Protected: Assured Autonomy Workshop #1
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Tag Archive: CCC
Protected: Computational Support for Substance Use Disorder Prevention, Detection, Treatment, and Recovery
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Leadership in Science Policy Institute
The Computing Research Association’s Computing Community Consortium offers its Leadership in Science Policy Institute to educate computing researchers on how science policy in the U.S. is formulated and how our government works. LiSPI features presentations and discussions with science policy experts, current and former Hill staff, and relevant agency and Administration personnel about mechanics of the legislative process, interacting with agencies, advisory committees, and the federal case for computing.
Symposium on Addressing National Priorities and Societal Needs
To raise awareness of the importance of computing research to the nation, and the CCC’s role in fostering that research, the CCC regularly holds a symposium in Washington, DC on Computing Research: Addressing National Priorities and Societal Needs, which also serves as an important medium for informing, inspiring, and engaging early career researchers. Learn about past symposiums below and stay tuned for updates about future symposiums
Wide-Area Data Analytics
Modern datasets are often distributed across many locations. This workshop will bring together researchers and practitioners in the database, networking, distributed systems, and storage fields in order to bridge the gap in research within wide-area data analytics.
Misinformation Roundtable
This roundtable will bring together computer scientists along with experts from disciplines potentially to include electrical engineering, psychology, marketing, information science, and political science to discuss challenges in detecting and countering misinformation.
AI Roadmap
In fall 2018, the Computing Community Consortium (CCC) started a new initiative to create a Roadmap for Artificial Intelligence, led by Yolanda Gil (University of Southern California and President-Elect of AAAI) and Bart Selman (Cornell University). A series of three workshops were held in the Fall/Winter of 2018/2019, which resulted in a Roadmap produced in the Spring of 2019. The goal of the initiative was to identify challenges, opportunities, and pitfalls, and create a compelling report that will effectively inform future federal priorities—including future AI R&D Investments. An Executive Summary of the Roadmap is now available.
Economics and Fairness
The Computing Community Consortium's (CCC) Fairness and Accountability Task Force will hold a visioning workshop on Economics and Fairness, May 22-23, 2019 in Cambridge, Massachusetts. This workshop will bring together computer science researchers with backgrounds in algorithmic decision making, machine learning, and data science with policy makers, legal experts, economists, and business leaders to discuss methods to ensure economic fairness in a data-driven world.
Code 8.7: Using Computational Science and AI to End Modern Slavery
Code 8.7 is a two-day conference that brings 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. Computational science, AI and machine learning can accelerate our understanding of these problems and help us determine “effective measures” to address them.
The featured image was made by Ira Gelb.
Artificial Intelligence Roadmap Workshop 3 – Self Aware Learning
Given the increasingly pervasive use in AI technologies in all sectors of industry and government and the enormous potential for future AI-based technologies, NSF has asked the Computing Community Consortium to organize an AI Roadmap to help prioritize research investments. The third workshop theme is Learning and Robotics and will take place on January 17-18, 2019 in San Francisco. The chairs of the Self Aware Learning workshop are Fei-Fei Li (Stanford University) and Thomas G. Dietterich (Oregon State University). This is part of the AI Roadmap workshop series – view the series page here.
