In May 2023, the President’s Council of Advisors on Science and Technology (PCAST) published a Request for Public Input to help assess key opportunities and risks and provide input on how best to ensure that these GenAI technologies are developed and deployed as equitably, responsibly, and safely as possible. The Computing Community Consortium (CCC) responded emphasizing the role of academic research in addressing risks associated with generative AI. Solutions will require multidisciplinary, multi-pronged approaches that simultaneously implement solutions in the form of policies and regulations, technological advances, and education. These will necessitate transparent communication among the various stakeholders, the use of basic computing research, major contributions and collaborations from social sciences, and a determined, […]

In May 2023, the Office of Science and Technology (OSTP) published a request for information on to inform the Biden-Harris Administration development of a National Artificial Intelligence (AI) Strategy. The strategy will chart a path for the United States to harness the benefits and mitigate the risks of AI and build on the actions that the Federal Government have already taken to responsibly advance the development and use of AI. Public comments will go towards helping to update U.S. national priorities and future actions on AI. You can read the Computing Community Consortium’s (CCC) response here. The CCC’s response focused on promoting academic research’s role in the research ecosystem, as […]

The Biden-Harris Administration is continuing their recent efforts to advance the research, development, and deployment of responsible AI. With the rise of AI and its increasing capabilities these initiatives are meant to protect American citizens’ rights and safety. Last week the CCC blog highlighted responsible AI efforts from the White House. Yesterday the White House announced three more initiatives summarized below. An update to the National AI Research and Development Strategic Plan. This plan builds on plans issued in 2016 and 2019, and sets out key priorities and research goals to guide federal investments in AI research and development (R&D). It will focus federal investments in R&D to promote responsible […]

The development and implementation of responsible artificial intelligence systems has come to the forefront of conversations and concerns in government, industry and academia. Last week the Biden-Harris Administration introduced new actions to advance responsible AI. The actions include: New investments to power responsible American AI research and development (R&D). The National Science Foundation is announcing $140 million in funding to launch seven new National AI Research Institutes. This investment will bring the total number of Institutes to 25 across the country, and extend the network of organizations involved into nearly every state. These Institutes catalyze collaborative efforts across institutions of higher education, federal agencies, industry, and others to pursue transformative AI […]

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 […]