Computing Community Consortium (CCC) council member David Danks was recently featured on ACM News for his involvement in a CCC-sponsored scientific session at AAAS 2023 “Maintaining a Rich Breadth for Artificial Intelligence.” The session featured discussions highlighting the importance of incorporating a broad range of multi-discipline research and expertise. Panelists recognized that neural networks and deep learning have driven progress in AI over the year resulting in an imbalance and dominance of these disciplines in AI research. These silos can stunt the development of AI and lead to missed opportunities for growth in the field. Accompanied by panelists Melanie Mitchell and Bo Li, David Danks discussion topic: “Let a Thousand […]

This blog post is a continuation of yesterday’s summary of the Maintaining a Rich Breadth for Artificial Intelligence panel at the 2023 AAAS meeting. This panel was moderated by Maria Gini (University of Minnesota) and the panel comprised David Danks (University of California – San Diego), Bo Li (University of Illinois – Urbana-Champaign), and Melanie Mitchell (Santa Fe Institute)   Following the panel, Dr. Gini opened the discussion up to the audience for Q&A. The first question came from a researcher in the audience:   To what extent do you think homogeneity is an effect of cost in terms of the available hardware? Neural networks are cheap to create and […]

The final CCC panel of AAAS 2023, “Maintaining a Rich Breadth for Artificial Intelligence”, was held on Sunday, March 5th, the last day of the conference. This panel was composed of David Danks (University of California – San Diego), Bo Li (University of Illinois – Urbana-Champaign), and Melanie Mitchell (Santa Fe Institute) and was moderated by Maria Gini (University of Minnesota).    Dr. Bo Li began the panel by discussing the importance of conducting trustworthy machine learning (ML), and the ways in which we can ensure ML is safe, equitable, and inclusive. Machine learning is ubiquitous, Li said, and today is used in a significant number of everyday activities, such […]

The Department of Commerce has released a request for comment on AI Accountability Policy. The National Telecommunications and Information Administration is requesting comments on AI system accountability measures and policies. The comments will help the administration to draft and issue a report on AI accountability policy development focusing on AI assurance ecosystems. Comments are due June 10th, 2023. Summary: The National Telecommunications and Information Administration (NTIA) hereby requests comments on Artificial Intelligence (“AI”) system accountability measures and policies. This request focuses on self-regulatory, regulatory, and other measures and policies that are designed to provide reliable evidence to external stakeholders – that is, to provide assurance – – that AI systems […]

The CCC just released the 2nd Report Out in the three part Artificial Intelligence/Operations Research Visioning Workshop series. In September of 2021, the CCC along with the Institute for Operations Research and the Management Sciences (INFORMS) and ACM SIGAI, held the first AI/OR workshop virtually, during which they reviewed the current state of AI/OR research and developed a strategic vision for increased collaboration between the two fields. You can view the Report Out from the first workshop here.   In August of 2022, the second AI/OR workshop was held in Atlanta, GA. This workshop, also supported by INFORMS and ACM SIGAI, was organized by John Dickerson (University of Maryland), Bistra […]

This week the National Artificial Intelligence Research Resource (NAIRR) Task Force released a roadmap to establish a national research infrastructure aimed to broaden access to resources for AI research and development. There are ever increasing opportunities to work with cutting-edge AI technologies, but many of the opportunities are limited to large companies, organizations and academic institutions with an abundance of resources. The implementation plan, Strengthening and Democratizing the U.S. Artificial Intelligence Innovation Ecosystem, aims to provide AI researchers and students with access to computational resources, high-quality data, training tools, and user support. The report lays out the following goals for the NAIRR: Provide AI researchers and students with significantly expanded […]