AI for Social Good - AAAI Fall Symposium 2019 Sponsored by the Association for the Advancement of Artificial Intelligence Westin Arlington Gateway, Arlington, Virginia, USA November 7 – 9, 2019 Website: https://ai-for-socialgood.github.io/ # Symposium Scope Recent developments in the availability of big data and computational power are continuing to revolutionize several domains opening up new opportunities and challenges. In this symposium, we highlight three specific disciplines where AI could be used for social good Humanitarian Relief and Development Planetary Intelligence from Spaceborne Imagery Responsible AI in Healthcare # Call for Papers This symposium solicits paper submissions from participants (2-6 pages) in either of the three disciplines described below: Humanitarian Relief and Development: Detecting and predicting how a crisis or conflict could develop, analyzing the impact of catastrophes in a cyber-physical society, and assisting in disaster response as well as resource allocation are of utmost importance, and the advances in AI can be utilized in many such tasks. This track will focus on all aspects of humanitarian relief operations supported by the novel use of AI ranging from enabling missing persons to be located, leveraging crowdsourced data to provide early warning for rapid response to emergencies, increasing situational awareness, to logistics and supply chain management. Planetary Intelligence from Spaceborne Imagery: We receive petabytes of image data from satellites every day that observes atmospheric processes, vegetation, and water bodies. Due to limited data assimilation techniques in practice, only a small fraction of these are used for extracting useful, actionable insights about our planet. This track will focus on computer vision and machine learning techniques applied on different types of imagery (satellite, drone, still and video capture, RGB, multispectral, hyperspectral, combination of imaging with other modalities) to address practical applications in the environmental and social sciences such as climate and weather prediction, urban planning, transportation systems, agricultural monitoring, and socio-economic development analysis. Responsible AI in Healthcare: Healthcare data, in general, is characterized by several data problems such as missing data, lack of standardization, incompleteness, etc. which hinders the deployment of solutions which are relevant to real-world use cases. Moreover, many AI solutions in healthcare have the "last mile problem" to deliver a practical solution. These have broader implications in the context of fairness, explainability, and transparency. This track will focus on a broad range of AI healthcare applications and challenges encountered including but not limited to: automation bias, prescriptive AI models, explainability, privacy and security, transparency, decision rights, and so on, especially in the context of deployment of AI in healthcare. Abstracts of the following flavors are sought: Research ideas Case studies (or deployed projects) Review papers Best practice papers Lessons learned Please submit your papers through the AAAI EasyChair site (choose 'AI for Social Good' track). The format is the standard double-column AAAI Proceedings Style. All submissions will be peer-reviewed. Some will be selected for spotlight talks, and some for the poster session. # Important Dates: Paper Submission Deadline: Jul 23, 2019 Online Registration Open: Aug 9, 2019 Paper Notifications: Aug 16, 2019 Camera Ready Deadline: Sep 13, 2019 Registratrion Deadline: Sep 20, 2019 Symposium Dates: Nov 7-9, 2019 # Organizers: Track 1: Humanitarian Relief and Development Dr. Hemant Purohit, George Mason University (Chair) Dr. James Hendler, Rensselaer Polytechnic Institute Dr. Mayank Kejriwal, University of Southern California Dr. Oshani Seneviratne, Rensselaer Polytechnic Institute Track 2: Planetary Intelligence from Spaceborne Imagery Dr. Kalai Ramea, Palo Alto Research Center (Chair) Dr. Raja Bala, Palo Alto Research Center Dr. Imme Ebert-Uphoff, Colorado State University Dr. Stefano Ermon, Stanford University Track 3: Responsible AI in Healthcare Dr. Muhammad Aurangzeb Ahmad, University of Washington and KenSci Inc. (Chair) Dr. Carly Eckert, University of Washington and KenSci Inc. Dr. Tae Hyun Hwang, Cleveland Clinic Dr. Ankur Teredesai, University of Washington and KenSci Inc.