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Comment by geocrasher | Hacker News Reader

Out of the hundreds of thousands of people who saw the original accusation, only a few will see the follow-up. It will forever be known that iPhones replace people's heads with leaves. This is how urban legends are born.

This is one of the few times I'll ever feel sorry for Apple! I can only imagine the calls they're going to get from Karen's who didn't take good pictures to begin with and blame Apple for it because they saw an internet that one time that somebody's iPhone replaced a head with some leaves.

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It's quite amusing though that so many brain cycles were wasted trying to figure out how ML image processing was to blame. I don't recall anyone in the previous thread saying: maybe there's a leaf between the camera and the woman's head. It certainly didn't occur to me that it was something so obvious.

(btw, is the "Karen" reference really necessary? It's a sexist, racist insult that detracts from an otherwise interesting comment)

There were a bunch of people who did say "I bet a leaf fell off a tree when you snapped the photo" - and the OP insisted that didn't happen.

Well, to be fair, he was correct. That's not what happened.

Nobody dare to insult saying that the leaves must have been in front of a face, just like nobody would dare to say to "google search doesn't work on my computer!" - "did you turn it on?".

Still interesting to see how people can rush to blame ML post-processing over a trivially overlooked parallax effect even when the former argument/theory may still potentially exist.

> btw, is the "Karen" reference really necessary

No, it wasn't necessary but at this point, what isn't considered a slur anymore?

Genuine Q: how is it racist?

A demeaning term applied to a subcategory of whites.

Stereotyping != Racism

Every culture, color, creed, nationality, and gender has Karens.

Karen is a pejorative term for a white woman perceived as entitled or demanding beyond the scope of what is normal [1] so it is just as "racist" as many other "racist" things. If "Karen" isn't racist then neither are many - if not most - things which are deemed racist. I'm fine with that so I hope you're sincere and are willing to follow this old-new definition of racism. If the term goes back to where it belongs - the assumption of people's traits based on their physical appearance with a heavy emphasis on skin tone - and it ceases to be bandied around as a label for anything which happens to displease the one doing the labelling the world will become a better place.

[1] https://en.wikipedia.org/wiki/Karen_(slang)

I sincerely appreciate your comment! With that definition in mind then I can understand why people downvoted my comment so much.

To anyone I offended, I sincerely apologize.

The truth of the matter is that I'll call anybody a Karen who is dumb enough to deserve the label. I don't care about color they are I don't care where they're from I don't care what they look like or how their hairstyle is done or what they're wearing or how many kids they have or how rich they are or how poor they are. I could have just as easily said a***e.

But I chose Karen because people who act like a Karen are idiots.

Its racist against the group that you "can't" be racist against

It’s racist against the group who can handle a bit of racism.

You didn't define which group that is... maybe you can enlighten us.

White people, particularly white women. I'm fairly sure you knew this? Here's the definition of the pejorative "Karen" [1]:

Karen is a pejorative term for a white woman perceived as entitled or demanding beyond the scope of what is normal. The term is a meme depicting white women who use their privilege to demand their own way.

[1] https://en.wikipedia.org/wiki/Karen_(slang)

> is the "Karen" reference really necessary? It's a sexist, racist insult

And also misused quite frequently. Its origin was a white woman who called the police on a group of black people who were doing nothing wrong other than being black in the wrong place.

I don't know where you heard that, but for a long time it was just a fill in name for a middle aged woman with a short hairstyle who would usually cause issues at customer service in retail. The "I'd like to see your manager" and the Karen stereotype go way further back. It's not usually about race with a Karen it's about power and getting their way even if that's not how the rules are set up. (This coupon is a year expired but I want it, this TV was marked for a dollar so you have to sell it to me, etc.)

Incorrect. Karen was originally someone who tried to wield power over retail workers, and always demanded a manager. The white lady calling police on black people usage came wayyy later.

Now it's been abused and overused to where I don't even know what it means anymore. Lady comes outside to ask TikTokers to quit doing burnouts in her yard and it's 'shutup kawen, stupid kawen LOL amirite'

I know exactly what the origin is (and as somebody commented below, it predates the incident you refer to). I also used it because it aptly describes people whose exaggerated sense of entitlement and privilege overshadows their desire to think critically.

My daughter saw this in person, where a woman was mad at people at the butcher section of the grocery store, calling woman who bought a whole chicken an 'animal murderer'. Plot twist: the very same woman had chicken breasts and thighs in her cart, but because they were not a whole chicken, she disassociated them from the animal they came from. I rest my case.

you can’t very well say a meme is misused, a meme is whatever it is.

Also, central park karen is a recent addition to the long history of using karen as a punchline, anytime you think you know the origin story, check know your meme first, you might be surprised: https://knowyourmeme.com/memes/karen

Anil Dash's interview with one of the co-founders of that site was interesting.

https://blog.glitch.com/episode/function-episode-3

So to make it meme it gets abstracted to "some self absorbed busybody stirring up unnecessary trouble for other people" or something similar. Nothing really racist or sexist about it at that point is there?

When we make every abstract thought racist, it weakens and renders the word "racist" into a casual meme, not unlike the name "karen".

Its origins are "racist" and "sexist" in that the stereotype is specifically a white woman.

I don't think there's anything wrong with a little stereotyping: the only reason it's "bad" is that actual bigots ruin the fun, so to speak. If anything, I feel bad for people named Karen.

No it wasn’t- there was just a heavy intersection between middle aged women complaining and BLM + other wokeness. “Karen” is used correctly here and your origin story is completely false.

You don't see men playing the victimization card at the drop of a pin. It is a genuine social phenomenon worthy of disregard.

> You don't see men playing the victimization card at the drop of a pin

I don't believe this was said jokingly, but just to be sure, this definitely happens all the time.

Where do you see men okay the victimization card at the drop of a pin? As far as I know there are as rare as hen's teeth, I have not seen a single example of either. If you have some examples I'd be interested in learning about them.

That or leaf people (similar to lizard people) can only be detected using iPhones.

Wouldn't need to obscure leaf people if we turned everyone into leaf people.

This is not just urban legends. In Hungary there's a soft dictorship where Viktor Orban is controlling the mainstream media with lots of lies. After independent organizations go to court, they usually win against Orban, and the media organizations publish corrections, but nobody reads them.

OMG, i was reading Quora today thinking exactly about what you wrote in the first paragraph. but in a different context.

there is that false story that gathered tons of likes and comments, even though a buried comment debunked the whole thing. the worst part is that it's since been shared in many Quora spaces. where it is gathering more likes and comments.

i stopped for a minute and wondered if the situation could have been prevented.

It's also an example of selection effects: this dude mentions he's taken 44k photos. You might think that such an experienced photographer wouldn't be fooled by this - "what, it was just a leaf in the way when he was zoomed in? that's all? surely he wouldn't make such a mistake, and it's surely machine learning at fault!" - but he's only human, and that's 44k+ chances to be wrong, for just a single photographer, where social media will amplify the oddest anecdote it can find across every photographer in the world.

It's not, "he took one photo and it came out wrong", it's, "humans everywhere took billions upon billions of photos and you only were told about the weirdest ones which fit a Narrative".

Looking at the original, yes, something leafy is in the foreground; however, the person’s visage and locks are made into cubist/polygonal-like leafiness in the background.

Yeah, this seems like damage control. The AI definitely made a mess of that woman's face.

The (a of course, but the one originally involved) responded 'it's a very cool lesson in focal length compression' though; so it seems to me from that & still from looking at the image that the iPhone is doing something - making choices, engineering trade-offs - that makes this accidental edge case worse.

No, focal length and its effects on imaging is a fundamental aspect of how lenses work. You could reproduce this with any camera. More here: https://en.wikipedia.org/wiki/Perspective_distortion_(photog...

This case actually seems even simpler though. There was a leaf in the foreground obscuring the face from the camera's perspective. Distortion doesn't quite enter into it.

They're not talking about the obscuring itself, but the focal compression effect which makes it look a lot like the leaf is where the head should be, rather than clearly being in front of said head.

Though the aggressive denoising and small lens probably doesn't help.

> Though the aggressive denoising and small lens probably doesn't help.

I think it's mostly this. The photograph is incredibly noisy, very difficult to tell what's going on.

Oh I didn't realise that was called 'compression', makes sense though, I was just thinking too software-y! Don't modern iPhones have multiple cameras for depth of field though, it could (or intends to) do something clever to make it clearer couldn't (resp. ) it?

The photo is already heavily denoised per the sibling comment — possible they could do more but it's difficult when the sensor and lens are so small.

I think it also speaks greatly to people's paranoia about technology they don't fully understand.

I think a lot of the HN crowd are susceptible to that because they know just enough to know it's possible but are not perhaps familiar with a given domain (I certainly know that applies to me).

It's perhaps some spin-off of the dunning-kruger observation... There must be a spot on the curve where a person knows just enough to be freaked out by what they're seeing, but not enough to explain it fully. Whereas here the Halide devs know the domain well enough to quickly diagnose it.

> I think a lot of the HN crowd are susceptible to that because they know just enough to know it's possible

Absolutely think this describes what happened

I'd have probably been more skeptical myself had I not seen an ad earlier in the day of an Android phone removing people from the background of an image as easily as you'd crop it. Whoops!

Eh, I mean you’re right that more people will hear the accusation than the retraction, but I think everyone already knows and will continue to know that iPhones have excellent cameras. I wouldn’t be worried about the reputation of iPhone cameras.

It's less about the reputation of the cameras but there was an unhealthy level of conspiracy in the original thread with regards to trust of digital images in general.

That post was already being widely used to justify the fairly ludite views on image upscaling by the judge in the Rittenhouse trial for example.

The judge was absolutely right to allow the defense to make sure no AI upscaling is used. It has nothing to do with Luddite views.

The judge didn't merely ask whether any such thing was used. He continuously pressed his own uninformed opinion over the evidence rather than trying to educate himself on the matter, especially given "expert" testimony

https://www.theverge.com/2021/11/12/22778801/kyle-rittenhous...

That's throwing his own incorrect mistrust of the technology into things. It wasn't based on precedent or founded by rational examples.

He also didn't provide alternate means for video playback that he would trust. It's reductionist.

At the very least, a competent prosecution should have then pulled up content in VLC and said "the source code for zooming is here and verifiable"

Interpolation algorithms (such as bicubic) used for zooming are not “AI” anymore than a decompression algorithm is. There’s no “training” involved; it’s an entirely “pure” algorithm. Same input in gets the exact same output out.

There was no AI upscaling. If you enlarge an image between two white pixels, the inserted pixel is white, you will not get an interpolated black pixel.

And in the opposite corner, we have valid concerns about the "just fill in the gaps" approach to photography getting shouted down by "have you missed the update? That was an actual leaf, not an iPhone dreaming!"

Dangerous precedent works both ways, I don't know which effect will be stronger.

But the iPhone has replaced her face with leaves. If you look at the photo. The place where her face and neck would be is replace with a blurred out brownness even on the parts not directly obstructed by the leaf.

For what it's worth I did send my friends this tweet with the rebuttal, after I had sent the original tweet a few hours ago, of course.

> This is one of the few times I'll ever feel sorry for Apple!

They're a trillion dollar company who don't give even the slightest little fuck about you. Stop feeling sorry for them, that is an insanely unhealthy way of thinking.

It’s the race stuff that now has me laughing. The machine learning had a data set that had too many white people and too few people of other colours (leaf colours?). Somehow this was relevant.

I find that people on here are _extremely_ uncharitable when it comes to anything Apple

This is why I don’t like Twitter.

Post now, think later

Twitter should have the ability to issue apology/retraction tweets. They know who's seen the original.

Their largest audience is "journalists" who wouldn't be happy with something like that.

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