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A Missed Opportunity to Further Build Trust in AI: A Landscape Analysis of OECD.AI

Author

Listed:
  • Susan Ariel Aaronson

    (George Washington University)

Abstract

OECD.AI is the world's best source for information on public policies dedicated to AI, trustworthy AI and international efforts to advance cooperation in AI. However, the web site is also a missed opportunity to ascertain best practice and to build trust in AI not just for citizens of reporting nations but for the world. The author came to that conclusion after examining the documentation that nations placed online at OECD.AI. website. She utilized a landscape analysis to group these policies reported to the OECD by country and type, whether the initiative was evaluated or reported on, and whether it provided new insights about best practice trust, in AI, and/or trustworthy AI. Some 61 countries and the EU reported to the OECD on their AI initiatives (for a total of 62). Although the members of the OECD are generally high and high-middle income nations, the 62 governments providing information to OECD.AI represent a mix of AI capacity, income level, economic system, and location. Some 814 initiatives placed on the website as of August 2022, but 4 were duplicative and some 30 were blank, leaving 780. Of these, countries claimed that 48 of these initiatives were evaluated. However, we actually found only four evaluations (and one in progress) with a clear evaluative methodology. Two initiatives were labeled evaluations but did not include a methodology. Many of the other 42 were reports rather than evaluations. In addition, only a small percentage (41 initiatives or 5% of all initiatives) were designed to build trust in AI or to create trustworthy AI systems. National policymakers and not the OECD Secretariat decide what each of the 62 governments choose to put on the site. These officials don't list every initiative their country implements to foster AI. But their choices reveal their priorities. Most of the documentation focuses on what they are doing to build domestic AI capacity and a supportive governance context for AI. We also found relatively few efforts to build international cooperation on AI, or to strengthen other countries' AI capacity. Taken in sum, these efforts are important but reveal little effort to build international trust in AI.

Suggested Citation

  • Susan Ariel Aaronson, 2022. "A Missed Opportunity to Further Build Trust in AI: A Landscape Analysis of OECD.AI," Working Papers 2022-10, The George Washington University, Institute for International Economic Policy.
  • Handle: RePEc:gwi:wpaper:2022-10
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    More about this item

    Keywords

    AI (artificial intelligence) trust; trustworthy; policies; innovation;
    All these keywords.

    JEL classification:

    • A1 - General Economics and Teaching - - General Economics

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