Last month, the National Telecommunications and Information Administration (NTIA) released a request for comment on Artificial Intelligence (AI) system accountability measures and policies. The request sought comments pertaining to both potential and existing self-regulatory, regulatory, and other measures designed to provide reliable evidence to external stakeholders that AI systems are legal, effective, ethical, safe, and otherwise trustworthy. Written by Nadya Bliss (Arizona State University), David Danks (University of California, San Diego), Maria Gini (University of Minnesota), Jamie Gorman (Arizona State University), William Gropp (University of Illinois), Madeline Hunter (Computing Community Consortium), Odest Chadwick Jenkins (University of Michigan), David Jensen (University of Massachusetts Amherst), Daniel Lopresti (Lehigh University), Bart Selman (Cornell […]

With the rise of Artificial Intelligence (AI) and its increasingly ubiquitous role in society, the Biden administration, a multitude of government agencies, and nonprofits are turning their attention to the assurance and implementation of responsible AI practices. The Center for Security and Emerging Technology (CSET) is no exception and has contributed to the effort with three recent reports seeking to help organizations implement responsible AI. A Matrix for Selecting Responsible AI Frameworks By Mina Narayanan and Christian Schoeberl Synopsis: Process frameworks provide a blueprint for organizations implementing responsible artificial intelligence (AI). A new issue brief by CSET’s Mina Narayanan and Christian Schoeberl presents a matrix that organizes approximately 40 process […]

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 […]