Roughly every ten years the Theoretical Computer Science (TCS) community comes together for a visioning workshop to discuss recent accomplishments and new challenges in the field of TCS. The workshop acts as an opportunity for reflection within the community and a way of informing interested investors. The newly released Visions in Theoretical Computer Science Workshop Report, written by Shuchi Chawla (University of Wisconsin-Madison), Jelani Nelson (University of California, Berkeley), Chris Umans (California Institute of Technology), and David Woodruff (Carnegie Mellon University) and supported by the Computing Community Consortium, summarizes the key takeaways from the 2020 TCS Visioning Workshop. Organized by the SIGACT Committee for the Advancement of Theoretical Computer Science, […]

The June issue of the Communications of the ACM (CACM) features the Viewpoint article “A Vision to Compute Like Nature: Thermodynamically.” Based on the Computing Community Consortium’s (CCC) Thermodynamic Computing workshop, this article advocates for a novel, physically grounded, computational paradigm centered on thermodynamics that the authors call “Thermodynamic Computing” (TC). This Viewpoint was written by workshop co-organizers, Todd Hylton (UC San Diego), Tom Conte (Georgia Tech), and Mark D. Hill (Microsoft & U. Wisconsin). In the article, they lay out the premise of TC: “…living systems evolve energy-efficient, universal, self-healing, and complex computational capabilities that dramatically transcend our current technologies. Animals, plants, bacteria, and proteins solve problems by spontaneously […]

Contributions to this post were provided by CCC Vice Chair Daniel Lopresti.  AI for Good Global Summit hosted a webinar on AI to Prevent Modern Slavery, Human Trafficking and Forced and Child Labour today and featured Computing Community Consortium (CCC) Executive Council Member Nadya Bliss (Executive Director of the Global Security Initiative at Arizona State University) as well as Alice Eckstein (Programme Manager, Modern Slavery Programme at United Nations University – Centre for Policy Research), Doreen Boyd (Professor of Earth Observation, Faculty of Social Sciences at University of Nottingham), James Goulding (Deputy Director N/LAB, Faculty of Social Sciences at University of Nottingham) and Anjali Mazumder (Thematic Lead on AI, Justice […]

Contributions to this post were provided by CCC Council member Holly Yanco (University of Massachusetts, Lowell).  In 2009, the CCC published a report, A Roadmap for US Robotics, From Internet to Robotics (a.k.a. the Robotics Roadmap), which explored the capacity of robotics to act as a key economic enabler, specifically in the areas of manufacturing, healthcare, and the service industry, 5, 10, and 15 years into the future. An updated version of the Robotics Roadmap was released in March 2013, November 2016, and now most recently in September 2020. See the CCC blog about the 2020 version here.  The original Robotics Roadmap was the basis for the 2011 National Robotics […]

The White House yesterday established a new office focused on coordinating U.S. efforts in Artificial Intelligence research. The new National Artificial Intelligence Initiative Office, under the leadership of Founding Director and current U.S. Deputy Chief Technology Officer Lynne Parker, “is charged with overseeing and implementing the United States national AI strategy and will serve as the central hub for Federal coordination and collaboration in AI research and policymaking across the government, as well as with private sector, academia, and other stakeholders.” See the new logo that features a bald eagle clutching a neural network.  The White House Office of Science and Technology Policy (OSTP) established the new office in accordance […]

Contributions to this post were provided by CCC Council member Odest Chadwicke Jenkins.  Computing Community Consortium (CCC) Council member Odest Chadwicke Jenkins (University of Michigan) was recently interviewed by the New York Times about his thoughts on the AI field’s apparent failure to make systems that are accurate for everyone. Many of today’s AI systems have biases against people of color and the broader diversity beyond the white, male, affluent and able-bodied developers  of most computer and robot systems. We need to be sure that when autonomous robots make their decisions, the designer’s flaws and judgements are not “baked in.”   Robotics researchers in our community are committed to ending the […]