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Jack Clark has been writing on Twitter about the need of greater public engagement in the AI space.

I followed up on his reading as the topic of public involvement in digital is high on our priority list at @openfuture (#SharedDigitalEurope).

Jack Clark and Jess Whittlestone argue for robust govt monitoring of AI space. I like the point that such monitoring-driven policies would be more dynamic.

Their approach assumes that govts make use of data that is in the open - which would make a good case of the value of OpenX approaches to data, code, research.

But I would push further: the case they describe is a great example why we need Public Data Commons and B2G data sharing.

http://arxiv.org/abs/2108.12427

2 użytkowników udostępniło to dalej

@Alek @Open Future Foundation
So i read

"5 How could governments use AI measurement and monitoring?
5.1 Testing deployed systems to see if they conform to regulation."


And below ... no single idea how to reliably test #closedsource / #closeddata #AI models learned from petabytes of public available data. Any possible "test" says nothing about possible problems with model/data but is ,in fact, another way to further (and free!) model learning. Without access to the source code and learning data set, "monitoring" of already available commercial AI models is simply bullshit and nonsens.