Three years after the release of the National Artificial Intelligence Research and Development Strategic Plan, the Trump administration issued an update this week, adding a new focus on public-private partnerships.
“The landscape for AI R&D is becoming increasingly complex due to the significant investments being made by industry, academia and non-profit organizations, and AI advancements are progressing rapidly,” said Michael Kratsios, deputy U.S. chief technology officer. “The federal government must therefore continually reevaluate its priorities for AI R&D investments to ensure that investments continue to advance the cutting edge of the field and are not duplicative of industry investments.”
The original strategic plan was issued by the Obama administration in 2016, with President Trump calling for an update through a February 2019 executive order.
“The common theme we saw in the responses included increased interest in the translational applications of AI technology, the importance of developing trustworthy AI systems, workforce considerations and, of course, public-private partnerships for furthering AI R&D,” said Lynne Parker, assistant director for AI in the White House Office of Science and Technology Policy.
Parker cited ongoing examples already in play in government, including the Defense Innovation Unit, Health and Human Services Department’s Health Tech Sprint Initiative and the National Science Foundation’s recent partnership with Amazon promoting fairness in AI development.
Going forward, Parker said the strategy will push for agencies and the private sector—including industry, non-profit and academia—to share resources, including research data, facilities and access to education.
The updated plan also modernizes focus areas in the original plan:
- Make long-term investments in AI research
- Develop effective methods for human-AI collaboration
- Understand and address the ethical, legal and societal implications of AI
- Ensure the safety and security of AI systems
- Develop shared public datasets and environments for AI training and testing
- Measure and evaluate AI technologies through standards and benchmarks
- Better understand the national AI R&D workforce needs.