This is a guest blog post by Greg Hager, Computing Community Consortium (CCC) Past Chair and Professor in the Department of Computer Science at Johns Hopkins University, with contributions from Eric Horvitz the Technical Fellow & Managing Director at Microsoft Research and a past president of the Association for the Advancement of Artificial Intelligence (AAAI). In a recent blog post, we summarized the report of an academic/industry roundtable, which, among other recommendations, advocated for mechanisms to support long-term, strategic, and sustained conversation between academics and industry representatives. Yesterday, one such mechanism came into being with the announcement of the Partnership on AI by a consortium consisting of Microsoft, Google, Amazon, Facebook, and IBM. From the press release: The objective of […]

Contributions to this post were made by Greg Hager, Computing Community Consortium (CCC) Past Chair and Professor in the Department of Computer Science at Johns Hopkins University.  In June, the White House Office of Science and Technology Policy (OSTP) announced a new Request for Information (RFI) on Artificial Intelligence (AI), to solicit feedback on how the United States can best prepare for the future of AI. According to the OSTP Blog, they “received 161 responses from a range of stakeholders, including individuals, academics and researchers, non-profit organizations, and industry.” All of the responses are now public and can be found here. The Computing Community Consoritum‘s (CCC) submitted a response, which can be found here, after […]

The following is a guest blog post by Greg Hager, Computing Community Consortium (CCC) Past Chair and Professor in the Department of Computer Science at Johns Hopkins University.  What do you think your field will look like in 100 years? Speculating about the world a century from now may be too challenging, so what if instead a community took it upon itself to periodically assess its progress and potential nearer-term futures over time? How might such reflections influence the rate of progress, the types of problems that the field focuses on, the public perception of the work, or the ability to anticipate and address thorny ethical or policy questions? Today, the […]

The following is a Dear Colleague Letter from the National Science Foundation‘s Directorates for Computer and Information Science and Engineering (CISE) and Engineering (ENG), announcing their support of research that advances the positive use of Unmanned Aerial Systems (UAS).  August 8, 2016 Dear Colleagues, With this Dear Colleague Letter (DCL), the National Science Foundation’s (NSF) Directorates for Computer and Information Science and Engineering (CISE) and Engineering (ENG) announce their intention to support, foster, and accelerate fundamental research that advances the positive use of Unmanned Aerial Systems (UAS) to save lives, increase safety and efficiency, and enable more effective science and engineering research. These research investments will be made through existing […]

The AAAI 2017 Spring Symposium on AI for Social Good (AISOC) will be March 27-29, 2017 at Stanford University.  A rise in real-world applications of AI has stimulated significant interest from the public, media, and policy makers, including the White House Office of Science and Technology Policy (OSTP). Along with this increasing attention has come media-fueled concerns about purported negative consequences of AI, which often overlooks the societal benefits that AI is delivering and can deliver in the near future. This symposium will focus on the promise of AI across multiple sectors of society. The organizers are especially interested in addressing societal challenges, which have not yet received significant attention by the AI community […]

The following is a guest blog by Vasant G Honavar, a Computing Community Consortium (CCC) council member and a Pennsylvania State University professor. The emergence of “big data” offers unprecedented opportunities for not only accelerating scientific advances but also enabling new modes of discovery. Some have gone so far as to suggest that “big data” makes the scientific method that has characterized natural science since the 17th century, consisting of systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses, obsolete. Nothing could be farther from truth.   The reality is that, in many disciplines, the emergence of big data exacerbates the gap between our ability to acquire, store, […]