The three challenges of AI regulation | Brookings thumbnail
The three challenges of AI regulation | Brookings
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can outstrip the federal government’s existing expertise and authority. The regulatory statutes and structures available to the government today were built on industrial era assumptions that have already been outpaced by the first decades of the digital platform era. Existing rules are insufficientl
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  • can outstrip the federal government’s existing expertise and authority. The regulatory statutes and structures available to the government today were built on industrial era assumptions that have already been outpaced by the first decades of the digital platform era. Existing rules are insufficiently agile to deal with the velocity of AI developmen...
  • Allowing the companies to become pseudo-governments and make their own rules to govern AI would be to repeat the mistake made when they were allowed to make their own rules for online platforms.
  • AI is a multi-faceted capability, “one-size-fits all” regulation will over-regulate in some instances and under-regulate in others. The use of AI in a video game, for instance, has a different effect—and should be treated differently—from AI that could threaten the security of critical infrastructure or endanger human beings. AI regulation, thus, m...
  • The “gateway drug” for digital exploitation is the collection of individuals’ personal information. The history of online platforms has been one of continued expansion of the amount of personal data collected to increase the granularity of the targeting the companies sell to advertisers.
  • Transparency is the tool that provides ongoing insight into the identification and mitigation of the evolutionary risks of AI. Such transparency begins with continuous research into how the models work. After having built the algorithmic “black box,” even the providers of AI often cannot know exactly what their creation is doing. Access to the mode...

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