Tag Archives: facial recognition

Communicate with the Words of Authority

Biometric marketing leaders, do your firm’s product marketing publications require the words of authority?

John E. Bredehoft of Bredemarket, the biometric product marketing expert.

Can John E. Bredehoft of Bredemarket—the biometric product marketing expert—contribute words of authority to your content, proposal, and analysis materials?

I offer:

  • 30 years of biometric experience, 10 years of product marketing expertise, and complementary proposal and product management talents.
  • Success with numerous biometric firms, including Incode, IDEMIA, MorphoTrak, Motorola, Printrak, and over a dozen biometric consulting clients.
  • Mastery of multiple biometric modalities: friction ridge (fingerprint, palm print), face, iris, voice, DNA.
  • Compelling CONTENT creation: blog posts, case studies and testimonials, LinkedIn articles and posts, white papers.
  • Winning PROPOSAL development: managing, writing, editing for millions of dollars of business for my firms.
  • Actionable ANALYSIS: strategic, market, product, competitive.

To embed Bredemarket’s biometric product marketing expertise within your firm, schedule a free meeting with me.

Make an impact.

Amazon’s Take on “Familiar Faces” is Not Available Everywhere

(Part of the biometric product marketing expert series)

Biometric Update reports that Amazon’s Ring products are offering a feature called “Familiar Faces.”

“In September, Amazon revealed a revamped Ring camera lineup featuring two notable AI features, Familiar Faces and Search Party. Familiar Faces uses facial recognition and lets users tag neighbors or friends so future alerts identify them by name rather than generic motion.”

If this sounds, um, familiar, it’s because Google also has a similar feature, called familiar face alerts, in its Nest offerings.

And like Google, Amazon’s Familiar Faces won’t be available to everyone. If you are, um, familiar withg the acronym BIPA, you will know why.

“The feature is slated for December, though it will be disabled in places with stricter biometric laws such as Illinois, Texas, and Portland.”

Differentiating the DNA of Twins?

(Part of the biometric product marketing expert series)

There are certain assumptions that you make in biometrics.

Namely, that certain biometrics are unable to differentiate twins: facial recognition, and DNA analysis.

Now as facial recognition algorithms get bettter and better, perhaps they will be able to tell twins apart: even identical twins.

But DNA is DNA, right?

Twins and somatic mutations

Mike Bowers (CSIDDS) links to an article in Forensic Magazine which suggests that twins’ DNA can be differentiated.

For the first time in the U.S., an identical twin has been convicted of a crime based on DNA analysis.

The breakthrough came from Parabon Nanolabs, who’s scientists used deep whole genome sequencing to identify extremely rare “somatic mutations” that differentiated Russell Marubbio and his twin, John. The results were admitted as evidence in court, making last week’s conviction of Russell in the 1987 rape of a 50-year-old woman a landmark case.

Twin DNA.

Parabon Nanolabs (whom I briefly mentioned in 2024) applied somatic mutations as follows:

Somatic mutations are DNA changes that happen after conception and can cause genetic differences between otherwise identical twins. These mutations can arise during the earliest stages of embryonic development, affecting the split of the zygote, and accumulate throughout life due to errors in cell division. Somatic mutations can be present in only one twin, a subset of cells, or both, potentially leading to differences in health and even developmental disorders—and in this case, DNA.

The science behind somatic mutations is not new, and is well-researched, understood and accepted. It’s just uncommon for DNA to lead to twins, and even more uncommon for somatic mutations to be able to distinguish between twins.

Note that “well-researched, understood and accepted” part (even though it lacks an Oxford comma). Because this isn’t the only recent story that touches upon whole genome sequencing.

Whole genome sequencing and legal admissibility

Bowers also links to a CNN article which references Daubert/Frye-like questions about whether evidence is admissable.

Evidence derived from cutting-edge DNA technology that prosecutors say points directly at Rex Heuermann being the Gilgo Beach serial killer will be admissible at his trial, a Suffolk County judge ruled Wednesday….

Heuermann’s defense attorney Michael Brown had argued the DNA technology, known as whole genome sequencing, has not yet been widely accepted by the scientific community and therefore shouldn’t be permitted. He said he plans to argue the validity of the technology before a jury.

Meanwhile, prosecutors have argued this type of DNA extraction has been used by local law enforcement, the FBI and even defense attorneys elsewhere in the country, according to court records.

Let me point out one important detail: the fact that police agencies are using a particular technology doesn’t mean that said technology is “widely accepted by the scientific community.” I suspect that this same question will be raised in other courts, and other judges may hold a different decision.

And after checking my blog, I realize that I have never written an article about Daubert/Frye. Another assignment for Bredebot, I guess…

Your identity/biometric product marketing needs to assert the facts rather than old lies,

Bredemarket can help.

Stop losing prospects! Use Bredemarket content for tech marketers

Forget About Milwaukee’s Facial Recognition DATA: We All Want to See Milwaukee’s Facial Recognition POLICY

(Part of the biometric product marketing expert series)

I love how Biometric Update bundles a bunch of stories into a single post. Chris Burt outdid himself on Wednesday, covering a slew of stories regarding use and possible misuse of facial recognition by Texas bounty hunters, the NYPD, and cities ranging from Chicago, Illinois to Houlton, Maine.

But those stories aren’t the ones that I’m focusing on. Before I get to my focus, I want to go off on a tangent and address something else.

Read us any rule, we’ll break it

In a huddle space in an office, a smiling robot named Bredebot places his robotic arms on a wildebeest and a wombat, encouraging them to collaborate on a product marketing initiative.
Bredebot and his pals.

By the time you read this, the first full post by my counterpart “Bredebot” will have published on the Bredemarket blog. This is a completely AI-generated post in which a bot DID write the first draft. More posts are coming.

What I didn’t expect was that competition would arise between me and my bot. I’m writing these words on August 27, two days before the first Bredebot post appears, and I’m already feeling the heat.

What if Bredebot’s posts receive more traffic than the ones I write myself? What does that mean for my own posts…and for the whole premise of hiring Bredemarket to write for others?

I’m treating this as a challenge, vowing to outdo my fast bot counterpart.

And in that spirit, let’s revisit Milwaukee.

Give us any chance, we’ll take it

Access.

When Biometric Update initially visited Milwaukee in its April 28 post, the main concern was the possible agreement for the Milwaukee Police Department to provide “access” to facial data to the company Biometrica in exchange for facial recognition licenses. I subsequently explored the data issue in my own May 6 guest post for Biometric Update.

Vendors must disclose responsible uses of biometric data.

But today the questions addressed to Milwaukee don’t focus on the data, but on the use of facial recognition itself. The Biometric Update article links to a Wisconsin Watch article with more detail. The arguments are familiar to all of you: facial recognition is racist, facial recognition is sometimes relied upon as the sole piece of evidence, facial recognition data can be sent to ICE, and facial recognition can be misused.

However, before Milwaukee’s Common Council can approve facial recognition use, one requirement has to be met.

“Since the passage of Wisconsin Act 12, the only official way to amend or reject MPD policy is by a vote of at least two-thirds of the Common Council, or 10 members. 

“However, council members cannot make any decision about it until MPD actually drafts its policy, often referred to as a “standard operating procedure.” 

“Ald. Peter Burgelis – one of four council members who did not sign onto the Common Council letter to Norman – said he is waiting to make a decision until he sees potential policy from MPD or an official piece of legislation considered by the city’s Public Safety and Health Committee.”

The Milwaukee Police Department agrees that such a policy is necessary.

“MPD has consistently stated that a carefully developed policy could help reduce risks associated with facial recognition.

“’Should MPD move forward with acquiring FRT, a policy will be drafted based upon best practices and public input,’ a department spokesperson said.”

An aside from my days at MorphoTrak, when I would load user conference documents into the CrowdCompass mobile app: one year the topic of law enforcement agency facial recognition policies was part of our conference agenda. One agency had such a policy, but the agency would not allow me to upload the policy into the CrowdCompass app. You see, the agency had a policy…but it wasn’t public.

Needless to say, the Milwaukee Police Department’s draft policy WILL be public…and a lot of people will be looking at it.

Although I don’t know if it will make everyone’s dreams come true.

Why retail needs biometrics – the cameras aren’t working, and the people aren’t working either

(Imagen 4)

In a recent post on Biometric Update, “Why retail needs biometrics – the cameras aren’t working,” Professor Fraser Sampson, former UK Biometrics & Surveillance Camera Commissioner made several points about the applicability of biometrics to retail. Among the many points he addressed, he dealt with algorithmic inaccuracy and the proper use of facial recognition as an investigative lead:

“It’s true that some early police algorithms were poor, but the biometric matching algorithms offered by some providers is over 99.99% – that’s as close to perfect as anyone has ever got. That’s NASA-level accuracy, better than some medical or military procedures and light years away from people staring at CCTV monitors. What about errors and misidentification? Used properly, LFR is a decision support tool, it’s not making the identification itself. Ultimately, it’s helping shopkeepers make their decisions and that’s where the occasional misidentification happens – by human error, not technical.”

I offered an additional comment:

“One other point: for all those who complain about the lack of perfection of automated facial recognition, it’s much better than manual facial recognition. The U.S. Innocence Project recounts multiple cases of witness MISidentification, where people have been imprisoned due to faulty and inaccurate identification of suspects as perpetrators. I’d much rather have a top tier FR algorithm watching me than a person who knows nothing about facial recognition at all.”

In case you missed it, I’ve written several Bredemarket blog posts on witness MISidentification: two on Robert Williams’ misidentification alone.

Heck, I addressed the topic back in 2021 in “The dangers of removing facial recognition and artificial intelligence from DHS solutions (DHS ICR part four).” This post covers the misidentification of Archie Williams (no relation).

So don’t toss out the automated facial recognition solution unless you have something better. I’ll wait.

Worries About the Certified Communist Products List

(Imagen 4)

(Part of the biometric product marketing expert series)

How many of you have heard of the Certified Products List (CPL)?

The CPL’s vendor coverage

This list, part of the FBI’s Biometric Specifications website (FBI Biospecs), contains fingerprint card printers, fingerprint card scan systems, identification flats systems, live scan systems, mobile ID devices, and other products. Presence on the CPL indicates that the product complies with a relevant image quality specification such as Appendix F of the Electronic Biometric Transmission Specification.

The Certified Products List has existed since the 1990s and includes a number of products with which I am familiar. These products come from companies past and present, including 3M Cogent, Aware, Biometrics4All, Cross Match, DataWorks Plus, IDEMIA Identity & Security France, Identicator, Mentalix, Morpho, Motorola, NEC Technologies, Printrak, Sagem Defense Securite, Thales, and many others.

As of June 26, 2025, it also references companies such as Shenzhen Interface Cognition Technology Co., Ltd. and Shenzhen Zhi Ang Science and Technology Co., Ltd.

A strongly worded letter

Those and other listings caused heartburn for the bipartisan Members of the U.S. House of Representatives Select Committee on the Chinese Communist Party.

So they sent a strongly worded letter.

“We write to respectfully urge the FBI to put an end to its ongoing certification of products from Chinese military-linked and surveillance companies—including companies blacklisted or red-flagged by the U.S. government—that could be used to spy on Americans, strengthen the repressive surveillance state of the People’s Republic of China (PRC), and otherwise threaten U.S. national security.”

Interestingly enough, they make a big deal of Hikvision products on the list, but I searched the CPL multiple times and found no Hikvision products.

The CPL’s purpose

And it’s important to note the FBI’s own caveat about the CPL:

“The Certified Product List (CPL) provides users with a list of products that have been tested and are in compliance with Next Generation Identification image quality specifications (IQS) regarding the capture of friction ridge images. Specifications and standards other than image quality may still need to be met. Appearance on the CPL is not, and should not be construed as, an FBI endorsement, nor should it be relied upon for any requirement beyond IQS. Users should contact their State CJIS Systems Officer (CSO) or Information Security Officer (ISO) to ensure compliance with the necessary policies and/or guidelines.“

In other words, the ONLY purpose of the CPL is to indicate whether the products in question meet technology standards. It has nothing to do with export controls or any other criteria that any law enforcement agency needs to follow when buying a product.

What about the U.S. Department of Commerce?

But the FBI isn’t the only agency “promoting” Chinese biometrics.

Wait until the Select Committee discovers the Department of Commerce’s NIST FRTE lists, including the FRTE 1:1 and FRTE 1:N lists. The tops of these lists (previously known as FRVT) include many Chinese companies.

And actually, the FRTE testing includes facial recognition products that inspired U.S. export bans. Fingerprint devices are harder to use to repress people.

What next?

What happens if the concern extends beyond China, to products produced in France and products produced in Canada?

Regarding the strongly worded letter, Biometric Update added one detail:

“As of this writing, the FBI has not issued a public response. Whether the bureau will move to decertify the flagged companies or push back on the committee’s recommendations remains to be seen. But with multiple national security statutes already in place, and Congress signaling a willingness to legislate further, the days of quiet certification for foreign adversary-linked tech firms may be numbered.”

The Monk Skin Tone Scale

(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?

40 point makeup skin tone scale

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.

6 point Fitzpatrick skin tone scale

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.

10 point Monk Skin Tone (MST) Scale

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.

From https://skintone.google/the-scale.

Where is the MST Scale used?

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?