The US Principles for AI and OECD

The Great Difference Between the OECD Principles and The US Principles

This may be one of the shortest articles I will ever write, however I think there is one major difference between the OECD Principles of AI and the US.

  1. Public participation. The public should have a chance to provide feedback in all stages of the rule-making process.
  2. Scientific integrity and information quality. Policy decisions should be based on science.
  3. Risk assessment and management. Agencies should decide which risks are and aren’t acceptable.
  4. Benefits and costs. Agencies should weigh the societal impacts of all proposed regulations.
  5. Flexibility. Any approach should be able to adapt to rapid changes and updates to AI applications.
  6. Fairness and nondiscrimination. Agencies should make sure AI systems don’t discriminate illegally.
  7. Disclosure and transparency. The public will trust AI only if it knows when and how it is being used.
  8. Safety and security. Agencies should keep all data used by AI systems safe and secure.
  9. Interagency coordination. Agencies should talk to one another to be consistent and predictable in AI-related policies.
  • AI systems should be designed in a way that respects the rule of law, human rights, democratic values and diversity, and they should include appropriate safeguards – for example, enabling human intervention where necessary – to ensure a fair and just society.
  • There should be transparency and responsible disclosure around AI systems to ensure that people understand AI-based outcomes and can challenge them.
  • AI systems must function in a robust, secure and safe way throughout their life cycles and potential risks should be continually assessed and managed.
  • Organisations and individuals developing, deploying or operating AI systems should be held accountable for their proper functioning in line with the above principles.

AI Policy and Ethics at Student at University of Copenhagen MSc in Social Data Science. All views are my own.

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