— Tate Ryan-Mosley, senior tech policy reporter

I’ve always been a super Googler and coped with uncertainty by trying to learn as much as I could about anything that might happen. Including my father’s throat cancer.

I began Googling the stages of grief and books and research on loss from an app on my iPhone, intentionally and unintentionally consuming people’s experiences of grief and tragedy through Instagram videos, various news feeds, and Twitter responses.

Yet, with every search and click, I was unwittingly creating a sticky web of digital grief. After all, it would prove almost impossible to untangle what the algorithms served me. I came out – finally. But why is it so hard to unsubscribe and opt out of content we don’t need, even if it hurts us? Read the story in its entirety.

AI models spit out photos of real people and copyrighted images

News: Image generation models can create identifiable photographs of real people, medical images and copyrighted works of artists, according to new research.

How they did it: Researchers have repeatedly prompted Stable Diffusion and Google Image for image captions, such as a person’s name. They then analyzed whether any of the generated images matched the original images in the model database. The group was able to obtain more than 100 copies of images from the AI ​​training set.

Why it matters: The finding could strengthen the case for artists who are currently suing AI companies for copyright infringement, and could potentially threaten people’s privacy. It could also have implications for startups looking to use generative AI models in healthcare, as it shows that these systems are at risk of leaking sensitive private information. Read the story in its entirety.

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