Venue: Stanford University, Palm Dr, Stanford, CA 94305
Room Number: History 200-030 (Lower Level)
Street Address for GPS: 450 Serra Mall, Stanford, CA 94305
Video Archive of All Talks
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. We seek to bring together AI researchers and researchers/practitioners/experts/policy makers from a wide variety of domains.
The focus on this symposium is on a broad scope of research topics. Almost any real-world problem, which is important for society’s benefit, and could potentially be solved using AI techniques, is within the ambit of this symposium. For example, in “urban computing”, (i) efficient management of traffic lights allows for smart flow of traffic through a city; (ii) spatio-temporal GPS data from various sources is used to predict traffic volume at various places and times in cities, which powers recommendation systems providing smart driving directions to commuters; (iii) GPS trajectories of taxicabs are utilized to detect flawed urban planning of newly built roads and subway lines; and (iv) aggregate level gas consumption and pollution emissions patterns of vehicles in different parts of a city are predicted using machine learning techniques, which can be used to identify “gas-efficient” driving routes. In the field of “healthcare”, (i) companion pet bots have been built which provide emotional support and monitor senior citizens for signs of depression; (ii) AI based virtual nursing assistants have been developed which follow up with patients after they have been discharged from hospitals; and (iii) sequential planning algorithms have been used to efficiently spread awareness about dangerous diseases such as HIV among disadvantaged populations such as homeless youth. In the field of “public welfare and social justice”, (i) data-driven early intervention systems have been built which pro-actively identify police officers likely to have adverse interactions with the general public, thereby harming police-public relations; (ii) decision support systems are in place which identify high-school students who are likely to need additional support so that they can complete high-school in time; and (iii) game theoretic techniques are used to determine the optimal government policies that would alleviate poverty in the most efficient, sustainable manner. In the field of “sustainability”, software assistants based on game theory recommend patrol plans to wildlife park rangers for protection of tigers and rhinos (among other animals) from being killed by well-organized poachers; (ii) spatio-temporal models for bird species distributions are built, which allows accurate visualization of migratory patterns of many birds; and (iii) sequential planning algorithms are used to decide which areas of coastal habitat to protect in order to minimize sea level rise. Finally, in the field of “security”, (i) software assistants based on game theory (a subfield of AI) have been developed for generating randomized patrol plans to protect important infrastructure such as ports, airports, flights, transit systems; (ii) AI techniques are used to decide where to place honeypot bots inside a computer network to fool hackers; and (iii) multilateral relations between countries are inferred from sparse dyadic political events using machine learning techniques.
While there has been significant progress, there still exist many major challenges facing the design of effective AI based approaches to deal with the difficulties in real-world domains. The symposium will serve two purposes in this regard. First, the symposium will provide an opportunity to showcase real-world deployments of AI based systems for social good. More often than not, unexpected practical challenges emerge when solutions developed in the lab are deployed in the real world, which makes it challenging to utilize complex and well thought out computational/modeling advances. Learning about the challenges faced in these deployments during the symposium will help us understand lessons of moving from the lab to the real world. Also, there is a need to build AI based systems which dynamically adapt to changing environments, are robust to errors in execution and planning, and handle uncertainties of different kinds that are common in the real world. Addressing these challenges requires collaboration from different communities including artificial intelligence, game theory, operations research, social science, and psychology. This symposium is structured to encourage a lively exchange of ideas between members from these communities. We encourage submissions to the symposium from: (i) researchers who have used (or are currently using) AI techniques to solve important real-world problems for society’s benefit in a measurable manner; and (ii) researchers/practitioners/domain experts from new social domains which could benefit from the introduction of AI based systems.