Identity/biometrics/technology marketing and writing services
I generated this picture in Imagen 4 after reading an AI art prompt suggestion from Danie Wylie. (I have mentioned her before in the Bredemarket blog…twice.)
The AI exercise raises a question.
What if you are in the middle of an identity verification or authentication process, and only THEN discover that a fraudster is impersonating you at that very moment?
Jobseekers need to know their potential employer when something about a job opportunity doesn’t feel right. And there are ways to do that.
I’ve previously talked about how common sense can minimize the chances of being fooled by a deepfake.
But common sense can help prevent other types of fraud such as employment fraud, as noted by Rachel Lund, chief risk officer with Sandia Area Federal Credit Union.
“Trust your gut- if it feels off, it probably is.”
But can we trust Lund?
Let’s look at another tip of hers:
“Research the company: Google “[Company Name] + Scam” and see if anything comes up.”
Although you can use Bing. Google isn’t the only search engine out there.
So I entered “Sandia Area Federal Credit Union Scam” into Bing…and found out about its warnings about scams.
As far as Bing is concerned, Scandia Area Federal Credit Union is not a scammer itself.
But Bing (and Google) are old fashioned dinosaurs.
So I clicked on the tab for Copilot results. (ChatGPT isn’t the only generative AI tool out there.)
Well, it’s good to know that a regulated credit union isn’t a scammer.
But what about something with a slightly sleazier reputation…like stuffing envelopes?
OK, Copilot isn’t hot on envelope stuffing opportunities.
But what if we get personal?
TL;DR: “That’s not us.”
Know your business. Know your employer.
You are the CMO, marketing leader, or other leader at an identity, biometric, or technology firm.
You’ve made the decision to work with Bredemarket to create your content, proposal, or analysis.
You’ve gone to the https://bredemarket.com/cpa/ page and scheduled a “Free 30 minute content needs assessment” with me on my Calendly calendar. We will talk via Google Meet.
You’ve answered the preliminary questions I asked in the meeting request, including:
So…what now?
I will make it real simple. I will ask you a single simple question:
“Why?”
We have 30 minutes to chat, and at the end of that time you and I will jointly determine
See you soon.
It’s nearly impossible to battle a tidal wave.
CBS News recently reported on the attempts of Meta and others to remove advertisements for “nudify” apps from their platforms. The intent of these apps is to take pictures of existing people—for example, “Scarlett Johansson and Anne Hathaway”—and creating deepfake nudes based on the source material.
But the apps may present their purposes differently when applying for Apple App Store and Google Play Store approval.
“The problem with apps is that they have this dual-use front where they present on the app store as a fun way to face swap, but then they are marketing on Meta as their primary purpose being nudification. So when these apps come up for review on the Apple or Google store, they don’t necessarily have the wherewithal to ban them.”
And there’s another problem. While the apps are marketed to adult men, their users extend beyond that.
“CBS News’ 60 Minutes reported on the lack of age verification on one of the most popular sites using artificial intelligence to generate fake nude photos of real people.
“Despite visitors being told that they must be 18 or older to use the site…60 Minutes was able to immediately gain access to uploading photos once the user clicked “accept” on the age warning prompt, with no other age verification necessary.”
We’ve seen this so-called “age verification” before.
But if whack-a-mole fighting against deepfake generators won’t work, what will?
I don’t have the answer. Even common sense won’t help here.
(Not a video, but a still image from Imagen 4)
My Google Gemini account does not include access to Google’s new video generation tool Veo 3. But I’m learning about its capabilities from sources such as TIME magazine.
Which claims to be worried.
“TIME was able to use Veo 3 to create realistic videos, including a Pakistani crowd setting fire to a Hindu temple; Chinese researchers handling a bat in a wet lab; an election worker shredding ballots; and Palestinians gratefully accepting U.S. aid in Gaza. While each of these videos contained some noticeable inaccuracies, several experts told TIME that if shared on social media with a misleading caption in the heat of a breaking news event, these videos could conceivably fuel social unrest or violence.”
However, TIME notes that the ability to create fake videos has existed for years. So why worry now?
“Veo 3 videos can include dialogue, soundtracks and sound effects. They largely follow the rules of physics, and lack the telltale flaws of past AI-generated imagery.”
Some of this could be sensationalism. After all, simple text can communicate misinformation.
And you can use common sense to detect deepfakes…sometimes.
Then again, some of the Veo 3 deepfakes look pretty good. Take this example of Will Smith slapping down some pasta at Eminem’s restaurant. The first part of the short was generated with old technology, the last part with Veo 3.
Now I am certain that Google will attempt to put guardrails on Veo 3, as it has attempted to do with other products.
But what will happen if a guardrail-lacking Grok video generator is released?
Or if someone creates a non-SaaS video generator that a user can run on their own with all guardrails disabled?
In that case, deepfake detection technology will become even more critical.
Does your firm offer deepfake detection technology?
Do you want your prospects to know how your technology benefits them?
Here’s how Bredemarket can help you help your prospects: https://bredemarket.com/cpa/
I’m experimenting with more detailed prompts for generative AI.
If you haven’t noticed, I use a ton of AI-generated images in Bredemarket blog posts and social media posts. They primarily feature wildebeests, wombats, and iguanas, although sometimes they feature other things.
My prompts for these images are usually fairly short, no more than two sentences.
But when I saw some examples of prompts written by Danie Wylie—yes, the same Danie Wylie who wrote the Facebook post earlier this year at the https://m.facebook.com/story.php?story_fbid=pfbid0nvmhyuLpn3jwMv8K8sbK5EXfS4kcpjfWHicgj4BJhdFLMme87P5fvPSYf9CwjRH7l&id=100001380243595&mibextid=wwXIfr URL—then I realized that I could include a lot more detail in my own image prompts.
If you read Wylie’s Facebook post, or my own subsequent post at the https://bredemarket.com/2025/06/03/when-hivellm-pitches-an-anti-fraud-professional/ URL, then you know exactly what the picture depicts.
Plus some other stuff buried in the details.
By the way, here is my prompt, which Google Gemini (Imagen 4) stored as “Eerie Scene: Sara’s Fake Bills.”
“Draw a realistic picture of a ghost-like woman wearing a t-shirt with the name “Sara.” She is holding out a large stack of dollar bills that is obviously fake because the picture on the bill is a picture of a clown with orange face makeup wearing a blue suit and a red tie. Next to Sara is a dead tree with a beehive hanging from it. Bees buzz around the beehive. A laptop with the word “HiveLLM” on the screen sits on the rocky ground beneath the tree. It is night time, and the full moon casts an eerie glow over the landscape.”
I didn’t get exactly what I wanted—the bills are two-faced—but close enough. And the accident of two-faced bills is a GOOD thing.
How detailed are your picture prompts?
(Part of the biometric product marketing expert series)
Now that I’ve dispensed with the first paragraph of Google’s page on the Monk Skin Tone Scale, let’s look at the meat of the page.
I believe we all agree on the problem: the need to measure the accuracy of facial analysis and facial recognition algorithms for different populations. For purposes of this post we will concentrate on a proxy for race, a person’s skin tone.
Why skin tone? Because we have hypothesized (I believe correctly) that the performance of facial algorithms is influenced by the skin tone of the person, not by whether or not they are Asian or Latino or whatever. Don’t forget that the designated races have a variety of skin tones within them.
But how many skin tones should one use?
The beauty industry has identified over 40 different skin tones for makeup, but this granular of an approach would overwhelm a machine learning evaluation:
[L]arger scales like these can be challenging for ML use cases, because of the difficulty of applying that many tones consistently across a wide variety of content, while maintaining statistical significance in evaluations. For example, it can become difficult for human annotators to differentiate subtle variation in skin tone in images captured in poor lighting conditions.
The first attempt at categorizing skin tones was the Fitzpatrick system.
To date, the de-facto tech industry standard for categorizing skin tone has been the 6-point Fitzpatrick Scale. Developed in 1975 by Harvard dermatologist Thomas Fitzpatrick, the Fitzpatrick Scale was originally designed to assess UV sensitivity of different skin types for dermatological purposes.
However, using this skin tone scale led to….(drumroll)…bias.
[T]he scale skews towards lighter tones, which tend to be more UV-sensitive. While this scale may work for dermatological use cases, relying on the Fitzpatrick Scale for ML development has resulted in unintended bias that excludes darker tones.
Enter Dr. Ellis Monk, whose biography could be ripped from today’s headlines.
Dr. Ellis Monk—an Associate Professor of Sociology at Harvard University whose research focuses on social inequalities with respect to race and ethnicity—set out to address these biases.
If you’re still reading this and haven’t collapsed in a rage of fury, here’s what Dr. Monk did.
Dr. Monk’s research resulted in the Monk Skin Tone (MST) Scale—a more inclusive 10-tone scale explicitly designed to represent a broader range of communities. The MST Scale is used by the National Institute of Health (NIH) and the University of Chicago’s National Opinion Research Center, and is now available to the entire ML community.
According to Biometric Update, iBeta has developed a demographic bias test based upon ISO/IEC 19795-10, which itself incorporates the Monk Skin Tone Scale.
At least for now. Biometric Update notes that other skin tone measurements are under developoment, including the “Colorimetric Skin Tone (CST)” and INESC TEC/Fraunhofer Institute research that uses “ethnicity labels as a continuous variable instead of a discrete value.”
But will there be enough data for variable 8.675309?
(Part of the biometric product marketing expert series)
A recent story about Meta face licensing changes caused me to get reflective.
“This openness to facial recognition could signal a turning point that could affect the biometric industry.
“The so-called “big” biometric players such as IDEMIA, NEC, and Thales are teeny tiny compared to companies like Meta, Alphabet, and Amazon. If the big tech players ever consented to enter the law enforcement and surveillance market in a big way, they could put IDEMIA, NEC, and Thales out of business.
“However, wholesale entry into law enforcement/surveillance could damage their consumer business, so the big tech companies have intentionally refused to get involved – or if they have gotten involved, they have kept their involvement a deep dark secret.”
Then I thought about the “Really Big Bunch” product that offered the greatest threat to the “Big 3” (IDEMIA, NEC, and Thales)—Amazon Rekognition, which directly competed in Washington County, Oregon until Amazon imposed a one-year moratorium on police use of facial recognition in June 2020. The moratorium was subsequently extended until further notice.
I last looked at Rekognition in June 2024, when Amazon teamed up with HID Global and may have teamed up with the FBI.
So what’s going on now?
Hard to say. I have been unable to find any newly announced Amazon Rekognition law enforcement customers.
That doesn’t mean that nothing is happening. Perhaps the government buyers are keeping their mouths shut.
Plus, there is this page, “Use cases that involve public safety.”
Nothing controversial on the page itself:
Nothing controversial at all, and I am…um…99% certain (geddit?) that IDEMIA, NEC, and Thales would endorse all these points.
But why does Amazon even need such a page, if Rekognition is only used to find missing children?
Maybe this is a pre-June 2020 page that Amazon forgot to take down.
Or maybe not.
Couple this with the news about Meta, and there’s the possibility that the Really Big Bunch may enter the markets currently dominated by the Big Three.
Imagine if the DHS HART system, delayed for years, were resurrected…with Alphabet or Amazon or Meta technology.
We are still in the time of uncertainty…and may never go back.
(Large and small wildebeests via Imagen 3)
Another post that probably won’t go on the socials, but that explains one of the key “whys” about Bredemarket.
If you haven’t noticed, there are a large number of people who lost full-time employment and years later have not regained it.
Some are getting by with part-time work or consulting. Others are draining their savings. Others are homeless.
The toxic positivists are fond of saying that you are one yes away, and that your job will come.
But what if it doesn’t come?
And for some it doesn’t.
Google Gemini summarized the findings at “Labor Force Characteristics (CPS) : U.S. Bureau of Labor Statistics”: https://www.bls.gov/cps/lfcharacteristics.htm
“A Bureau of Labor Statistics survey in January 2024 found that 65.7% of long-tenured workers (those with at least 3 years on the job) displaced between 2021 and 2023 had been re-employed.
“Re-employment rates vary by age. In January 2024, the rate was 74.5% for those aged 25-54, but significantly lower for older workers (55-64: 55.3%; 65 and over: 34.4%).”
In short, if you’re over 55 and lose your job, there’s a good chance that you’re not getting another one.
Having only enjoyed full-time employment for one year out of the last five, I realize that I may never work again, even though I am years away from retirement age.
Bredemarket started during my first bout of unemployment between 2020 and 2022, when I pursued a two-pronged approach of consulting and searching for full-time employment.
In 2023 I found myself pursuing the two-pronged approach again.
As I say, we’ll see what happens.
Technology marketers, do your prospects know who you are?
If they don’t, then your competitors are taking your rightful revenue.
Don’t let your competitors steal your money.
Before I tell you how Bredemarket can solve your technology company’s awareness problem, let me spill the secret of why I’m asking the question in the first place.
Normally I don’t let non-person entities write Bredemarket content, but today I’m making an exception.
My usual generative AI tool is Google Gemini, so I sent this prompt:
“What are the five most important types of marketing content to create for a technology software company?”
A little secret: if you want generative AI to supply you with 3 things, ask for more than that. Some of the responses will suck, but maybe the related ones are insightful.
In this case I only wanted ONE type of marketing content, but I reserve the right to “co-author” four more posts based upon the other responses.
Of the 5 responses from Google Gemini, this was the first:
“In-depth Problem-Solving Content (Think Blog Posts, White Papers, Ebooks): Your potential customers are likely facing specific challenges. Content that dives deep into those problems and offers insightful solutions (even if it doesn’t directly pitch your product) builds trust and positions you as a thought leader. Think “The Ultimate Guide to [Industry Challenge]” or a white paper on “Navigating [Complex Technical Issue].””
Now you see where I got the idea for the title of this post. Normally I shy away from bombastic words like “ultimate,” but this sage is going a little wild.
So the bot tells me that the most important type of marketing content for a technology software company is short-form or long-form problem-solving content.
Let’s get a little meta (small m) here.
If your prospects don’t know who you are, create customer-focused content that explains how your company can solve their problems.
Now let’s get meta meta.
If you need help creating this content, whether it’s blog posts, articles, white papers, case studies, proposals, or something else, Bredemarket can help you solve your problem.
Let’s talk about your problem and how we can work together to solve it. Book a free meeting via the https://bredemarket.com/cpa/ URL.
(All AI illustrations from Imagen 3 via Google Gemini, of course)
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