To think this is what companies are trying to get away with whilst the technology is still flawed enough to be caught. As it gets more accurate in what it can create we're going to have less of a realistic understanding of reality.
If they say what this is, then fine, if they don't then its a problem.
The reason being that an artist rendition is almost clearly an artist rendition, whereas ai imagery can look cannily like an actual photograph, and therefore present itself as a primary document.
The problem with misrepresenting, whether deliberately or accidentally, primary documentation is that this is supposed to be a documentary, one of the few show types where fact and accuracy (should) matter.
Netflix has used what strongly appears to be AI-generated or -manipulated images in a recent documentary about a murder-for-hire plot involving a woman named Jennifer Pan that took place in Canada back in 2010.
The streaming service used the photos to illustrate her "bubbly, happy, confident, and very genuine" personality, as high school friend Nam Nguyen described her.
The images that appear around the 28-minute mark of Netflix's "What Jennifer Did," have all the hallmarks of an AI-generated photo, down to mangled hands and fingers, misshapen facial features, morphed objects in the background, and a far-too-long front tooth.
Needless to say, using generative AI to describe a real person in a true-crime documentary is bound to raise some eyebrows.
But resorting to the tech to generate pictures of a real person, especially of somebody who's still in jail and will only be eligible for parole around 2040, should raise some alarm bells.
This isn't inventing a fictional narrative for the sake of entertainment — this is tinkering with the fabric of reality itself to manipulate a true story that actually happened.
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I’ve said this since day one - we need a reliable way to identify AI generated content
If we fail to separate the two, or create safeguards like this, we’re in a lot more trouble than the destruction of the job market would be. And that’s saying something.
“Put it back in the box” isn’t a solution.
Banning the technology isn’t a solution.
We must face it for what it is, put our heads together, and create the solution.
If you ever create a reliable tool to identify AI images, you automatically provide learning data for AI to generate images that get past the AI detection.
You don't understand that tech; when making an AI model, you do code both a generator of whatever it is you want to make, as well as a "detector" which tells you whether or not the result is convincing.
Then you change the genertor slightly based of the results of the "detector"
You do that a few million times and then you have a correct AI model, the quality of which is dependant on both the quantity of training and the "detector".
If someone comes up with a really strong "detector", they will do work as intended for a few days/weeks, and then AIs will come on the market which will be able to fool the detector
I've done that for broadcast before. Sadly it barely made any difference, but I felt it was at least just a little better than nothing and made it at least possible to sorta see what was supposed to be going on in the low quality source images and those images were the only ones that seemed to exist of the thing we were showing.