MTC: Everyday Tech, Extraordinary Evidence: How Lawyers Can Turn Smartphones, Dash Cams, and Wearables Into Case‑Winning Proof After the Minnesota ICE Shooting 📱⚖️

Smartphone evidence: Phone as Proof!

The recent fatal shooting of ICU nurse Alex Pretti by a federal immigration officer in Minneapolis has become a defining example of how everyday technology can reshape a high‑stakes legal narrative. 📹 Federal officials claimed Pretti “brandished” a weapon, yet layered cellphone videos from bystanders, later analyzed by major news outlets, appear to show an officer disarming him moments before multiple shots were fired while he was already on the ground. In a world where such encounters are documented from multiple angles, lawyers who ignore ubiquitous tech risk missing powerful, and sometimes exonerating, evidence.

Smartphones: The New Star Witness

In the Minneapolis shooting, multiple smartphone videos captured the encounter from different perspectives, and a visual analysis highlighted discrepancies between official statements and what appears on camera. One video reportedly shows an officer reaching into Pretti’s waistband, emerging with a handgun, and then, barely a second later, shots erupt as he lies prone on the sidewalk, still being fired upon. For litigators, this is not just news; it is a case study in how to treat smartphones as critical evidentiary tools, not afterthoughts.

Practical ways to leverage smartphone evidence include:

  • Identifying and preserving bystander footage early through public calls, client outreach, and subpoenas to platforms when appropriate.

  • Synchronizing multiple clips to create a unified timeline, revealing who did what, when, and from where.

  • Using frame‑by‑frame analysis to test or challenge claims about “brandishing,” “aggressive resistance,” or imminent threat, as occurred in the Pretti shooting controversy.

In civil rights, criminal defense, and personal‑injury practice, this kind of video can undercut self‑defense narratives, corroborate witness accounts, or demonstrate excessive force, all using tech your clients already carry every day. 📲

GPS Data and Location Trails: Quiet but Powerful Proof

The same smartphones that record video also log location data, which can quietly become as important as any eyewitness. Modern phones can provide time‑stamped GPS histories that help confirm where a client was, how long they stayed, and in some instances approximate movement speed—details that matter in shootings, traffic collisions, and kidnapping cases. Lawyers increasingly use this location data to:

Dash cam / cameras: Dashcam Truth!

  • Corroborate or challenge alibis by matching GPS trails with claimed timelines.

  • Reconstruct movement patterns in protest‑related incidents, showing whether someone approached officers or was simply present, as contested in the Minneapolis shooting narrative.

  • Support or refute claims that a vehicle was fleeing, chasing, or unlawfully following another party.

In complex matters with multiple parties, cross‑referencing GPS from several phones, plus vehicle telematics, can create a robust, data‑driven reconstruction that a fact‑finder can understand without a computer science degree.

Dash Cams and 360‑Degree Vehicle Video: Replaying the Scene

Cars now function as rolling surveillance systems. Many new vehicles ship with factory cameras, and after‑market 360‑degree dash‑cam systems are increasingly common, capturing impacts, near‑misses, and police encounters in real time. In a Minneapolis‑style protest environment, vehicle‑mounted cameras can document:

  • How a crowd formed, whether officers announced commands, and whether a driver accelerated or braked before an alleged assault.

  • The precise position of pedestrians or officers relative to a car at the time of a contested shooting.

  • Sound cues (shouts of “he’s got a gun!” or “where’s the gun?”) that provide crucial context to the video, like those reportedly heard in footage of the Pretti shooting.

For injury and civil rights litigators, requesting dash‑cam footage from all involved vehicles—clients, third parties, and law‑enforcement—should now be standard practice. 🚗 A single 360‑degree recording might capture the angle that police‑worn cameras miss or omit.

Wearables and Smartwatches: Biometrics as Evidence

GPS & wearables: Data Tells All!

Smartwatches and fitness trackers add a new dimension: heart‑rate, step counts, sleep data, and sometimes even blood‑oxygen metrics. In use‑of‑force incidents or violent encounters, this information can be unusually persuasive. Imagine:

  • A heart‑rate spike precisely at the time of an assault, followed by a sustained elevation that reinforces trauma testimony.

  • Step‑count and GPS data confirming that a client was running away, standing still, or immobilized as claimed.

  • Sleep‑pattern disruptions and activity changes supporting damages in emotional‑distress claims.

These devices effectively turn the body into a sensor network. When combined with phone video and location data, they help lawyers build narratives supported by objective, machine‑created logs rather than only human recollection. ⌚

Creative Strategies for Integrating Everyday Tech

To move from concept to courtroom, lawyers should adopt a deliberate strategy for everyday tech evidence:

  • Build intake questions that explicitly ask about phones, car cameras, smartwatches, home doorbell cameras, and even cloud backups.

  • Move quickly for preservation orders, as Minnesota officials did when a judge issued a temporary restraining order to prevent alteration or removal of shooting‑related evidence in the Pretti case.

  • Partner with reputable digital‑forensics professionals who can extract, authenticate, and, when needed, recover deleted or damaged files.

  • Prepare demonstrative exhibits that overlay video, GPS points, and timelines in a simple visual, so judges and juries understand the story without technical jargon.

The Pretti shooting also underscores the need to anticipate competing narratives: federal officials asserted he posed a threat, while video and witness accounts cast doubt on that framing, fueling protests and calls for accountability. Lawyers on all sides must learn to dissect everyday tech evidence critically—scrutinizing what it shows, what it omits, and how it fits with other proof.

Ethical and Practical Guardrails

Ethics-focused image: Ethics First!

With this power comes real ethical responsibility. Lawyers must align their use of everyday tech with core duties under the ABA Model Rules of Professional Conduct.

  • Competence (ABA Model Rule 1.1)
    Rule 1.1 requires “competent representation,” and Comment 8 now expressly includes a duty to keep abreast of the benefits and risks of relevant technology. When you rely on smartphone video, GPS logs, or wearable data, you must either develop sufficient understanding yourself or associate with or consult someone who does.

  • Confidentiality and Data Security (ABA Model Rule 1.6)
    Rule 1.6 obligates lawyers to make reasonable efforts to prevent unauthorized access to or disclosure of client information. This extends to sensitive video, location trails, and biometric data stored on phones, cloud accounts, or third‑party platforms. Lawyers should use secure storage, limit access, and, where appropriate, obtain informed consent about how such data will be used and shared.

  • Preservation and Integrity of Evidence (ABA Model Rules 3.4, 4.1, and related e‑discovery ethics)
    ABA ethics guidance and case law emphasize that lawyers must not unlawfully alter, destroy, or conceal evidence. That means clients should be instructed not to edit, trim, or “clean up” recordings, and that any forensic work should follow accepted chain‑of‑custody protocols.

  • Candor and Avoiding Cherry‑Picking (ABA Model Rule 3.3, 4.1)
    Rule 3.3 requires candor toward the tribunal, and Rule 4.1 prohibits knowingly making false statements of fact. Lawyers should present digital evidence in context, avoiding selective clips that distort timing, perspective, or sound. A holistic, transparent approach builds credibility and protects both the client and the profession.

  • Respect for Privacy and Non‑Clients (ABA Model Rule 4.4 and related guidance)
    Rule 4.4 governs respect for the rights of third parties, including their privacy interests. When you obtain bystander footage or data from non‑clients, you should consider minimizing unnecessary exposure of their identities and, where feasible, seek consent or redact sensitive information.

FINAL THOUGHTS

Handled with these rules in mind, everyday tech can reduce factual ambiguity and support more just outcomes. Misused, it can undermine trust, compromise admissibility, and trigger disciplinary scrutiny. ⚖️

🧪🎧 TSL Labs Bonus Podcast: Open vs. Closed AI — The Hidden Liability Trap in Your Firm ⚖️🤖

Welcome to TSL Labs Podcast Experiment. 🧪🎧 In this special "Deep Dive" bonus episode, we strip away the hype surrounding Generative AI to expose a critical operational risk hiding in plain sight: the dangerous confusion between "Open" and "Closed" AI systems.

Featuring an engaging discussion between our Google Notebook AI hosts, this episode unpacks the "Swiss Army Knife vs. Scalpel" analogy that every managing partner needs to understand. We explore why the "Green Light" tools you pay for are fundamentally different from the "Red Light" public models your staff might be using—and why treating them the same could trigger an immediate breach of ABA Model Rule 5.3. From the "hidden crisis" of AI embedded in Microsoft 365 to the non-negotiable duty to supervise, this is the essential briefing for protecting client confidentiality in the age of algorithms.

In our conversation, we cover the following:

  • [00:00] – Introduction: The hidden danger of AI in law firms.

  • [01:00] – The "AI Gap": Why staff confuse efficiency with confidentiality.

  • [02:00] – The Green Light Zone: Defining secure, "Closed" AI systems (The Scalpel).

  • [03:45] – The Red Light Zone: Understanding "Open" Public LLMs (The Swiss Army Knife).

  • [04:45] – "Feeding the Beast": How public queries actively train the model for everyone else.

  • [05:45]The Duty to Supervise: ABA Model Rules 5.3 and 1.1[8] implications.

  • [07:00] – The Hidden Crisis: AI embedded in ubiquitous tools (Microsoft 365, Adobe, Zoom).

  • [09:00] – The Training Gap: Why digital natives assume all prompt boxes are safe.

  • [10:00] – Actionable Solutions: Auditing tools and the "Elevator vs. Private Room" analogy.

  • [12:00] – Hallucinations: Vendor liability vs. Professional negligence.

  • [14:00] – Conclusion: The final provocative thought on accidental breaches.

RESOURCES

Mentioned in the episode

Software & Cloud Services mentioned in the conversation

MTC: The Hidden Danger in Your Firm: Why We Must Teach the Difference Between “Open” and “Closed” AI!

Does your staff understand the difference between “free” and “paid” aI? Your license could depend on it!

I sit on an advisory board for a school that trains paralegals. We meet to discuss curriculum. We talk about the future of legal support. In a recent meeting, a presentation by a private legal research company caught my attention. It stopped me cold. The topic was Artificial Intelligence. The focus was on use and efficiency. But something critical was missing.

The lesson did not distinguish between public-facing and private tools. It treated AI as a monolith. This is a dangerous oversimplification. It is a liability waiting to happen.

We are in a new era of legal technology. It is exciting. It is also perilous. The peril comes from confusion. Specifically, the confusion between paid, closed-system legal research tools and public-facing generative AI.

Your paralegals, law clerks, and staff use these tools. They use them to draft emails. They use them to summarize depositions. Do they know where that data goes? Do you?

The Two Worlds of AI

There are two distinct worlds of AI in our profession.

First, there is the world of "Closed" AI. These are the tools we pay for - i.e., Lexis+/Protege, Westlaw Precision, Co-Counsel, Harvey, vLex Vincent, etc. These platforms are built for lawyers. They are walled gardens. You pay a premium for them. (Always check the terms and conditions of your providers.) That premium buys you more than just access. It buys you privacy. It buys you security. When you upload a case file to Westlaw, it stays there. The AI analyzes it. It does not learn from it for the public. It does not share your client’s secrets with the world. The data remains yours. The confidentiality is baked in.

Then, there is the world of "Open" or "Public" AI. This is ChatGPT. This is Perplexity. This is Claude. These tools are miraculous. But they are also voracious learners.

When you type a query into the free version of ChatGPT, you are not just asking a question. You are training the model. You are feeding the beast. If a paralegal types, "Draft a motion to dismiss for John Doe, who is accused of embezzlement at [Specific Company]," that information leaves your firm. It enters a public dataset. It is no longer confidential.

This is the distinction that was missing from the lesson plan. It is the distinction that could cost you your license.

The Duty to Supervise

Do you and your staff know when you can and can’t use free AI in your legal work?

You might be thinking, "I don't use ChatGPT for client work, so I'm safe." You are wrong.

You are not the only one doing the work. Your staff is doing the work. Your paralegals are doing the work.

Under the ABA Model Rules of Professional Conduct, you are responsible for them. Look at Rule 5.3. It covers "Responsibilities Regarding Nonlawyer Assistance." It is unambiguous. You must make reasonable efforts to ensure your staff's conduct is compatible with your professional obligations.

If your paralegal breaches confidentiality using AI, it is your breach. If your associate hallucinates a case citation using a public LLM, it is your hallucination.

This connects directly to Rule 1.1, Comment 8. This represents the duty of technology competence. You cannot supervise what you do not understand. You must understand the risks associated with relevant technology. Today, that means understanding how Large Language Models (LLMs) handle data.

The "Hidden AI" Problem

I have discussed this on The Tech-Savvy Lawyer.Page Podcast. We call it the "Hidden AI" crisis. AI is creeping into tools we use every day. It is in Adobe. It is in Zoom. It is in Microsoft 365.

Public-facing AI is useful. I use it. I love it for marketing. I use it for brainstorming generic topics. I use it to clean up non-confidential text. But I never trust it with a client's name. I never trust it with a very specific fact pattern.

A paid legal research tool is different. It is a scalpel. It is precise. It is sterile. A public chatbot is a Swiss Army knife found on the sidewalk. It might work. But you don't know where it's been.

The Training Gap

The advisory board meeting revealed a gap. Schools are teaching students how to use AI. They are teaching prompts. They are teaching speed. They are not emphasizing the where.

The "where" matters. Where does the data go?

We must close this gap in our own firms. You cannot assume your staff knows the difference. To a digital native, a text box is a text box. They see a prompt window in Westlaw. They see a prompt window in ChatGPT. They look the same. They act the same.

They are not the same.

One protects you. The other exposes you.

A Practical Solution

I have written about this in my blog posts regarding AI ethics. The solution is not to ban AI. That is impossible. It is also foolish. AI is a competitive advantage.

* Always check the terms of use in your agreements with private platforms to determine if your client confidential data and PII are protected.

The solution is policies and training.

  1. Audit Your Tools. Know what you have. Do you have an enterprise license for ChatGPT? If so, your data might be private. If not, assume it is public.

  2. Train on the "Why." Don't just say "No." Explain the mechanism. Explain that public AI learns from inputs. Use the analogy of a confidential conversation in a crowded elevator versus a private conference room.

  3. Define "Open" vs. "Closed." Create a visual guide. List your "Green Light" tools (Westlaw, Lexis, etc.). List your "Red Light" tools for client data (Free ChatGPT, personal Gmail, etc.).

  4. Supervise Output. Review the work. AI hallucinates. Even paid tools can make mistakes. Public tools make up cases entirely. We have all seen the headlines. Don't be the next headline.

The Expert Advantage

The line between “free” and “paid” ai could be a matter of keeping your bar license!

On The Tech-Savvy Lawyer.Page, I often say that technology should make us better lawyers, not lazier ones.

Using Lexis+/Protege, Westlaw Precision, Co-Counsel, Harvey, vLex Vincent, etc. is about leveraging a curated, verified database. It is about relying on authority. Using a public LLM for legal research is about rolling the dice.

Your license is hard-earned. Your reputation is priceless. Do not risk them on a free chatbot.

The lesson from the advisory board was clear. The schools are trying to keep up. But the technology moves faster than the curriculum. It is up to us. We are the supervisors. We are the gatekeepers.

Take time this week. Gather your team. Ask them what tools they use. You might be surprised. Then, teach them the difference. Show them the risks.

Be the tech-savvy lawyer your clients deserve. Be the supervisor the Rules require.

The tools are here to stay. Let’s use them effectively. Let’s use them ethically. Let’s use them safely.

MTC