On May 23, 2023, the White House released The National Artificial Intelligence R&D Strategic Plan. The plan is an update of the 2016 and 2019 editions of the National Strategic Plan for AI R&D, reiterating the previous eight strategic objectives, adjusting and refining the specific priorities of each strategy, and adding a new strategy to emphasize international cooperation.
I. Introduction
In February 2022, the White House Office of Science and Technology Policy (OSTP) issued a request for information seeking input from interested parties on the development of the National Strategic Plan for AI R&D. Subsequently, OSTP received more than 60 responses from researchers, scientific institutions, professional societies, civil society organizations and individuals. Notably, most of the responses addressed the ethical, legal, and social implications of AI (see Strategy 3) or the safety and security of AI systems (see Strategy 4), with academia, industry, and the public placing high priority on the development and deployment of safe, transparent, fair, and privacy-free AI systems.
The response also highlighted the importance of supporting AI research and development to help address some of the most important challenges and opportunities facing the United States, including advancing personalized medicine, improving cybersecurity, addressing social inequality, improving efficiency in manufacturing, transportation, and other important economic sectors, ensuring environmental sustainability, driving scientific discovery and innovation, and powering the next generation of technological breakthroughs.
The Fiscal Year 2024 Multiagency R&D Priorities Memorandum of Understanding issued by the U.S. Office of Management and Budget (OMB) and OSTP similarly calls on agencies to prioritize funding for technology research and development to enhance national security and technological competitiveness, including trusted artificial intelligence, as well as other critical and emerging technologies of national interest.
OSTP established the National Office of Artificial Intelligence Programs (NAIIO) under the National Artificial Intelligence Initiative Act of 2020, which oversees and implements the U.S. National AI Strategy and serves as a central hub for U.S. government coordination with the private sector and academia in AI research and decision-making. In addition, NAIIO contributes to the priorities outlined in the plan and comprehensively addresses AI-related risks and opportunities.
II. Background
Artificial intelligence is one of the most powerful technologies of our time. To seize the opportunities presented by AI, countries must work to manage their risks. The federal government plays a key role in this, including by investing in research and development to promote responsible innovation and proposing solutions to challenges that other sectors cannot tackle alone. The federal government must put people at the center, invest in responsible research and development, serve the public interest, protect people's rights and safety, and uphold democratic values. This updated National Strategic Plan for AI R&D is a roadmap to drive this goal.
The plan identifies key R&D challenges in the field of AI that will ensure continued U.S. leadership in developing and using trusted AI systems.
3. Nine strategies
Strategy 1: Long-term investment foundation and responsible AI research
Prioritize investments in next-generation AI technologies to drive responsible innovation, serve the public interest, and keep the United States a world leader in AI. This includes improving AI-based capabilities such as sensing, representation, learning, and reasoning, and working to make AI easier to use and more reliable, as well as assessing and managing the risks associated with generative AI.
Table 1 Specific elements of the 10 areas covered by strategy 1
Strategy 2: Develop effective human-AI collaborative approaches
Delve into how to create AI systems that effectively complement and augment human capabilities. Open research areas include the attributes and requirements of excellent human-AI teams; Ways to measure the efficiency, effectiveness, and performance of AI team collaboration, and how to reduce the risk of human misuse of AI applications. The strategy recognizes the growing importance of socio-technical and human factors, arguing that effective human-AI cooperation requires multidisciplinary research.
Table 2 Specific elements of the five areas covered by strategy 2
Strategy 3: Understand and address the ethical, legal and social implications of AI
Take steps to understand and mitigate the ethical, legal, and social risks posed by AI, and ensure that AI systems reflect the right values and promote equity. Interdisciplinary research is one of the important approaches, including upholding values through technological processes and design, and advancing the design and analysis of AI explainability and privacy protection. At the same time, it is critical to develop verifiable metrics and frameworks for accountability, fairness, privacy, and bias. The strategy highlights society's growing concern about the ethical, legal and social implications of AI.
Table 3 Specific elements of the four areas covered by strategy 3
Strategy 4: Ensure the security of AI systems
Learn more about ways to design AI systems that are trustworthy, reliable, and secure, including how to improve the ability to test, verify the functionality and accuracy of AI systems, and protect AI systems from cybersecurity and data vulnerabilities.
Table 4 Specific elements of the two areas covered by strategy 4
Strategy 5: Develop shared public datasets and environments for AI training and testing
Develop and enable high-quality datasets and environments, as well as testing and training resources. Allowing a broader and more diverse community to participate in AI research using high-quality data and tools can effectively promote innovation and equity in research.
Table 5 Specific elements of the four areas covered by strategy 5
Strategy 6: Measure and evaluate AI systems using standards and benchmarks
Develop widely available assessment techniques, including technical standards and benchmarks, for AI, in line with the government's AI Bill of Rights blueprint and AI risk management framework.
Table 6 Specific elements of the five areas covered by strategy 6
Strategy 7: Better understand the needs of national AI R&D talent
Improve R&D opportunities and strategically develop AI talent in the United States. This requires research to further understand the limitations and possibilities of AI and related work, as well as to improve the education and fluency necessary to interact effectively with AI systems.
Table 7 Specific elements of the 10 areas covered in strategy 7
Strategy 8: Strengthen public-private partnerships to accelerate AI development
Work with academia, industry, international partners, and other non-federal entities to promote continued investment in responsible AI R&D and enhance the ability to translate advanced results.
Table 8 Specific elements of strategy 8 in three areas
Strategy 9: Establish principled and coordinated approaches to international cooperation on AI research
Prioritize international cooperation on AI R&D to address global challenges such as environmental sustainability, healthcare, and manufacturing. Strategic international partnerships will help drive responsible AI research and development, as well as the development and implementation of international norms and standards for AI.
Table 9 Specific elements of the four areas covered by strategy 9
Disclaimer: This article is transferred from Meta Strategy, the original author Zhou Wei. The content of the article is the personal views of the original author, this public account compilation/reprint is only to share, convey different views, if you have any objections, welcome to contact us!
Transferred from 丨 Meta Strategy
Author丨Zhou Wei
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