This post was co-authored by EFF legal intern Noam Shemtov.

We are in a constant dialogue with Internet search engines, ranging from the mundane to the confessional. We ask search engines everything: What movies are playing (and which are worth seeing)? Where’s the nearest clinic (and how do I get there)? Who’s running in the sheriff’s race (and what are their views)? These online queries can give insight into our private details and innermost thoughts, but police increasingly access them without adhering to longstanding limits on government investigative power.

A Virginia appeals court is poised to review such a request in a case called Commonwealth v. Clements. In Clements, police sought evidence under a “reverse-keyword warrant,” a novel court order that compels search engines like Google to hand over information about every person who has looked up a word or phrase online. While the trial judge correctly recognized the privacy interest in our Internet queries, he overlooked the other wide-ranging harms that keyword warrants enable and upheld the search.

But as EFF and the ACLU explained in our amicus brief on appeal, reverse keyword warrants simply cannot be conducted in a lawful way. They invert privacy protections, threaten free speech and inquiry, and fundamentally conflict with the principles underlying the Fourth Amendment and its analog in the Virginia Constitution. The court of appeals now has a chance to say so and protect the rights of Internet users well beyond state lines.

To comply with a keyword warrant, a search engine has to trawl through its entire database of user queries to pinpoint the accounts or devices that made a responsive search. For a dominant service like Google, that means billions of records. Such a wide dragnet will predictably pull in people with no plausible connection to a crime under investigation if their searches happened to include keywords police are interested in.

Critically, investigators seldom have a suspect in mind when they seek a reverse-keyword warrant. That isn’t surprising. True to their name, these searches “work in reverse” from the traditional investigative process. What makes them so useful is precisely their ability to identify Internet users on the sole basis of what they searched online. But what makes a search technique convenient to the government does not always make it constitutional. Quite the opposite: the constitution is anathema to inherently suspicionless dragnets.

The Fourth Amendment forbids “exploratory rummaging”—in fact, it was drafted in direct response to British colonial soldiers’ practice of indiscriminately searching people’s homes and papers for evidence of their opposition to the Crown. To secure a lawful warrant, police must have a specific basis to believe evidence will be found in a given location. They must also describe that location in some detail and say what evidence they expect to find there. It’s hard to think of a less specific description than “all the Internet searches in the world” or a weaker hunch than “whoever committed the crime probably looked up search term x.” Because those airy assertions are all law enforcement can martial in support of keyword warrants, they are “tantamount to high-tech versions of the reviled ‘general warrants’ that first gave rise to the . . . Fourth Amendment” and Virginia’s even stronger search-and-seizure provision.

What’s more, since keyword warrants compel search engine companies to hand over records about anyone anywhere who looked up a particular search term within a given timeframe, they effectively make a suspect out of every person whose online activity falls within the warrant’s sweep. As one court has said about related geofences, this approach “invert[s] probable cause” and “cannot stand.”

Keyword warrants’ fatal flaws are even more drastic considering that privacy rights apply with special force to searches of items—like diaries, booklists, and Internet search queries—that reflect a person’s free thought and expression. As both law and lived experience affirm, the Internet is “the most important place[] . . . for the exchange of views.” Using it—and using keyword searches to navigate the practical infinity of its contents—is “indispensable to participation in modern society.” We shouldn’t have to engage in that core endeavor with the fear that our searches will incriminate us, subject to police officers’ discretion about what keywords are worthy of suspicion. That outcome would predictably chill people from accessing information about sensitive and important topics like reproductive health, public safety, or events in the news that could be relevant to a criminal investigation.

The Virginia Court of Appeals now has the opportunity in Clements to protect privacy and speech rights by affirming that keyword warrants can’t be reconciled with constitutional protections guaranteed at the federal or state level. We hope it does so.

Across the country, people are collecting and sharing footage of masked law enforcement officers from both federal and local agencies deputized to do so-called immigration enforcement: arresting civilians, in some cases violently and/or warrantlessly. That footage is part of a long tradition of recording law enforcement during their operations to ensure some level of accountability if people observe misconduct and/or unconstitutional practices. However, as essential as recording police can be in proving allegations of misconduct, the footage is rendered far less useful when officers conceal their badges and/or faces. Further, lawyers, journalists, and activists cannot then identify officers in public records requests for body-worn camera footage to view the interaction from the officers’ point of view. 

In response to these growing concerns, California has introduced S.B. 627 to prohibit law enforcement from covering their faces during these kinds of public encounters. This builds on legislation (in California and some other states and municipalities) that requires police, for example, “to wear a badge, nameplate, or other device which bears clearly on its face the identification number or name of the officer.” Similarly, police reform legislation passed in 2018 requires greater transparency by opening individual personnel files of law enforcement to public scrutiny when there are use of force cases or allegations of violent misconduct.

But in the case of ICE detentions in 2025, federal and federally deputized officers are not only covering up their badges—they're covering their faces as well. This bill would offer an important tool to prevent this practice, and to ensure that civilians who record the police can actually determine the identity of the officers they’re recording, in case further investigation is warranted. The legislation explicitly includes “any officer or anyone acting on behalf of a local, state, or federal law enforcement agency.” 

This is a necessary move. The right to record police, and to hold government actors accountable for their actions, requires that we know who the government actors are in the first place. The new legislation seeks to cover federal officers in addition to state and local officials, protecting Californians from otherwise unaccountable law enforcement activity. 

As EFF has stood up for the right to record police, we also stand up for the right to be able to identify officers in those recordings. We have submitted a letter to the state legislature to that effect. California should pass S.B. 627, and more states should follow suit to ensure that the right to record remains intact. 

The moment Axon Enterprise announced a new product, Draft One, that would allow law enforcement officers to use artificial intelligence to automatically generate incident report narratives based on body-worn camera audio, everyone in the police accountability community immediately started asking the same questions. 

What do AI-generated police reports look like? What kind of paper trail does this system leave? How do we get a hold of documentation using public records laws? 

Unfortunately, obtaining these records isn't easy. In many cases, it's straight-up impossible. 

Read our full report on how Axon's Draft One defies transparency expectations by design here. 

In some jurisdictions, the documents are walled off behind government-created barriers. For example, California fully exempts police narrative reports from public disclosure, while other states charge fees to access individual reports that become astronomical if you want to analyze the output in bulk. Then there are technical barriers: Axon's product itself does not allow agencies to isolate reports that contain an AI-generated narrative, although an agency can voluntarily institute measures to make them searchable by a keyword.  

This spring, EFF tested out different public records request templates and sent them to dozens of law enforcement agencies we believed are using Draft One. 

We asked each agency for the Draft One-generated police reports themselves, knowing that in most cases this would be a long shot. We also dug into Axon's user manuals to figure out what kind of logs are generated and how to carefully phrase our public records request to get them. We asked for the current system settings for Draft One, since there are a lot of levers police administrators can pull that drastically change how and when officers can use the software. We also requested the standard records that we usually ask for when researching new technologies: procurement documents, agreements, training manuals, policies, and emails with vendors. 

Like all mass public records campaigns, the results were… mixed. Some agencies were refreshingly open with their records. Others assessed us records fees well outside the usual range for a non-profit organization. 

What we learned about the process is worth sharing. Axon has thousands of clients nationwide that use its Tasers, body-worn cameras and bundles of surveillance equipment, and the company is using those existing relationships to heavily promote Draft One.  We expect many more cities to deploy the technology over the next few years. Watchdogging police use of AI will require a nationwide effort by journalists, advocacy organizations and community volunteers.

Below we’re sharing some sample language you can use in your own public records requests about Draft One — but be warned. It’s likely that the more you include, the longer it might take and the higher the fees will get. The template language and our suggestions for filing public records requests are not legal advice. If you have specific questions about a public records request you filed, consult a lawyer.

1. Police Reports

As an add-on to Axon's evidence and records management platforms, Draft One uses ChatGPT to convert audio taken from Axon body-worn cameras into the so-called first draft of the narrative portion of a police report. 

When Politico surveyed seven agencies in September 2024, reporter Alfred Ng found that police administrators did not have the technical ability to identify which reports contained AI-generated language. As Ng reported. “There is no way for us to search for these on our end,” a Lafayette, IN police captain told Ng. Six months later, EFF received the same no-can-do response from the Lafayette Police Department.

Although Lafayette Police could not create a list on their own, it turns out that Axon's engineers can generate these reports for police if asked. When the Frederick Police Department in Colorado received a similar request from Ng, the agency contacted Axon for help. The company does internally track reports written with Draft One and was able to provide a spreadsheet of Draft One reports (.csv) and even provided Frederick Police with computer code to allow the agency to create similar lists in the future. Axon told them they would look at making this a feature in the future, but that appears not to have happened yet. 

But we also struck gold with two agencies: the Palm Beach County Sheriff's Office (PBCSO) in Florida and the Lake Havasu City Police Department in Arizona. In both cases, the agencies require officers to include a disclosure that they used Draft One at the end of the police narrative. Here's a slide from the Palm Beach County Sheriff's Draft One training:

And here's the boilerplate disclosure: 

I acknowledge this report was generated from a digital recording using Draft One by Axon. I further acknowledge that I have I reviewed the report, made any necessary edits, and believe it to be an accurate representation of my recollection of the reported events. I am willing to testify to the accuracy of this report.

As small a gesture as it may seem, that disclosure makes all the difference when it comes to responding to a public records request. Lafayette Police could not isolate the reports because its policy does not require the disclosure. A Frederick Police Department sergeant noted in an email to Axon that they could isolate reports when the auto-disclosure was turned on, but not after they decided to turn it off. This year, Utah legislators introduced a bill to require this kind of disclosure on AI-generated reports.

As the PBCSO records manager 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." In fact, in Palm Beach County and Lake Havasu, records administrators dug up huge numbers of records. But, once we saw the estimated price tag, we ultimately narrowed our request to just 10 reports.

Here is an example of a report from PBCSO, which only allows Draft One to be used in incidents that don't involve a criminal charge. As a result, many of the reports were related to mental health or domestic dispute responses.  

A machine readable text version of this report is available here. Full version here.

And here is an example from the Lake Havasu City Police Department, whose clerk was kind enough to provide us with a diverse sample of requests.

A machine readable text version of this report is available here. Full version here.

EFF redacted some of these records to protect the identity of members of the public who were captured on body-worn cameras. Black-bar redactions were made by the agencies, while bars with X's were made by us. You can view all the examples we received below: 

• 10 Axon Draft One-assisted reports from the Palm Beach County Sheriff's Office
• 10 Axon Draft One-assisted reports from the Lake Havasu Police Department

We also received police reports (perhaps unintentionally) from two other agencies that were contained as email attachments in response to another part of our request (see section 7).

• Frederick Police Department, Colorado
• Lone Tree Police Department, Colorado

2. Audit Logs

Generally, many of the basic actions a police officer takes using Axon technology — whether it's signing in, changing a password, accessing evidence or uploading BWC footage — is logged in the system. 

This also includes some actions when an officer uses Draft One. However, the system only logs three types of activities: requesting that Draft One generate a report, signing a Draft One liability disclosure, or changing Draft One's settings. And these reports are one of the only ways to identify which reports were written with AI and how widely the technology is used. 

Unfortunately, Axon appears to have designed its system so that administrators cannot create a list of all Draft One activities taken by the entire police force. Instead, all they can do is view an individual officer's audit log to see when they used Draft One or look at the log for a particular piece of evidence to see if Draft One was used. These can be exported as a spreadsheet or a PDF. (When the Frederick Police Department asked Axon how to create a list of Draft One reports, the Axon rep told them that feature wasn't available and they would have to follow the above method. "To set expectations, it’s not going to be graceful, but this wasn’t a scenario we anticipated needing to make easy," Axon wrote in August 2024, then suggested it might come up with a long-term solution. We emailed Axon back in March to see if this was still the case, but they did not provide a response.) 

Here's an excerpt from a PDF version from the Bishop Police Department in California:

Here are some additional audit log examples: 

• Campbell Police Department, California (XLSX)
• Lafayette Police Department, Indiana (XLSX)
• Bishop Police Department, California (PDF)
• Pasco Police Department, Washington (CSV)

If you know the name of an individual officer, you can try to request their audit logs to see if they used Draft One. Since we didn't have a particular officer in mind, we had to get creative. 

An agency may manage their documents with one of a few different Axon offerings: Axon Evidence, Axon Records, or Axon Standards. The process for requesting records is slightly different depending on which one is used. We dug through the user manuals and came up with a few ways to export a random(ish) example. We also linked the manuals and gave clear instructions for the records officers.

With Axon Evidence, an administrator can simply sort the system to show the 10 most recent users then export their usage logs. With Axon Records/Standard, the administrator has to start typing in a name and then it auto-populates with suggestions. So, we ask them to export the audit logs for the first few users who came up when they typed the letters M, J, and S into the search (since those letters are common at the beginning of names). 

Unfortunately, this method is a little bit of a gamble. Many officers still aren't using Draft One, so you may end up with hundreds of pages of logs that don't mention Draft One at all (as was the case with the records we received from Monroe County, NY).

3. Settings

We knew the Draft One system offers department managers the option to customize how it can be used, including the categories of crime for which reports can be generated and whether or not there is a disclaimer automatically added to the bottom of the report disclosing the use of AI in its generation. So we asked for a copy of these settings and configurations. In some cases, agencies claimed this was exempted from their public records laws, while other agencies did provide the information. Here is an example from the Campbell Police Department in California: 

(It's worth noting that while Campbell does require each police report to contain a disclosure that Draft One was used, the California Public Records Act exempts police reports from being released.)

Examples of settings: 

• Bishop Police Department, California
• Campbell Police Department, California 
• Pasco Police Department, Washington

4. Procurement-related Documents and Agreements

It can be helpful to know how much Draft One costs, how many user licenses the agency paid for, and what the terms of the agreement are. That information is often contained in records related to the contracting process. Agencies will often provide these records with minimal pushback or redactions. Many of these records may already be online, so a requester can save time and effort by looking around first. These are often found in city council agenda packets. Also, law enforcement agencies often will bump these requests to the city or county clerk instead. 

Here's an excerpt from the Monroe County Sheriff's Office in New York:

These kinds of procurement records describe the nature and cost of the relationship between the police department and the company. They can be very helpful for understanding how much a continuing service subscription will cost and what else was bundled in as part of the purchase. Draft One, so far, is often accessed as an additional feature along with other Axon products. 

We received too many documents to list them all, but here is a representative example of some of the other documents you might receive, courtesy of the Dacono Police Department in Colorado.

5. Training, Manuals and Policies

In addition to seeing when Draft One was used and how it was acquired, it can be helpful to know what rules officers must follow, what directions they're given for using it, and what features are available to users. That's where manuals, policies and training materials come in handy. 

User manuals are typically going to come from Axon itself. In general, if you can get your hands on one, this will help you to better understand the mechanisms of the system, and it will help you align the way you craft your request with the way the system actually works. Luckily, Axon has published many of the materials online and we've already obtained the user manual from multiple agencies. However, Axon does update the manual from time to time, so it can be helpful to know which version the agency is working from.

Here's one from December 2024:

• Dacono Police Department - Axon Draft One User Guide

Policies are internal police department guidance for using Draft One. Not all agencies have developed a policy, but the ones they do have may reveal useful information, such as other records you might be able to request. Here are some examples: 

• Palm Beach County Sheriff's Office General Order 563 - Axon Draft One
• Colorado Springs Police Department General Order 1904 - Use of Specialized Axon System
• Lake Havasu Police Department Policy 342 - Report Preparation
• Campbell Police Department Policy 344 - Report Preparation
• Lafayette Police Department Policy 608 - Computer Software and Transcription-Assisted Report Generation

Training and user manuals also might reveal crucial information about how the technology is used. In some cases these documents are provided by Axon to the customer. These records may illuminate the specific direction that departments are emphasizing about using the product.

Here are a few examples of training presentations:

• Colorado Springs Police Department 2025-Q1-Draft-One-Training
• Palm Beach County Sheriff's Office - Axon Draft One Training Material
• Pasco Police Department - Axon Draft One Presentation

 6. Evaluations

Many departments are getting access to Draft One as part of a trial or pilot program. The outcome of those experiments with the product can be eye-opening or eyebrow-raising. There might also be additional data or a formal report that reviews what the department was hoping to get from the experience, how they structured any evaluation of its time-saving value for the department, and other details about how officers did or did not use Draft One. 

Here are some examples we received: 

• The Effect of Artificial Intelligence has on Time Spent Writing Reports: An analysis of data from the Lake Havasu City Police Department
• Colorado Springs Police Department: Spreadsheets measuring amount of time officers spent writing reports versus using Draft One (zip) 

7. Communications

The communications we wanted were primarily the emails between Axon and the law enforcement agency. As you can imagine, these emails could reveal the back-and-forth between the company and its potential customers, and these conversations could include the marketing pitch made to the department, the questions and problems police may have had with it, and more. 

In some cases, these emails reveal cozy relationships between salespeople and law enforcement officials. Take, for example, this email exchange between the Dickinson Police Department and an Axon rep:

Or this email between a Frederick Police Department sergeant and an Axon representative, in which a sergeant describes himself as "doing sales" for Axon by providing demos to other agencies.

A machine readable text version of this email is available here.

Emails like this also show what other agencies are considering using Draft One in the future. For example, in this email we received from the Campbell Police Department shows that the San Francisco Police Department was testing Draft One as early as October 2024 (the usage was confirmed in June 2025 by the San Francisco Standard).

A machine readable text version of this email is available here.

Your mileage will certainly vary for these email requests, in part because the ability for agencies to search their communications can vary. Some agencies can search by a keyword like "Draft One” or "Axon" and while other agencies can only search by the specific email address. 

Communications can be one of the more expensive parts of the request. We've found that adding a date range and key terms or email addresses has helped limit these costs and made our requests a bit clearer for the agency. Axon sends a lot of automated emails to its subscribers, so the agency may quote a large fee for hundreds or thousands of emails that aren't particularly interesting. Many agencies respond positively if a requester reaches out to say they're open to narrowing or focusing their request. 

Asking for Body-Worn Camera Footage 

One of the big questions is how do the Draft One-generated reports compare to the BWC audio the narrative is based on? Are the reports accurate? Are they twisting people's words? Does Draft One hallucinate?

Finding these answers requires both obtaining the police report and the footage of the incident that was fed into the system. The laws and process for obtaining BWC footage vary dramatically state to state, and even department to department. Depending on where you live, it can also get expensive very quickly, since some states allow agencies to charge you not only for the footage but the time it takes to redact the footage. So before requesting footage, read up on your state’s public access laws or consult a lawyer.

However, once you have a copy of a Draft One report, you should have enough information to file a follow-up request for the BWC footage. 

So far, EFF has not requested BWC footage. In addition to the aforementioned financial and legal hurdles, the footage can implicate both individual privacy and transparency regarding police activity. As an organization that advocates for both, we want to make sure we get this balance right. Afterall, BWCs are a surveillance technology that collects intelligence on suspects, victims, witnesses, and random passersby. When the Palm Beach County Sheriff's Office gave us an AI-generated account of a teenager being hospitalized for suicidal ideations, we of course felt that the minor's privacy outweighed our interest in evaluating the AI. But do we feel the same way about a Draft One-generated narrative about a spring break brawl in Lake Havasu? 

Ultimately, we may try to obtain a limited amount of BWC footage, but we also recognize that we shouldn't make the public wait while we work it out for ourselves. Accountability requires different methods, different expertise, and different interests, and with this guide we hope to not only shine light on Draft One, but to provide the schematics for others–including academics, journalists, and local advocates–to build their own spotlights to expose police use of this problematic technology.

Where to Find More Docs 

Despite the variation in how agencies responded, we did have some requests that proved fruitful. You can find these requests and the documents we got via the linked police department names below.

Please note that we filed two different types of requests, so not all the elements above may be represented in each link.

Via Document Cloud (PDFs)

• Dacono Police Department, Colorado
• Mount Vernon Police Department, Illinois
• Monroe County Sheriff's Office, New York
• Joliet Police Department, Illinois
• Elgin Police Department, Illinois
• Bishop Police Department, California
• Palm Beach County Sheriff's Office
• Lake Havasu City Police Department, Arizona
• Dickinson Police Department, ND 
• Firestone Police Department, Colo.
• Frederick Police Department (DocumentCloud and Google Drive. Frederick provided us a large number of emails in a difficult-to-manage PST format. We unpacked that PST into individual EML files. Because the agency did a keyword search, you may find that some of the emails are not relevant to the issue, but do include the term "draft one."  To reduce the noise, we removed emails that were generated prior to the existence of Draft One. We also removed emails that contained police reports with PII. We redacted those reports and uploaded them independently. While Document Cloud allowed us to convert EML files to PDF files, it did not allow us to keep the relationship between the emails and attachments. You can find those records with the relationships somewhat maintained in Google Drive.)

Via MuckRock (Assorted filetypes)

• Pasco Police Department, Washington (Part 1, Part 2)
• Colorado Springs Police Department, Colorado
• Fort Collins Police Department, Colorado
• Campbell Police Department, California (Part 1, Part 2)
• Lafayette Police Department, Indiana
• East Palo Alto Police Department, California

Special credit goes to EFF Research Assistant Jesse Cabrera for public records request coordination. 

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