now, our office has made the decision not to accept any police narratives that were produced with the assistance of AI.”
What’s being stated here isn’t speculation. It’s already happened. Clark cited an AI-assisted report received by prosecutors that referenced an officer who wasn’t actually at the scene.
Axon, however, still remains bullish on its new offering. Its statement in response to this announcement by the KCPAO says a lot of things that sound meaningful, but are ultimately meaningless once you understand every asserted backstop relies on cops doing their job thoroughly, honestly, and competently.
“Agencies have various considerations when implementing new public safety technology and Axon is dedicated to offering comprehensive resources to support them throughout this process as well as addressing questions or concerns. With Draft One, initial report narratives are drafted strictly from the audio transcript from the body-worn camera recording and Axon calibrated the underlying model for Draft One to minimize speculation or embellishments. Police narrative reports continue to be the responsibility of officers and critical safeguards require every report to be edited, reviewed and approved by a human officer, ensuring accuracy and accountability of the information. Axon rigorously tests our AI-enabled products and adheres to a set of guiding principles to ensure we innovate responsibly, including building in controls so that human decision-making is never removed in critical moments.“
Police reports have never been the paragon of accuracy. And when cops need to cover something up, they’re filled with deliberate misstatements (we call those “lies” in the civilian world) and omissions. Claiming adding AI to the mix will ultimately be OK because cops are the final backstop for accuracy belies a willful ignorance of how this process works in the real world.
The only meaningful move being made here is the ban on AI-assisted reports by prosecutors. This means any agency that’s currently paying for Draft One access should — if the King County prosecutor’s office is serious about this — have all of its reports rejected out-of-hand until access is removed and/or Draft One contracts are terminated.
So, for now, King County will only allow human-generated narrative “hallucinations” to be used during prosecutions. And while it’s not much to cheer about, at least it prevents officers from distancing themselves from their lies by blaming software for inconsistencies in their statements.
So, in 2021 there was a car accident in Atwater California that killed a married couple, Pam and Joe Juarez. According to police reports at the time, a 20-year-old Stanford student, King Vanga, struck their car from behind. Here’s how ABC 30 reported on the matter:
The California Highway Patrol says Pam, 56, and Joe, 57, were driving west on Santa Fe Avenue approaching Spaceport Entry in Atwater.
They were just minutes away from their son’s house.
Officials say that’s when 20-year-old King Vanga collided into the back of their car at a high rate of speed.
The Juarez’s spun out and their vehicle caught fire.
Vanga overturned into a fence.
The Juarez’s died at the scene.
Vanga had minor injuries was booked into the Merced County Jail for driving under the influence of drugs and/or alcohol and vehicular manslaughter.
The filed police reports claim that the officers believed Vanga was under the influence of alcohol, saying they smelled alcohol, though they were unable to administer a field sobriety test. He was still charged with a DUI, along with the vehicular manslaughter charges.
Vanga has since sued the police, claiming that the police violated his rights by attacking and tasing him, and that he “never drinks” and therefore the DUI charges are bogus. A blood test that was analyzed later by the California DOJ found that he had no traces of alcohol in his blood at the time, so it is entirely possible that he wasn’t actually drunk. Whether or not he was actually drunk or not seems like a fairly minor point in all of this, given that two people died in an accident where Vanga drove into the back of their car at high speed.
The family of Pam & Joe Juarez were understandably upset by their death, and a few family members sent emails to Stanford to alert them to what had happened, and alert them that they did not feel that Vanga had live up to Stanford’s code of conduct.
Vanga, somewhat incredibly, has decided to sue the family members of the couple he killed, claiming that their emails to Stanford were defamatory, because (a) they mention the DUI based on the police report and public reporting and (b) some of them said he “murdered” their family members, rather than merely killing them.
Let me repeat that, because it is quite incredible. It is undisputed that Vanga rear-ended another car, leading to the death of the two people in that car. Some of family members of the dead couple sent understandably angry letters to Stanford, the university Vanga attended. And now Vanga has sued those family members for relying on a potentially inaccurate police report, and using the word “murder” for what he did.
This is the SLAPPiest of SLAPP suits.
And now one of the defendants, Priscilla Juarez (a daughter-in-law of the deceased couple), has brought on Ken “Popehat” White to represent her against this insult-to-injury lawsuit. White has now filed an anti-SLAPP motion on Juarez’s behalf that calls out just how crazy this situation is:
Plaintiff King Vanga, a privileged student at an elite university, killed Defendant Priscilla Juarez’s in-laws and is now suing her for privately complaining about it. He is doing so in an overt effort to extort from her a promise not to encourage his criminal prosecution. This is a shocking and contemptible abuse of the justice system. Fortunately, the system that lets King Vanga abuse and harass his victims also provides a remedy – California’s robust anti-SLAPP statute. Plaintiff’s First Amended Complaint (“FAC”) is a classic SLAPP, and this Court should dismiss it and award Ms. Juarez her fees and costs.
It’s undisputed that King Vanga was in a car accident that killed Jose and Pamela Juarez, Ms. Juarez’ husband’s parents. It’s also undisputed that Merced County charged Plaintiff with vehicular manslaughter and DUI causing great injury, and that the press widely reported that Plaintiff was intoxicated at the time of the accident. Based on the criminal charges against Plaintiff, the press coverage she reviewed, and statements by police officers on the scene, Ms. Juarez wrote an email (“the Email”) to Stanford University stating her opinion that Plaintiff had violated its honor code, based explicitly on the criminal charges and press coverage. There’s no indication that Stanford disciplined Plaintiff. Instead, Plaintiff got a copy of the Email through a FERPA request, used it as an opportunity to sue Ms. Juarez for defamation, and made an extortionate demand that he would not drop the suit unless Ms. Juarez stopped talking about him killing her in-laws and stopped pushing for his prosecution.
California’s anti-SLAPP statute protects Ms. Juarez from King Vanga’s loathsome and immoral abuse of process. Ms. Juarez easily meets the first prong of the anti-SLAPP test, as her Email was sent in relation to an ongoing judicial proceeding and was an exercise of her right to free speech on an issue of public interest. But Plaintiff cannot carry his burden of showing a probability of prevailing. Most of the Email was Ms. Juarez’ overt opinions and conclusions, and was absolutely protected by the First Amendment. To the extent Ms. Juarez repeated factual allegations in the criminal complaint against Plaintiff and the extensive news coverage of the accident, Plaintiff cannot show that Ms. Juarez was negligent to rely on it.
Such a rule would mean that crime victims could never comment on crimes based on criminal charges and news coverage. Ms. Juarez’s statement is also protected by California’s common interest privilege. Finally, Plaintiff cannot provide admissible evidence of damages resulting from the Email. The Court should grant this Motion, dismiss this utterly shameful FAC, and award Ms. Juarez her attorney fees and costs.
There’s much more in the anti-SLAPP motion to strike. It details how Priscilla not only read the news about this, which accurately reported what Vanga was charged with, but also that family members had spoken with the arresting officer, who told them of his belief that Vanga was intoxicated. Whether or not that turned out to be true, it certainly shows that Juarez had a justification for saying what she said.
It also highlights how the first time she heard about Vanga denying being intoxicated was when he filed his lawsuit against the police, which was long after she had sent her email to Stanford.
And then there’s this:
After filing the lawsuit, Plaintiff’s counsel sent Mrs. Juarez an email offering to drop the lawsuit if Ms. Juarez agreed “not to make or publish any disparaging statements about Mr. Vanga in the future” and “not to encourage the criminal prosecution of Mr. Vanga, including by communicating with government officers or protesting at any conference, hearing, or trial involving Mr. Vanga.” (Juarez Decl. at ⁋21; Exhibit 9). Mrs. Juarez did not agree to abandon her First Amendment right to advocate for her in-laws.
Gross.
Again, it is entirely possible that the cops were wrong in believing Vanga was intoxicated. We’ve covered many cases on this very site about cops being wrong. So if Vanga wants to sue the cops, more power to him.
But suing the family of the people who died because he rear-ended their car, for sending a private email to Stanford (over which the University took no action), based on public reporting and what officers on the scene said, is fucking crazy. It’s yet another example of abusing the courts to silence someone, and in this particular case adding real insult to actual injury.
The court should grant the motion to strike and make him pay through the nose for this gross abuse of the legal process to silence speech.
This is why we have been arguing for years for more and better anti-SLAPP laws. Luckily, California has a strong one. But many states do not. And even in many states that do have one, it cannot apply in federal court. We need every state to have a strong anti-SLAPP law and we need a federal anti-SLAPP law.
Rental car company Hertz has put the “hurt” back in, um, “Hertz.” The company recently declared itself bankrupt, something that presumably only referred to its balance sheet.
But Hertz has more problems. In 2021 (the same year Hertz “emerged” from bankruptcy), the company was sued by a man who could have been cleared of murder charges if only the company has been interested in finding his rental receipt. It took the company three years to produce the records clearing Herbert Alford, but that came at the tail end of Alford’s five years behind bars.
More recently, the company has been sued for falsely reporting rental vehicle thefts — something that has led to false charges, wrongful imprisonment, and a class action lawsuit. Hertz’s best practices when it comes to suspected theft are apparently the worst. Hundreds of plaintiffs claim Hertz doesn’t do much in terms of verification, apparently preferring law enforcement handle its due diligence for it. Unfortunately, turning this over to law enforcement means people lose their freedoms. And, if the practice continues, people are going to lose their lives.
Bogus stolen vehicle reports lead to guns out traffic stops by law enforcement. Once the guns are out, it’s up to the driver to ensure they don’t get shot. That’s not always going to work out and Hertz is lucky it’s not fielding wrongful death suits. But that luck isn’t going to hold forever. Sooner or later, the utterly imaginable will happen and Hertz will be somewhat responsible for the dead body lying near an officer who mistook confusion for resistance.
Hertz claims in court this inability to properly research alleged thefts only affects a very small percentage of its customers. But that still means 3,500-8,000 customers are wrongly accused of theft every year. Thousands of false reports are resulting in dozens of cases where people have lost their jobs, their freedom (at least temporarily), and their ability to live a normal life despite never having stolen a car from Hertz.
Daniel Stokes worked for Hertz for 11 years from 1996 till 2007 and was a branch and city manager in charge of 24 different Hertz locations.
“Being a city manager and knowing what the processes were and learning more about what actually happens to the people, quite honestly, it pissed me off that knowing that it was still going on,” Stokes told NewsNation investigative reporter Rich McHugh.
Stokes believes the way Hertz is managing this current process is wrong.
“I don’t see how it’s legal,” Stokes said.
He says Hertz should not be involving police in most of these cases, but a collections company, instead.
In cases where customers have rented a car and not returned it on the due date, “Hertz is actually using the police department as a repo company and the court system as a collection company,” Stokes said. “All of these supposed embezzlement by thefts are collection issues. They’re not actual thefts.”
As a private company, Hertz is free to pursue alleged theft however it wants to. But that freedom to pursue ends where its bottom line meets the public dollar. A private company should not be using law enforcement as its proxy collection effort, especially when Hertz is often wrong about its theft allegations. This offloads the cost and potentially deadly outcomes to non-customers, who are forced to not only pay for enforcement efforts triggered by Hertz’s theft reports, but officers who may be sued for actions they’ve taken in response to possibly bogus reports.
According to the whistleblower, Hertz’s rental system lags behind its theft-reporting system. Even if a car has been returned after it was due and all additional charges paid, the car is handed over to a new renter prior to the car being cleared. That leads to more false theft reports, this time targeting a new renter who has returned a vehicle late or otherwise raised flags in the rental system.
Hertz has yet to respond to these allegations. That’s unsurprising, considering it’s currently being sued for doing exactly the sort of thing alleged by the whistleblower. To be clear, there has been no independent verification of the claims made by the former Hertz employee — one who was also allegedly falsely accused of theft and embezzlement by his employer over his use of a company-owned car while he was on medical leave.
If anything lends credence to this whistleblower’s claims, it’s the fact that no other car rental company is facing similar allegations. This indicates something is severely broken in Hertz’s rental system — one that allows rental agents to not only act on limited info, but to compel law enforcement to act on reports that appear to be lacking in actionable evidence.
Deliberately or inadvertently, Hertz has managed to leverage human nature to create a cottage industry of false accusations and bogus arrests. Hertz employees naturally want to limit theft of vehicles. And law enforcement officers are always looking for a good bust — one that rises about the normal street hassle that tends to define their day-to-day work. When it all comes together, innocent people who owe Hertz nothing and who haven’t actually broken any laws are becoming victims of a justice system that moves fastest when it’s working with nothing more than allegations and much more slowly when it comes to clearing people who are supposed to be presumed innocent.
As was noted above, Hertz is still involved in a lawsuit over its sketchy theft reporting practices. It has been ordered to turn over information about its theft reports to the court. Discovery continues. Whether or not there’s anything to the whistleblower’s allegations may soon become public record. But until then, we should remain skeptical of these claims, but not so skeptical we refuse to acknowledge the uncomfortable fact that no other rental car company in the nation is facing similar allegations from hundreds of renters.
