National Artificial Intelligence R&D Strategic Plan# Programming - 葵花宝典
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https://www.nitrd.gov/news/national_ai_rd_strategic_plan.aspx
Strategy 1: 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 world leader in AI.
Strategy 2: Develop effective methods for human-AI collaboration. Rather
than replace humans, most AI systems will collaborate with humans to achieve
optimal performance. Research is needed to create effective interactions
between humans and AI systems.
Strategy 3: Understand and address the ethical, legal, and societal
implications of AI. We expect AI technologies to behave according to the
formal and informal norms to which we hold our fellow humans. Research is
needed to understand the ethical, legal, and social implications of AI, and
to develop methods for designing AI systems that align with ethical, legal,
and societal goals.
Strategy 4: Ensure the safety and security of AI systems. Before AI systems
are in widespread use, assurance is needed that the systems will operate
safely and securely, in a controlled, well-defined, and well-understood
manner. Further progress in research is needed to address this challenge of
creating AI systems that are reliable, dependable, and trustworthy.
Strategy 5: Develop shared public datasets and environments for AI training
and testing. The depth, quality, and accuracy of training datasets and
resources significantly affect AI performance. Researchers need to develop
high quality datasets and environments and enable responsible access to high
-quality datasets as well as to testing and training resources.
Strategy 6: Measure and evaluate AI technologies through standards and
benchmarks. . Essential to advancements in AI are standards, benchmarks,
testbeds, and community engagement that guide and evaluate progress in AI.
Additional research is needed to develop a broad spectrum of evaluative
techniques.
Strategy 7: Better understand the national AI R&D workforce needs. Advances
in AI will require a strong community of AI researchers. An improved
understanding of current and future R&D workforce demands in AI is needed to
help ensure that sufficient AI experts are available to address the
strategic R&D areas outlined in this plan.
Strategy 1: 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 world leader in AI.
Strategy 2: Develop effective methods for human-AI collaboration. Rather
than replace humans, most AI systems will collaborate with humans to achieve
optimal performance. Research is needed to create effective interactions
between humans and AI systems.
Strategy 3: Understand and address the ethical, legal, and societal
implications of AI. We expect AI technologies to behave according to the
formal and informal norms to which we hold our fellow humans. Research is
needed to understand the ethical, legal, and social implications of AI, and
to develop methods for designing AI systems that align with ethical, legal,
and societal goals.
Strategy 4: Ensure the safety and security of AI systems. Before AI systems
are in widespread use, assurance is needed that the systems will operate
safely and securely, in a controlled, well-defined, and well-understood
manner. Further progress in research is needed to address this challenge of
creating AI systems that are reliable, dependable, and trustworthy.
Strategy 5: Develop shared public datasets and environments for AI training
and testing. The depth, quality, and accuracy of training datasets and
resources significantly affect AI performance. Researchers need to develop
high quality datasets and environments and enable responsible access to high
-quality datasets as well as to testing and training resources.
Strategy 6: Measure and evaluate AI technologies through standards and
benchmarks. . Essential to advancements in AI are standards, benchmarks,
testbeds, and community engagement that guide and evaluate progress in AI.
Additional research is needed to develop a broad spectrum of evaluative
techniques.
Strategy 7: Better understand the national AI R&D workforce needs. Advances
in AI will require a strong community of AI researchers. An improved
understanding of current and future R&D workforce demands in AI is needed to
help ensure that sufficient AI experts are available to address the
strategic R&D areas outlined in this plan.