this post was submitted on 28 Nov 2023
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That explanation makes no fucking sense and makes them look like they know fuck all about AI training.
The output keywords have nothing to do with the training data. If the model in use has fuck all BME training data, it will struggle to draw a BME regardless of what key words are used.
And any AI person training their algorithms on AI generated data is liable to get fired. That is a big no-no. Not only does it not provide any new information from the data, it also amplifies the mistakes made by the AI.
They are not talking about the training process, to combat racial bias on the training process, they insert words on the prompt, like for example "racially ambiguous". For some reason, this time the AI weighted the inserted promt too much that it made Homer from the Caribbean.
They literally say they do this "to combat the racial bias in its training data"
And like I said, this makes no fucking sense.
If your training processes, specifically your training data, has biases, inserting key words does not fix that issue. It literally does nothing to actually combat it. It might hide issues if the data model has sufficient training to do the job with the inserted key words, but that is not a fix, nor combating the issue. It is a cheap hack that does not address the underlying training issues.
Yes. The training data has a bias, and they are using a cheap hack (prompt manipulation) to try to patch it.