Comment by jjeaff
2 years ago
In fairness to the AI, I have often been confused by stock images or old images on news articles that are not from the event in question.
2 years ago
In fairness to the AI, I have often been confused by stock images or old images on news articles that are not from the event in question.
Photo attribution is a bit of a problem. For a tornado in Kansas they may use an image from another year’s tornado in Mississippi. For the war in Azerbaijan they might use an image from Chechnya, etc.
That is precisely the type of editorial affordance I would expect the AI to strip. This is just another way for media organizations to distort the news. I look forward to those enhancements
False metadata for rich media is a damned tough problem to target.
Putting aside any actually truthful captions, how do I know that "image of X" is actually an image of X?
Reading some of the Bellingcat investigations, and time spent, doesn't bode well.
I guess you could TinEye and index/hash the entire web's worth of rich media, then spot discrepancies (listed as X here, but Y there), but that seems horrendous in compute/bandwidth/storage terms.
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> This is just another way for media organizations to distort the news
No, it's not. This is done because stories with images perform better, and obtaining images (& licenses) for photos of every event is not always possible.
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AI can just fabricate a new photo for any event.
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True, I have a photograph taken in Kenya that has been variously described as in California, Guatemala, Colombia, Australia and South Africa.