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James Yoon is an associate in the firm’s Data Privacy and Cybersecurity Practice Group. Prior to joining the firm, he served as a law clerk to Judge J. Clifford Wallace on the U.S. Court of Appeals for the Ninth Circuit and Judge Barbara M.G. Lynn on the U.S. District Court for the Northern District of Texas.

James is a member of the Bar of California. District of Columbia bar application pending; supervised by principals of the firm.

The National Institute of Standards and Technology (“NIST”) has published the first draft of the Four Principles of Explainable Artificial Intelligence (NISTIR 8312), a white paper that seeks to define the principles that capture the fundamental properties of explainable AI systems.  AI Initiative Co-Chair Lee Tiedrich, Sam Choi, and James Yoon discuss

The National Institute of Standards and Technology (“NIST”) is seeking comments on the first draft of the Four Principles of Explainable Artificial Intelligence (NISTIR 8312), a white paper that seeks to define the principles that capture the fundamental properties of explainable AI systems.  NIST will be accepting comments until October 15, 2020.

In February 2019, the Executive Order on Maintaining American Leadership in Artificial Intelligence directed NIST to develop a plan that would, among other objectives, “ensure that technical standards minimize vulnerability to attacks from malicious actors and reflect Federal priorities for innovation, public trust, and public confidence in systems that use AI technologies; and develop international standards to promote and protect those priorities.”  In response, NIST issued a plan in August 2019 for prioritizing federal agency engagement in the development of AI standards, identifying seven properties that characterize trustworthy AI—accuracy, explainability, resiliency, safety, reliability, objectivity, and security.

NIST’s white paper focuses on explainability and identifies four principles underlying explainable AI.


Continue Reading AI Standards Update: NIST Solicits Comments on the Four Principles of Explainable Artificial Intelligence and Certain Other Developments

On June 4, 2020, Representatives Anna Eshoo (D-CA-18), Anthony Gonzalez (R-OH-16), and Mikie Sherrill (D-NJ-11) introduced the National AI Research Resource Task Force Act.  This bipartisan bill would create a task force to propose a roadmap for developing and sustaining a national research cloud for AI.  The cloud would help provide researchers with access to computational resources and large-scale datasets to foster the growth of AI.

“AI is shaping our lives in so many ways, but the true potential of it to improve society is still being discovered by researchers,” explained Rep. Eshoo. “I’m proud to introduce legislation that reimagines how AI research will be conducted by pooling data, compute power, and educational resources for researchers around our country.  This legislation ensures that our country will retain our global lead in AI.”


Continue Reading Bipartisan Bill Seeks to Create National Artificial Intelligence Research Resource Task Force

On May 19, 2020, Representative Morgan Griffith (R-VA-9) introduced the Advancing Quantum Computing Act (AQCA), which would require the Secretary of Commerce to conduct a study on quantum computing.  “We can’t depend on other countries . . . to guarantee American economic leadership, shield our stockpile of critical supplies, or secure the benefits of technological

Lee Tiedrich, B.J. Altvater, and James Yoon recently published an article summarizing recent developments in artificial intelligence law and policy on the University of Pennsylvania Law School’s Regulatory Review.  The article primarily focuses on developments in the United States, including the National Artificial Intelligence Initiative Act introduced by members of the House Committee

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