In its update to its National Artificial Intelligence Research And Development Strategic Plan, the White House’s Office of Science and Technology Policy has set new objectives for federal AI research.
WHY IT MATTERS
The strategic plan boils down to eight strategies for how government can better enable development of safe and effective AI and machine learning technologies for healthcare and other industries.
- Make long-term investments in AI research, prioritizing next-generation applications that can help “drive discovery and insight and enable the United States to remain a world leader in AI.”
- Develop more effective strategies for human-AI collaboration, with a focus on AI systems that “effectively complement and augment human capabilities.”
- Understand and address the “ethical, legal, and societal implications of AI” and how they can be addressed through the technology.
- Work to ensure AI systems’ safety and security, and spread knowledge of “how to design AI systems that are reliable, dependable, safe, and trustworthy.”
- Create high-quality, shared public datasets and environments for AI training and testing.
- Measure and evaluate AI with standards and benchmarks, eventually arriving at a broad set of evaluative techniques, including technical standards and benchmarks.
- Better understand the workforce needs of AI researchers and developers nationwide, and work strategically to foster an AI-ready workforce.
- Expand existing public-private partnerships, and create new ones to speed advances in AI, promoting opportunities for sustained investment R&D and for “transitioning advances into practical capabilities, in collaboration with academia, industry, international partners, and other non-Federal entities.”
The 50-page document takes special interest in ensuring that data used to power AI is trustworthy and that the algorithms used to process it are understandable – not least in healthcare.
“A key research challenge is increasing the ‘explainability’ or ”transparency’ of AI,” according to the report. “Many algorithms, including those based on deep learning, are opaque to users, with few existing mechanisms for explaining their results. This is especially problematic for domains such as healthcare, where doctors need explanations to justify a particular diagnosis or a course of treatment. AI techniques such as decision-tree induction provide built-in explanations but are generally less accurate. Thus, researchers must develop systems that are transparent, and intrinsically capable of explaining the reasons for their results to users.”
THE LARGER TREND
The Office of Science and Technology Policy sees many uses for AI in healthcare, not just for clinical and operational improvements, but, among other things, enhanced security. It points to work from the HHS Division of Research, Innovation, and Ventures that involves an accelerator network and is recruiting a nonprofit partners who can work with investors to fund “innovative technologies and products to solve systemic health security challenges, with AI applications being one area of interest.”
The new strategic plan comes just four months after President Donald Trump signed the American AI Initiative, which calls for the federal government to prioritize research and development for artificial intelligence, in recognition that the U.S. needs to play catch-up in the global push for AI innovation.
The country “urgently needs workers and businesses skilled in AI and capable of leading our country’s development and application of AI into the future,” said administration officials in making the announcement.
But that initiative was criticized by many for being light on specific details and its failure to include any new funding for its R&D aims.
“There’s no AI strategy,” Dr. Eric Topol, founder and director of Scripps Research Translational Institute, told Healthcare IT News in March. “We’re doing nothing. We have we have a zero-dollar investment in this country. The recent Trump declaration that it’s a top priority was accompanied by zero resources.”
ON THE RECORD
“Artificial intelligence presents tremendous opportunities that are leading to breakthroughs in improved healthcare, safer and more efficient transportation, personalized education, significant scientific discoveries, improved manufacturing, increased agricultural crop yields, better weather forecasting, and much more,” said Michael Kratsios, deputy assistant to the president for technology policy.
“These benefits are largely due to decades of long-term Federal investments in fundamental AI R&D, which have led to new theories and approaches for AI systems, as well as applied research that allows the translation of AI into practical applications,” he added.
“The landscape for AI R&D is becoming increasingly complex, due to the significant investments that are being made by industry, academia, and nonprofit organizations,” said Kratsios. “Additionally, AI advancements are progressing rapidly. 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 unnecessarily duplicative of industry investments.”