Identify current and anticipated challenges and problems in assuring autonomous systems within and across applications/sectors.
The goal of this workshop was to bring together a group of researchers with expertise in relevant content, technology, and method domains to accelerate and guide progress in this important area.
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.
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.
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.
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, with the goal of identifying challenges, opportunities, and pitfalls, and create a compelling report that will effectively inform future federal priorities—including future AI R&D Investments. The final report is now available.
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. '>
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 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.
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.
The overall objective of this workshop was to identify academic research challenges in PQC migration and cryptographic agility. That is, organizers wanted to identify aspects of the complex and global migration to new public-key cryptography standards that could benefit from a more rigorous study and analysis.