I suspect that it wouldn’t be that hard to train models at datacenters outside of CA (my guess is this is already done to a decent extent today: 1⁄12 of Google’s US datacenters are in CA according to wiki). That models are therefore a pretty elastic regulatory target.
Data as a regulatory target is interesting, in particular if it transfers ownership or power over the data to data subjects in the relevant jurisdiction. That might e.g. make it possible for CA citizens to lodge complaints about potentially risky models being trained on data they’ve produced. I think the whole domain of data as a potential lever for AI governance is worthy of more attention. Would be keen to see someone delve into it.
I like the thought that CA regulating AI might be seen as a particularly credible signal that AI regulation makes sense and that it might therefore be more likely to produce a de jure effect. I don’t know how seriously to take this mechanism though. E.g. to what extent is it overshadowed by CA being heavily Democrat. The most promising way to figure this out in more detail to me seems like talking to other state legislators and looking at the extent to which previous CA AI-relevant regulation or policy narratives has seen any diffusion. Data privacy and facial recognition stand out as most promising to look into, but maybe there’s also stuff wrt autonomous vehicles.
Yeah, I’m really bullish on data privacy being an effective hook for realistic AI regulation, especially in CA. I think that, if done right, it could be the best option for producing a CA effect for AI. That’ll be a section of my report :)
Funnily enough, I’m talking to state legislators from NY and IL next week (each for a different reason, both for reasons completely unrelated to my project). I’ll bring this up.
I suspect that it wouldn’t be that hard to train models at datacenters outside of CA (my guess is this is already done to a decent extent today: 1⁄12 of Google’s US datacenters are in CA according to wiki). That models are therefore a pretty elastic regulatory target.
Data as a regulatory target is interesting, in particular if it transfers ownership or power over the data to data subjects in the relevant jurisdiction. That might e.g. make it possible for CA citizens to lodge complaints about potentially risky models being trained on data they’ve produced. I think the whole domain of data as a potential lever for AI governance is worthy of more attention. Would be keen to see someone delve into it.
I like the thought that CA regulating AI might be seen as a particularly credible signal that AI regulation makes sense and that it might therefore be more likely to produce a de jure effect. I don’t know how seriously to take this mechanism though. E.g. to what extent is it overshadowed by CA being heavily Democrat. The most promising way to figure this out in more detail to me seems like talking to other state legislators and looking at the extent to which previous CA AI-relevant regulation or policy narratives has seen any diffusion. Data privacy and facial recognition stand out as most promising to look into, but maybe there’s also stuff wrt autonomous vehicles.
Yeah, I’m really bullish on data privacy being an effective hook for realistic AI regulation, especially in CA. I think that, if done right, it could be the best option for producing a CA effect for AI. That’ll be a section of my report :)
Funnily enough, I’m talking to state legislators from NY and IL next week (each for a different reason, both for reasons completely unrelated to my project). I’ll bring this up.
Great! Looking forward to seeing it!