[This post was originally published on the CCC Blog by Helen Wright.]
The National Artificial Intelligence (AI) Research Resource (NAIRR) Task Force convened its third virtual public meeting to further develop a vision and implementation plan for the NAIRR. Computing Community Consortium (CCC) Council Member Ian Foster (Argonne National Laboratory and University of Chicago), was invited to speak about the recently published A National Discovery Cloud: Preparing the US for Global Competitiveness in the New Era of 21st Century Digital Transformation white paper.
In addition, 84 responses from industry, academia, and government stakeholders were recently released regarding the White House Office of Science and Technology Policy and the National Science Foundation request for information to develop an implementation roadmap for the NAIRR. The CCC, Computing Research Association-Industry (CRA-I), and the Association for the Advancement of Artificial Intelligence (AAAI) submitted a joint response.
The joint response came from the extensive discussions within the national AI research community that arose while developing A 20-Year Community Roadmap for Artificial Intelligence Research in the US (AI Roadmap) as well as conversations among the newly formed CRA-I Steering Committee and community.
See some snippets from the joint response below:
- A NAIRR should support work on a range of core challenges in AI research and development.
- i. Integrated intelligence, including developing foundational principles for combining modular AI capabilities and skills, approaches for contextualizing general capabilities to suit specific uses, creation of open shared repositories of machine understandable world 1 knowledge, and understanding human intelligence both to inspire novel AI approaches and to develop models of human cognition.
- ii. Meaningful interaction, comprising techniques for productive collaboration in mixed teams of humans and machines, combining diverse communication modalities (verbal, visual, emotional) while respecting privacy, responsible and trustworthy behaviors that can be corrected directly by users, and fruitful online and real-world interaction among humans and AI systems.
- iii. Self-aware learning, developing robust and trustworthy learning, quantifying uncertainty and durability, learning from small amounts of data and through instruction, incorporating prior knowledge into learning, developing causal and steerable models from numerical data and observations, and learning real-time behaviors for intentional sensing and acting.
- In looking at the organization and management of the NAIRR, it is important to recognize both the key importance of data and the reality that that data will be distributed across the country, in commercial clouds, at national research facilities, and at academic institutions. An NAIRR needs to place adequate computing near the data, which implies that there are multiple sites providing computing resources for NAIRR.
The NAIRR, like the AI Roadmap, has the potential to bring the field to a new era of audacious AI research to tackle long-standing and multidisciplinary problems. These investments will significantly accelerate the development and deployment of AI technologies with a profound impact across all sectors of society.