Ongoing CCC Activities
In the chart below you can check the status of ongoing white papers, reports, and workshops.
|AI Working Group||The Artificial Intelligence Working Group has generated an AI Roadmap. Lead by Yolanda Gil (University of Southern California and President-Elect of AAAI) and Bart Selman (Cornell University), this new effort is in support of the Administrations’ efforts in this area, and brought together academic and industrial researchers and federal agency representatives to help chart a course for needed research in AI, through a series of workshops in the Fall of 2018, resulting in a Roadmap that was released in the summer of 2019. The final Roadmap is now available here. Learn more about the process to create the roadmap here.|
|Industry Working Group||The Industry Collaboration Working Group will lead the CCC’s effort to find and communicate best practices to industry-academia and public-private partnerships. Informed by the CCC’s 2015 The Future of Computing Research: Industry-Academia Collaborations this working group will establish ties with industry and lead the creation of white papers, workshops, and other content for future collaborations. The focus of the working group for 2018-2019 has been transportation, particularly autonomous vehicles and the requisite intelligent infrastructure. The Computing Community Consortium’s (CCC) Industry Working Group released their Evolving Academia/Industry Relations in Computing Research: Interim Report for comments in March, and the final report was released in June 2019. Read the final report here.|
|Thermodynamic Computing Workshop||The Systems and Architecture task force led the Thermodynamic Computing Workshop, which took place January 3-5, 2019 in Honolulu, Hawaii. The workshop posited that striving for thermodynamic efficiency is not only highly desirable in hardware components, but may also be used as an embedded capability in the creation of algorithms: can dissipated heat be used to trigger adaptation/restructuring of (parts of) the functioning hardware, thus allowing hardware to evolve increasingly efficient computing strategies? Recent theoretical developments in non-equilibrium thermodynamics suggest that thermodynamics drives the organization of open systems as a natural response to external input potentials; that is, that these systems adapt as they dissipate energy, enter low dissipation homeostatic states and as a result ‘learn’ to ‘predict’ future inputs. A workshop report is in progress. The CCC also sponsored the Manoa Mini-Symposium on Physics of Adaptive Computation, which featured a number of speakers from the Thermodynamic Computing workshop. Two podcast episodes about the workshop, featuring interviews with the workshop organizers and participants are available here, and a workshop report is now available here.|
|Assured Autonomy Workshop Series||Autonomy is becoming mainstream. The anticipation is that cyber-physical-human systems and services enabled by autonomy will improve the future work conditions and the quality of life for humans and create new business models. On the other hand, a number of looming challenges—whether autonomous systems are safe and secure, whether we can assure their safety and security, whether humans will ever trust and work with them, whether we can integrate them at scale and whether we can do all these economically—overshadow the popular belief that a revolution driven by autonomy is imminent.
This series of three workshops aims to help create a unified understanding of the goals for assured autonomy and the research trends as well as near-term, mid-term and long-term research needs supporting these goals. The first workshop took place October 16-17 in Arlington, VA, and the second workshop took place February 20-21, 2020 in Phoenix, AZ. A third workshop will take place in 2020. Learn more about the workshop series here.
|Wide-Area Data Analytics Workshop||Modern datasets are often distributed across many locations. In some cases, datasets are naturally distributed because they are collected from multiple locations, such as sensors spread throughout a geographic region. In other cases, datasets are distributed across different data centers to improve scalability or reliability, or to reduce cost; these distributed locations could be a mix of public clouds, private data centers, and edge computing sites. How should we analyze data collected or stored at multiple far-flung locations? We believe that bringing these researchers together at a single workshop will create opportunities for interdisciplinary collaboration, and help in bridging the gaps between related work in different areas. In addition, the workshop can help create a stronger foundation for a broader view of “systems” as a common core research area in computer science, rather than separate research communities. The CCC held a workshop on wide-area data analytics on October 3-4, 2019 in Washington, D.C. A workshop report was released in June 2020 — read it here.|
|Computational Support for Substance Use Disorder Prevention, Detection, Treatment, and Recovery||In the United States, 20.2 million adults or 8% of the population is estimated to suffer from a substance use disorder (SUD). SUDs include a wide array of substances such as alcohol, opioids, methamphetamine, and other substances and are characterized by an inability to decrease use, despite severe social, economic, and health-related consequences to the individual. In 2017, the US Department of Health & Human Services declared a public health emergency to combat what has been termed as “the opioid epidemic” and highlighted five critical strategies:
Computational support may contribute to each of these strategies by mobilizing a new set of systems, algorithms, and tools to understand and combat substance use disorders. These technologies may provide scalable and accessible complementary approaches to traditional methods and services.
In November, 2019 the CCC held a workshop to the discuss opportunities and challenges to developing such computational support systems in Washington, D.C. A workshop report was released in June 2020 — read it here.
|Leadership in Embedded Security Workshop||The Cybersecurity Taskforce of the CCC held a leadership workshop to envision the future of embedded security research and education from hardware to cyberphysical systems to human factors, co-located with the 27th USENIX Security Symposium. A workshop report is now available.|
|Code 8.7: Using Computation Science and AI to End Modern Slavery||On February 19-20, 2019, the CCC co-sponsored the Code 8.7: Using Computation Science and AI to End Modern Slavery conference with the United Nations University Centre for Policy Research, The Alan Turing Institute, Tech Against Trafficking, University of Nottingham Rights Lab, and Arizona State University Global Security Initiative. The two-day conference brought together the computational research and artificial intelligence (AI) communities together with those working to achieve Target 8.7 of the Sustainable Development Goals.With Target 8.7, 193 countries agreed to take immediate and effective measures to end forced labour, modern slavery and human trafficking by 2030, and the worst forms of child labour by 2025. You can stream the recordings of the conference on the Delta 8.7 Facebook page. A podcast episode about the conference is available for streaming here.
On March 3-4, 2020, the CCC and Code 8.7 held a workshop on Applying AI in the Fight Against Modern Slavery in Washington, DC. Session topics included self-aware learning, meaningful interaction with AI systems, integrated intelligence, open AI platforms and resources, and computational techniques designed to support the sharing of highly sensitive data while at the same time providing strong privacy guarantees. A workshop report is in progress.
For more information about ongoing CCC activities contact Director Ann Drobnis at adrobnis [at] cra.org.