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Regardless of their intentions, current state of the art automatic censorship have dangerously bad false positive and false negative rates. So, they inadvert

by hedora 3y ago

Regardless of their intentions, current state of the art automatic censorship have dangerously bad false positive and false negative rates. So, they inadvertently and inevitably suppress the truth and broadcast misinformation. Their performance on images is similarly bad. Of course, even if they did work, centralizing control of them is a bad idea. The end user should have the freedom to control such things. (In the same way you can type swear words into a word processor).

the_snooze 3y ago
In practice, these AI models are centralized services. Few people are running them locally on their machine with knowledge of the training data, weights, or system prompts. There isn't a direct line between "user intent" and "system output," unlike the local word processor in your example. Someone has to make value judgments on the underlying data and algorithms, if only to build the system in the first place. If users can't (or don't care to) run these models locally, who else will decide other than the service operator?
jameshart 3y ago
‘The censorship work done in AI alignment is insufficiently accurate to rely on for production use’ is a good and valid position ‘Therefore AI vendors should release uncensored models and let everyone else figure it out’ is not a logical consequent from it. ‘Therefore don’t use current AI tech to build apps that photomanipulate user submitted content and echo the results back to them with your logo on it’ would be a more logical conclusion to draw.
Fubarberry 3y ago
Thankfully that is how a lot of AI is working right now, open source models for both LLM and Stable Diffusion let people have access to uncensored reasonably decent quality AI tools. In other categories of AI generated content though, such as speech and music, the open source alternatives are either lacking or completely absent. And with the company behind Stable Diffusion being on the verge of financial collapse, we may see Stable Diffusion fall far behind it's closed source counterparts.

by hedora 3y ago

the_snooze 3y ago

In practice, these AI models are centralized services. Few people are running them locally on their machine with knowledge of the training data, weights, or system prompts. There isn't a direct line between "user intent" and "system output," unlike the local word processor in your example. Someone has to make value judgments on the underlying data and algorithms, if only to build the system in the first place. If users can't (or don't care to) run these models locally, who else will decide other than the service operator?

jameshart 3y ago

‘The censorship work done in AI alignment is insufficiently accurate to rely on for production use’ is a good and valid position ‘Therefore AI vendors should release uncensored models and let everyone else figure it out’ is not a logical consequent from it. ‘Therefore don’t use current AI tech to build apps that photomanipulate user submitted content and echo the results back to them with your logo on it’ would be a more logical conclusion to draw.

Fubarberry 3y ago

Thankfully that is how a lot of AI is working right now, open source models for both LLM and Stable Diffusion let people have access to uncensored reasonably decent quality AI tools. In other categories of AI generated content though, such as speech and music, the open source alternatives are either lacking or completely absent. And with the company behind Stable Diffusion being on the verge of financial collapse, we may see Stable Diffusion fall far behind it's closed source counterparts.