- ACR Offers Free Healthcare Artificial Intelligence Platform
“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,” particularly in healthcare, the plan argued.
For the 2019 update, the council issued a request for information (RFI) in August of last year to get public feedback on ways the strategic plan should be revised or improved. This feedback, as well as an independent agency review, led to the update of the 2016 plan.
“A significant number of responses noted the importance of investing in the application of AI in areas such as manufacturing and supply chains; healthcare; medical imaging; meteorology, hydrology, climatology, and related areas; cybersecurity; education; data-intensive physical sciences such as high-energy physics; and transportation,” the plan related.
Respondents also argued for fairness, ethics, accountability, and transparency in AI systems, as well as curated and accessible datasets, workforce implications, and public-private partnerships in AI research and development.
Noting the rapid rise of privately funded AI R&D projects and the rapid adoption of AI by industry, respondents also advocated increased federal government engagement with the private sector.
Strategic Priorities for Federally Funded AI Research
The plan identified eight strategic priorities for federally funded AI research:
- Make long-term investments in AI research; prioritize investments in the next generation of AI that will drive discovery and insight and enable the United States to remain a leader in AI
- Develop effective methods for human-AI collaboration; increase understanding of how to create AI systems that complement and augment human capabilities
- Address the ethical, legal, and societal implications of AI; research AI systems that incorporate ethical, legal, and societal concerns through technical mechanisms
- Ensure the safety and security of AI systems; advance knowledge of how to design AI systems that are reliable, dependable, safe, and trustworthy
- Develop shared public datasets and environments for AI training and testing; enable access to high-quality datasets and environments, as well as to testing and training resources
- Evaluate AI technologies using standards and benchmarks; develop a spectrum of evaluative techniques for AI
- Understand the national AI R&D workforce needs; improve opportunities for workforce development to foster an AI-ready workforce
- Expand public-private partnerships to accelerate advances in AI; promote opportunities for sustained investment in AI R&D and for transitioning advances into capabilities, in collaboration with academia, industry, international partners, and other non-federal entities
“AI has advanced tremendously and today promises better, more accurate healthcare; enhanced national security; improved transportation; and more effective education, to name just a few benefits. Increased computing power, the availability of large datasets and streaming data, and algorithmic advances in machine learning (ML) have made it possible for AI development to create new sectors of the economy and revitalize industries,” the plan noted.
“AI technologies are critical for addressing a range of long-term challenges, such as constructing advanced healthcare systems, a robust intelligent transportation system, and resilient energy and telecommunication networks,” the plan concluded.