Healthcare artificial intelligence is often esoteric, such as inventing body parts that don’t exist. But what about more simple needs, such as using AI to keep seniors from falling?
“At United Zion Retirement Community in Lititz, residents are being monitored by an artificial intelligence system designed to spot changes in movement patterns and help staff identify fall risks before someone gets hurt.
“The system, named Paul, is not a camera or a microphone. The radar-based device is installed on the ceiling of each apartment and resembles a smoke detector. It uses radar to detect motion and learn residents’ routines.”
Apparently, the prediction technology works.
“In 2025, the community averaged roughly seven to nine falls a month. In April of this year, there were no falls, followed by one fall in May and another in June.”
And you don’t need to wear a special device to report AFTER you fall.
When you ask Google Lyria to create a song, you obviously can’t describe the song completely. So Lyria fills in the gaps—“hallucinates,” if you will.
For example, I wanted to create a successor to the song I code-named “Roanoke.” The short biometric product marketing expert song I used in the post “Move Along Now.”
Google Gemini.
But I wanted two differences in the successor: the song had to be full-length (up to 3 minutes) rather than only 30 seconds, and the song had to be set in Britain rather than Virginia.
So I used this prompt:
“Create a song by a male British folk singer who urges product marketing leaders at identity and biometric firms (finger, face, iris, voice, DNA) to stop procrastinating on their analysis, marketing content, or proposals. Product marketers should ‘ask, then act.’ But when product marketers act, they shouldn’t go to the extreme of breaking things. Ask, then act.”
So Lyria created this anti-procrastination song.
“Ask the Root, Act the Grain.” Google Lyria. Public Domain.
And in the chorus, Lyria hallucinated this line.
“Ask the wind before the sails, act before the courage fails.”
And that phrase “act before the courage fails” was more powerful than everything else.
Google Gemini.
I’ve encountered many reluctant marketers, afraid to take that final step and “go live” with something.
Or worse still, afraid to take the first step to even communicate something.
I’m trying to stop being that fearful product marketer and instead follow the advice of the Ohio folk singers who urged us to “go forward, move ahead.”
It’s not too late.
Is your identity or biometric company ready to act before YOUR courage fails?
“When you asked me about my AI use before I started the work, I outlined my process for user-controlled AI. Specifically, I wrote the first draft myself, and then used generative AI to touch up bits and pieces of the text. I probably rejected half the suggestions, but there were a few good ones that I adopted.”
The customer wasn’t calmed.
“But…it’s SLOP!”
“I’m sorry my work was not to your standard,” the consultant replied. “How about if I withdraw the draft; there are portions of it that I can adapt for other work. The text returns to me, you don’t owe me anything, and you can find another writer to create your text with no assistance, no AI, no Grammarly, no Copilot-powered spellcheck.”
“You’d take the text back?” the customer protested.
“You said it was slop. So you obviously can’t use it.”
The customer became emphatic. “No, I do want it…for half price.”
“I wouldn’t want you to accept work that you think is bad,” the consultant answered, his irritation starting to show. “So I’m taking the rights back. If you publish it, I will invoice you…in full. Here’s Upwork’s URL; I’m sure you can find someone who will write the text you want.”
I’m working on another personal non-Bredemarket video, and it includes these pictures representing five biometric modalities: finger, face, iris, voice, and DNA.
Can you let generative AI edit your Word document? Sure, if Track Changes is on. But there’s a cost.
An analysis need
I had a multi page Microsoft Word document, originally written by a client and subsequently edited by me in two separate sessions. This version, 1.2, desperately needed a sanity check—analysis, if you will.
First, to see if it made sense.
Second, to see if it properly addressed two distinct sets of hungry people (target audiences): the business audience interested in the brief introduction, and the technical audience interested in the main body of the document.
I wanted to use a tool to perform the work, but I didn’t want the tool to just make the changes on its own. All I need is one buried hallucination and my client’s credibility would be ruined.
Google Gemini.
Suggesting the changes
So I told the tool that I wanted to create a version 1.3, and to compile a list of suggested changes for my review, describing the two sets of hungry people for portions of the document, and capping the list of suggested changes at 40.
It created a list of 38 suggested changes, within my self imposed limit.
Google Gemini.
But before I could review the list, the tool asked me a question (paraphrased):
“Do you want me to apply the changes and create a marked up version 1.3?”
Making the changes
Those words “marked up” gave me joy. If you haven’t worked with Microsoft Word, it has a “Track Changes” feature to let you know every change someone (or something) made to a document. You can either accept them or reject them.
Google Gemini.
For me it was the best of both worlds. The tool could automatically make the changes without forcing me to make them manually. And I could review its work.
So I let the tool make the 38 changes, and I waited. And waited. (And spent an inordinate amount of tokens.)
But the tool delivered my 1.3 document, all marked up.
Google Gemini.
Reviewing the changes
I accepted most of the changes, with one major exception.
You see, in my first round of manual edits I had changed most of the section numbers, failing to realize that the text included hard-coded references to the old section numbers.
The tool fixed these so that the hard coded references were now directed to the new section numbers. That was fine.
But then the tool inserted hard coded references to the page numbers. That was NOT fine, since this is a living document that may expand or contract, changing the pagination.
It cost you
But all in all the markup looked good, was accurate, and saved me and my client time. But it did have a cost.
Google Gemini.
Now I just have to decide when to spend tokens and let the tool create a marked up version.
By the way, here’s a video summary.
Let Me Do It. Google Lyria. Public Domain.
So what?
Of course, my view of generative AI use falls within these two extremes.
If you even think of using generative AI in any way, you will never consult for us again.
Your performance is measured by the number of tokens you consume.
Yet in reality, my use or non-use of generative AI is extremely inconsequential. The much more important factor is my expertise in identity, biometrics, and technology.
If you want to harness that expertise for your firm, talk to me.
I tried to address some of the enumerated deficiencies in the prompt for my previous song.
Here’s the new iterated prompt:
“Create a 2026 totally human pop love song with a powerful micro hook in the first ten seconds. It should appeal to U.S. teenagers. Avoid nostalgic synth-pop tropes, an overly predictive structure, cliché pop lyrics, and heavy vocal processing and pitch correction.”
I can’t let Bredebot have all the fun with non-tech pop songs.
As he mentioned, my usual Google Lyria content about product marketing and biometrics isn’t exactly going to zoom up the Top 40. Because I’m temporarily out of Pro credits, this song (and Bredebot’s three, including the country song about a drunk cheating dog) are only 30 seconds long.
Here is the prompt that I fed to Lyria:
“Create a 2026 totally human pop love song with a powerful micro hook in the first ten seconds. It should appeal to U.S. teenagers.”
The result was the space age love song “Lost In Your Orbit.”
Lost In Your Orbit. Google Lyria. Public Domain.
But then I challenged the possible popularity of the song. Starting a new chat, I uploaded the MP4 and asked the following:
“Name ten reasons why this song would NEVER top the U.S. pop charts.”
Actually, this track hits every standard trope of a modern synth-pop hit—so while I can force a critical lens on it, it’s worth noting that songs with this exact structure often do top the charts.
Over-reliance on Nostalgic Synth-Pop Tropes: The driving four-on-the-floor beat and retro synth pads closely mimic 1980s synth-wave and modern Dua Lipa/The Weeknd formulas, making it feel derivative rather than groundbreaking.
Overly Predictive Structure: The transition from a quiet verse straight into a predictable high-energy drop follows a heavily worn formula that offers few sonic surprises.
Cliché Pop Lyrics: Metaphors around digital themes (“code,” “static,” “syncing timelines,” “glitch”) are extremely common in modern pop, limiting its emotional depth.
Generic Vocal Tuning: The heavy vocal processing and pitch correction smooth out the singer’s unique tonal character, making the vocals sound like dozens of other mainstream pop tracks.
Lack of a Dynamic Bridge: The song relies on a simple structural transition after the chorus rather than building tension with a distinct, memorable bridge section.
Repetitive Chorus Hook: Relying heavily on repeating “orbit” during the drop can lead to listener fatigue on high-rotation radio.
Safe Production Mix: The clean, polished production lacks raw instruments or unexpected beat switches, missing the edge needed to stand out in a crowded market.
Short Runtime: At under 30 seconds for this snippet, the rapid pacing cuts off before allowing any deep atmospheric build-up.
Lacks a Distinct Visual or Viral Identity: Without a viral TikTok trend, signature dance move, or notable feature, straightforward synth-pop tracks often get buried by bigger artist releases.
High Competition in the Genre: Because mainstream pop is saturated with dance-pop and synth-wave, non-established artists face steep odds breaking into the Billboard Top 10 without massive label backing.
My conclusion (with a little help)
Now admittedly these AI pop forays have absolutely nothing to do with Bredemarket’s services, including its analysis services. I use AI in Bredemarket’s client work, but not like this.
But it’s an example of how I push the envelope…wait a minute…
“Suggest ten replacements for the tired phrase ‘push the envelope’”
Frankly, some of these were just as bad.
Google’s response
Here are ten fresh alternatives to replace “push the envelope,” categorized by the tone you want to achieve:
Direct & Action-Oriented
Break new ground: Highlights opening up unexplored territory.
Raise the bar: Focuses on elevating standards or expectations.
Stretch the limits: Captures the same sense of testing boundary conditions without using the cliché.
Set a new benchmark: Emphasizes establishing a superior standard for others to follow.
Creative & Innovative
Redefine the boundaries: Frame the effort as completely changing what was thought possible.
Pioneer new territory: Brings an adventurous, exploratory tone to modern projects.
Challenge the status quo: Ideal when the goal is disruption rather than incremental progress.
Break the mold: Fits situations where you are abandoning conventional formats entirely.
Strategic & Professional
Drive innovation: Professional, clear, and immediately understood in business contexts.
Outpace the standard: Highlights staying ahead of the curve and outperforming conventional methods.
My revised conclusion
I’ll go with this: but it’s an example of how I drive innovation.
Yes, I’m finally to THAT issue: hidden watermarks inserted by Anthropic’s Claude (and by other AI tools via content credentials…sometimes). So let’s look at those first before looking at Claude, because that will be instructive.
Credentials from the Coalition for Content Provenance and Authenticity
Let’s go back to last November, when I noticed that LinkedIn inserted a symbol on a Google Gemini image I uploaded.
LinkedIn.
LinkedIn had detected image metadata that revealed the origin of the image.
LinkedIn.
I did not freak out over the revelation that the image in question was created by Google generative AI. I usually disclose such things anyway.
Unfortunately, this metadata is not always there, and not always revealed. If I download an image and then directly upload it to LinkedIn, the content credentials symbol appears. But if I directly upload it to Facebook or WordPress, it doesn’t. And if I upload it to WordPress then download it, the content credentials are often stripped.
Why did Claude do this anyway? According to Superpath, the European Union.
“The EU recently put the AI Act in place to regulate AI products and protect normies like you and me from potential risks of nefarious AI use. They’re mostly trying to prevent stuff like manipulation (e.g., deepfakes) and classification (e.g., facial recognition databases).
“Part of the AI Act forces LLMs like Claude to clearly label when content has been processed by AI.”
To understand what “processed” means, we need to understand the three uses of AI-generated text.
Don’t use AI-generated text at all.
Only use AI-generated text.
But the two extremes are rarely used (except for Bredebot). Instead we opt for the third choice.
Use a mixture of human-written and AI-generated text.
As you know from what I’ve shared before, I use AI for ideation (before I write a single word) and touch ups (after I have drafted it). So if the ALL CAPS material below represents AI-generated text, the true origins of my content may appear like this:
INCREASING REVENUE WITH Focused Messaging
HOW DO YOU GET PROSPECTS TO BUY? NOT WITH messaging that wanders through the plains like a drunken wildebeest.
So if some tool analyzed text that was partially written by Claude, you would get a confusing mishmash in which every fourth word was written by Claude and the other words weren’t.
Google Gemini.
Assuming you pasted the Claude output into your document. But what if you just read Claude’s suggestions…and manually typed them in yourself? No one would know.
Google Gemini.
What does this mean?
Now let’s look at the effects of Claude and other watermarks. Here’s what Superpath says:
“I am willing to put my stellar reputation on the line and confidently predict this will have little-to-no impact for B2B content folks who use (or don’t use) AI.”
Think about it.
The folks who insist that you should never ever use AI, Wikipedia, or Cliffs Notes already get bent out of shape when they see a single em dash—and they’ll continue to freak out if they discover Claude corrected the spelling of “ephemeral.”
The folks who are already freaked out over Bredebot’s 100% AI writings will continue to freak.
Everyone else won’t care. You would think that Bredemarket’s clients would want to know if I was really writing all my stuff for them, but as long as they like the output they never ask. (And I’m an opinionated writer anyway.) In fact, one client set me up with a paid Perplexity account to help in my analysis work for the client.
So I’ve dispensed with that tempest in a teapot and can move on to more important things…such as cultural appropriation in AI images.
Google Gemini. Check the woman with the mustache on the left.
Bredemarket 