Using ‘radioactive data’ to detect if a data set was used for training
At first glance, this seems like one of the more interesting projects to come out of Facebook AI. Justification: In the future, AI models will increasingly become interwoven with tech. It's not going to be so much "AI programming" as just "programming".<p>That raises an interesting question – one that has bothered me for a long time: Who owns copyright on training data?<p>As we saw with Clearview AI, a lot of data is being used without consent or even knowledge of the creators. And it's extremely hard to detect this usage, let alone enforce rights on it.<p>I might be misunderstanding this work, but it <i>seems</i> like this would give you the ability to mark your digital data in such a way that you could prove it was later used in a model.<p>Unfortunately, it's not that simple. You don't have access to the models (normally). And I'm betting that this work is somehow domain-specific, meaning you can't really come up with a generalized marker to imprint on all your data.<p>But this implies you might be able to mark your data with <i>many</i> such markers, in hopes that one of them will later be triggered:<p><i>We also designed the radioactive data method so that it is extremely difficult to detect whether a data set is radioactive and to remove the marks from the trained model.</i><p>The flipside is interesting, too: This might give companies yet another way of tracking users. Now you can check whether a given user was in your model's actual training set, and if not, fine-tune the model on the fly.<p>Looking forward to seeing what comes of this.