A 20-Year Community Roadmap for Artificial Intelligence Research in the US
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Abstract (arXiv)
Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Aug 2019.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 4.
8 papers.
- 2021Unsolved Problems in ML Safetycited by 291
- 2022Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignmentcited by 27
- 2023Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Gamescited by 10
- 2023Analyzing the Impact of Companies on AI Research Based on Publicationscited by 5
- 2022Artificial intelligence in government: Concepts, standards, and a unified frameworkcited by 3
- 2023Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanationscited by 3
- 2021CCC/Code 8.7: Applying AI in the Fight Against Modern Slaverycited by 1
- 2023Deep Learning for Spatiotemporal Big Data: A Vision on Opportunities and Challengescited by 1
- 2023Analyzing the Impact of Companies on AI Research Based on Publications31 Oct 2023
- 2023Deep Learning for Spatiotemporal Big Data: A Vision on Opportunities and Challenges30 Oct 2023
- 2023Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations8 Jul 2023
- 2023Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games2 Mar 2023
- 2022Artificial intelligence in government: Concepts, standards, and a unified framework31 Oct 2022
- 2022Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment6 Feb 2022
- 2021Unsolved Problems in ML Safety28 Sep 2021
- 2021CCC/Code 8.7: Applying AI in the Fight Against Modern Slavery24 Jun 2021