In 2009, Ralph Lauren published an ad where a model's waist was edited smaller than her head. The brand apologized and called it "very distorted." The model was fired. That ad ran fifteen years before anyone asked me whether AI headshots were ethical. I want to start there because the question has a longer history than the discourse pretends. The line we are arguing about now sits exactly where it sat then.
By Joshua Albanese, founder, Aurawave AI · May 4, 2026 · 9 minute read.
Why I am the one writing this
20 years behind a camera · 15,000 studio sessions · roughly 3 million headshots retouched · founder of a top-10 US headshot studio (Chicago, 2007 to 2024) · founder of Aurawave AI · the only AI-headshot brand led by a working photographer
In this post
The argument I am making, in order:
- An AI headshot built from your real reference photos is not a deception.
- Every professional headshot you have ever trusted has been manipulated.
- The "best day" the AI shows you is the same goal a working photographer has at the cull.
- The dishonest photo is the 5-year-old one, not the polished new one.
- The hardest counter-argument is fake-identity fraud, and that is a different category.
The thesis, plainly
Here is what I believe, after 20 years of pushing pixels on real faces.
"AI builds from real reference photographs. I can see every pore of the person, and it literally just recreates them. It shows them up on their best day. Pretty much all headshots go through a layer of Photoshop, which all those pixels get pushed around, edited, and adjusted, so at the end of the day, most professional photographs are already manipulated."
That is the spine. The rest of this post defends it.
What the AI is actually doing
A customer uploads reference photos. Real ones. The AI grades those photos for skin tone, hair line, jaw shape, ear position, eye shape. Every pore and freckle is in the input.
The AI is not inventing a face. It is rebuilding one from the pixels the customer handed over. If the reference photos are honest, the output is a polished version of the same person.
I have run this loop on my own studio shoots for years, just by hand. I cull the keepers. I clean a blemish. I balance the fill ratio. The AI runs the same loop in software. The materials are the same. The standard is the same.
"AI doesn't invent the person. It rebuilds them from the photos they handed me."
The "best day" framing
A working photographer shoots hundreds of frames in a session. We deliver five. The 795 we threw away were the same person on the same day. We chose the keepers because they were the better version.
Every working studio uses some version of this language. The goal, in our trade, is to keep the subject looking like their natural self on their best day. Not a model. Not a stranger. Them, on the take where the eyes were alive and the shoulders were square.
The AI is doing the cull in software. It grades, it kills the failures, and it ships the keepers. The customer never sees the rejects, the same way my studio clients never saw their 795 throwaways.
A 5-star Aurawave reviewer named the outcome better than I could. Jeremy Bengtson called his photos "a version of yourself that looks like you, but on your absolute best day." That sentence is the job.
Every professional headshot is already manipulated
The discourse pretends the manipulation question started with AI. It did not. Photoshop shipped in 1990. The line we are arguing about now was crossed three decades ago.
Three cases anchor the history. Each one is a working photographer or magazine doing what AI critics fear, with no AI in the room.
Three cases that prove the point
The named retouching scandals predate AI by a decade or more. They tell the same story the new debate is trying to tell, with old tools.
- Ralph Lauren, 2009. A Filippa Hamilton ad in Japan was edited so her waist was smaller than her head. Ralph Lauren apologized for "poor imaging and retouching." The model was 5'10" and 120 pounds. She was then fired.
- Vanity Fair, February 2014. A "Vanities" feature appeared to lighten Lupita Nyong'o's complexion in a way that contradicted her actual skin tone. Side-by-side comparisons surfaced within hours. The retouching changed the identity, not just the polish.
- GQ UK, January 2003. Kate Winslet's legs were digitally narrowed by about a third on the cover. Winslet objected on the record: "I do not look like that and more importantly I don't desire to look like that." She later signed a no-retouching clause with L'Oréal.
These are working photographers and magazines. None of them used AI. All of them changed the photo. The honest debate about AI headshots is not new. It is a 20-year-old debate with a new tool in the room.
The studio pipeline you trust is already manipulated
Frequency separation is the standard professional retouching technique. It splits the photo into a texture layer and a tone layer, then lets the retoucher smooth one without losing the other. Every working headshot studio uses it. The PetaPixel guide to professional frequency separation retouching has been the reference text on the technique since 2015.
A clean retouch on one photo runs four to five minutes. A full pass with dodge-and-burn, color correction, and blemish cleanup can run thirty minutes to an hour. I have personally retouched, supervised, or approved retouching on roughly 3 million headshots across my career.
"I've retouched roughly 3 million headshots. The line between honest and dishonest sits in the same place it sat in 2007."
That line is craft, not absolutism. The honest question is not whether the photo was manipulated. The honest question is whether it still looks like you.
The dishonest photo is the 5-year-old one
The discourse points at the polished new photo and calls it the lie. I think that is the wrong target.
The dishonest photo is the one from 2019. The one with the hair you no longer have. The lighting from a kitchen you have moved out of. The face of a person who has gained or lost ten pounds since.
A polished photo built from current reference shots is closer to the person who walks into the meeting. The 5-year-old selfie is not. The viewer will recognize you. The 5-year-old photo guarantees they will not.
"The dishonest photo is the one that no longer looks like you."
The deception the discourse fears is already on the platform. It is just wearing a 2019 timestamp.
The honest counter-arguments
I am not making the soft version of this argument. The strongest objections deserve the steelmanned answer.
"Aren't AI photos already being used for fraud?"
Yes, and the case is darker than people realize. Microsoft documented North Korean operatives using AI-swapped photos to place fake IT workers inside 320+ US companies last year. The Microsoft research on North Korean fake-IT-worker AI tactics is the hardest version of this objection. I take it seriously. But the crime there is the fake identity. Fake names, stolen documents, fabricated résumés, swapped faces. The photo is one tool inside a fraud built on a person who does not exist. That is a different category from a real working professional updating a profile photo from their own reference shots. One is fake-identity fraud. The other is real-person-presented-well. The same word "AI photo" is doing too much work if it covers both. The Stanford research surfaced by NPR's coverage of fake LinkedIn profiles using AI faces tells the same story. The deception is the made-up person, not the polish.
"Aren't you just presenting a polished version that isn't really you?"
Every professional headshot ever taken is the polished version. That is the job. The studio has better lighting than your kitchen. The photographer has a better eye for posture than your selfie does. The retoucher cleans the blemish you would have cleaned in the mirror. If "the polished version isn't really you" is an objection to AI, it is also an objection to professional photography. I have been making polished versions of real people for 20 years. The polish is honest as long as it is faithful to the person.
"Shouldn't AI photos be disclosed?"
The disclosure norm is forming, but it has not reached profile photos. YouTube, Meta, and TikTok all require labels on photorealistic synthetic video. New York's Synthetic Performer Disclosure Bill targets AI-generated talent in advertising. None of those rules currently cover a profile headshot built from your own reference photos. LinkedIn's profile photo policy permits AI-enhanced photos provided they "reflect your likeness." That platform hosts more professional headshots than any other site. It has already adjudicated this question. I would tell a colleague how the photo was made if they asked. I would not label every photo "AI-built" any more than I would label a 2010 portrait "Photoshop-retouched."
The platform that has already decided
The platform discourse treats this as unresolved. LinkedIn does not.
LinkedIn's policy permits AI-enhanced profile photos as long as they "reflect your likeness." No mandatory disclosure. No AI label. No warning badge. The platform that hosts more professional headshots than any other site on the internet has made the call. A polished AI headshot built from your own reference photos is allowed. A photo of a different person, or of nobody, is not.
That is the right line. It is the same line I draw in my own studio.
Where the line actually sits
The honest test is not "was Photoshop used" or "was AI used." Both questions are decades late.
The honest test is whether the photo represents the person who is going to walk into the meeting. If a colleague at the next desk would recognize you from the photo, it is honest. If they would not, it is not.
That is the test I run on every studio session I cull. It is the test the Aurawave engine runs on every output it grades. Jeremy's review put the outcome in customer voice. "Former colleagues have messaged asking when I had a professional shoot done." His old colleagues recognized him. The photo passed.
The line was crossed the day Photoshop shipped. The question now is which side you are standing on.
Try the headshot the colleague will recognize
We built Aurawave to ship the polished version of you that still looks like you. The grading loop runs on every order. If the photo does not look like you, we redo it.
See sample headshots · Read the recruiter-detection post
About the author
Joshua spent 20 years shooting studio headshots before he wrote a line of code for Aurawave. The ethics question is the one his clients have asked him directly, in his studio, every week for the last 18 months. This post is his answer.
Joshua Albanese is the founder of Aurawave AI. He spent 20+ years as a working professional headshot photographer. He founded a top-10 US headshot studio in Chicago. His career covers 15,000+ studio sessions and 3M+ images.
Joshua Albanese, founder, Aurawave AI