Twenty years ago, a forensic report about a hard drive was mostly an argument about whether a file existed and when it was last touched. And of course, trying to recover deleted material. Today the same report might need to address whether a video is real, whether a document was generated by a language model, whether a “deleted” text message ever really existed on the device in the first place, and especially, whether the tool used to answer any of those questions is itself reliable enough to stand behind in front of a jury.

It doesn’t come up in every case, but when it does, we’d better be ready to answer. Digital forensics has always rested on the idea that a method can be explained, tested, and challenged — that’s pretty much the whole premise behind Daubert and Frye. AI-assisted analysis complicates that premise, because a growing number of detection and authentication tools now involve models whose internal reasoning isn’t fully visible even to the people who built them. Courts are already grappling with what that means for the right to confront the basis of evidence against you, and there isn’t yet a settled answer For instance, I’ve seen questions about whether Cellebrite might mis‑label a recovered file as‘deleted’ or treat an active file as if ithad been deleted, even though the platform is historically solid and time‑tested in most other respects. Still, that’s not a hypothetical academic question; it’s a live one working its way through appellate opinions right now and it’s going to shape how expert reports get written well into the future.

What’s changing on the ground, in the meantime, is the volume and variety of source data an expert has to account for. A phone used to mean call logs and texts. Now it means cloud-synced photo libraries, health data, smart-home integration logs, location history from a dozen apps that nobody remembers granting permission to (or maybe that an update changed the permissions you did or did not grant, and metadata trails that span devices the owner may not even still possess. The expert’s job isn’t just extraction anymore — it’s building a coherent, defensible narrative out of data that lives in more places than any one device.

The next several years will bring a few concrete shifts. Although there will certainly be changing laws for changing environments, standards bodies and courts will move, slowly and , toward requiring more explicit validation testimony for AI-assisted tools. Not just “the software said so,” but documented error rates, testing methodology, and version-specific behavior, the same rigor that’s long been expected of DNA analysis and toxicology. Authentication of video and audio is going to become its own specialized sub-field, distinct from general digital forensics, the

way arson investigation split off from general fire science. And attorneys are going to need to get comfortable asking experts pointed questions about tool provenance — not because they distrust the expert, but because opposing counsel increasingly will.

None of this replaces the fundamentals. A well-documented chain of custody still matters. So does a methodology that can be explained in plain English to twelve people, a judge, and possibly an attorney who’ve never heard of a hash value, and an expert willing to say plainly what the evidence does and doesn’t show — that hasn’t changed and I don’t expect it to. What’s changing is the amount of homework required to get there, and how much of that homework now involves tools that didn’t exist five years ago.I’d like to makethis the first in a short series looking at where this field is actually headed, drawing on conversations with people building the tools and writing the standards rather than just my own two cents.

If there’s a specific angle—AI detection reliability, Confrontation Clause questions, how courts are handling deepfake authentication—you’d like covered first, I’m glad to hear it. Trial lawyers and judges who live with these issues every day are exactly who I’m hoping to hear from, so please let me know.

Steve Burgess is a digital forensics expert witness with more than 40 years of experience and over 20,000 devices and digital media examined. He is the principal of Burgess Forensics, founded in 1984.

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AI and Elder Abuse, copyright 20025, Steve Burgess

The news is full of AI (Artificial Intelligence) stories. How will it empower us in our jobs? Whose job will it take next? Is it creating actual fake news? 

While there’s a lot of “we’ll see” in the answers to these questions, one immediate and quite pressing issue is how AI is contributing to Elder Abuse. Elder abuse is an action(s) in any relationship where there is an expectation of trust that causes harm or distress to an older person.

American elders were conned out of more than three $3 billion dollars in 2023 in a range of financial crimes, according to the FBI data. AI can make these scammers seem more believable partially because these programs help with content creation and cleaning up human error that might otherwise warn us we’re being served up something fraudulent.

Already, there are so many scams via email, websites, phone calls, advertisements, and offers of romance that there’s plenty to worry about. But does the emergence of AI in everyday life and writing supercharge these efforts to relieve the older amongst us of their carefully husbanded and/or limited resources?

Already, individuals are reaching through our computers and phones to lighten our wallets and bank accounts. There are websites that look like our bank sites, phishing emails that look like they’re from someone or from an institution that we know and trust, ads galore that tempt the reader with promised services, goods, or fortunes.

Already, we give away so much of our privacy in return for the freedom to browse the web and to use other online services. We also regularly share our private information, favorite colors, cars, dates and faces on publicly available social media. But now, there are tools in the guise of fun apps that offer to clean up our photos, or ones to let us have our own voices sing our favorite songs perfectly, our own tin ears notwithstanding.

I see ads every day inviting me to seamlessly insert my voice instead of the original voice – say Sting’s or Sinatra’s, into a popular song. Like karaoke on steroids that we can save and play for or send to others. It’s likely to be fun, but then your voice is being stored in records you have no control over. Thousands of people’s voices are thereby being harvested and stored by some company you don’t know, that has a privacy policy that most of us never read through, and which can be used by these unknown persons in any which way. 

Even if the company offering these services is completely on the up and up, they are a prime target to be hacked by those who would love to use these stored audio clips to clone your voice into realistic but invented audio sent to you via email, or even a phone call.

So what happens when you hear from a beloved grandchild – in their own voices – that they are suffering, or need help out of a jam? And what if you, as a parent, grandparent, or even just a friend, hears from another trusted friend or loved one that they have “such a deal?”

Why, for the cost of nothing at all, you can use chat GPT right now to create a picture of you standing next to the President or your favorite rock star. Some generative AI tools can even create  a video of the two of you singing 70’s rock anthems together.

But nearly as easily, a bad actor could create a picture or audio of your child or friend, needing bail, stuck without airfare far away, injured, in a foreign prison cell, or in the hands of dangerous thugs, begging for your help. 

As technology advances in leaps and bounds, human nature stays much the same. There’s always somebody out to take advantage of the system ,and of you, while we remain always sympathetic to those we care about. The game hasn’t changed – just the tools of the game, and the ease with which the unscrupulous can run their scams on a wider swath of folks. And the tools are ever more easily and cheaply accessible. 

So, what to do?

There are simple steps to make it harder for unscrupulous folks to take advantage. First of all, educate yourself and your elder relations and loved ones about the risks. There’s no need to get paranoid about it – just to take some practical steps.

• DO enable two-factor authentication (2FA) , one of the most important, but simple security practices. 
• DON’T share passwords. (There are a few exceptions for the elderly or ill.)
• DON’T use dictionary words or favorite colors, cars, kids, or teams as your passwords.
• If passwords are hard to remember, DO use password managers, such as NordPass, Dashlane, 1Password, or Last Pass.
• DON’T give away your voice to be recorded by those you don’t know, no matter how much fun it looks like.
• DON’T click on links in emails or texts, especially from financial institutions. Rather, use your browser and type in the website of the institution. Most offer apps for direct access that are generally safe.
• DO look for odd misspellings or extra words in email addresses and domains. Website domains don’t have typos. For instance Welsfargo.com is not Wellsfargo.com (it’s missing an “l.”). Applepayments.com is not Apple.com/payments.
• DON’T open attachments to emails or texts if you’re not sure or don’t know who the sender is.

Modern tech and the Internet make so many things available for us and in many cases, easier for us. While there are always bad actors, and while AI tools make it easier for those bad actors to fool us, some sensible practices make it more difficult for those bad actors to fleece us of our hard-earned resources

Checking up on our elders and educating them about some of these simple steps can make them and you safer, help you both sleep at night, and even bring you a little bit closer, and after all, what could be better than that?

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