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Comments to NTIA on AI Accountability

by Hodan Omaar

The Center for Data Innovation has filed comments with the National Telecommunications and Information Administration (NTIA) on AI system accountability measures and policies. As explained in the RFC, the request seeks information on self-regulatory, regulatory, and other measures and policies designed to provide reliable evidence to external stakeholders—that is, to provide assurance—that AI systems are legal, effective, ethical, safe, and otherwise trustworthy. Our comments respond to the following questions:

  • AI accountability measures have been proposed in connection with many different goals. To what extent are there tradeoffs among goals?
  • The application of accountability measures (whether voluntary or regulatory) is more straightforward for some trustworthy AI goals than for others. Are there any trustworthy AI goals that are not amenable to requirements or standards? How should accountability policies, whether governmental or non-governmental, treat these differences?
  • Are there ways in which accountability mechanisms are unlikely to further, and might even frustrate, the development of trustworthy AI? Are there accountability mechanisms that unduly impact AI innovation and the competitiveness of U.S. developers?
  • Where in the value chain should accountability efforts focus?
  • Should AI accountability mechanisms focus narrowly on the technical characteristics of a defined model and relevant data? Or should they feature other aspects of the sociotechnical system, including the system in which the AI is embedded?
  • Is the lack of a federal law focused on AI systems a barrier to effective AI accountability?

Read our comments.

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