SHOOTING FOR THE MOON MAKING SMART CITIES ETHICAL AND SUSTAINABLE From self-driving cars to smart buildings, new questions are arising as intelligent and autonomous systems become more and more a part of our daily lives. Who owns and benefits from all the data collected? Who do these solutions help and who might they leave out? How will they impact an environment already pushed to the brink by our current way of life?
“We used to build machines that did exactly what we told them,” says CEE Professor Mario Bergés. “Now we’re teaching machines to make decisions on our behalf and implement those decisions on the fly. It’s more vital than ever that our designs consider these ethical dimensions.” Bergés is the principal investigator on the Autonomous Technologies for Livability and Sustainability initiative, which won funding from the CMU College of Engineering’s Moonshot 2020 competition. United by a bold vision, the initiative brings together people from across Engineering as well as Architecture, Computer Science, Philosophy, and Heinz College. The group will also partner with industry and local government as they develop and test theories, methodologies, and technologies to solve wide-ranging ethical and sustainability concerns around autonomous systems. CEE Professor Greg Lowry is one of the seven CEE researchers involved. “A lot of people are working on smart cities. Very few people are thinking about how to implement those systems in a sustainable way that maintains people’s privacy and that is equitable across the board,” he says. “If you don’t prioritize and design those features into the system from the start, you’re going to discover that what you created encourages or enhances inequities.”
A Layered Approach: Sensing, Planning, and Acting
Mario Bergés (top) Greg Lowry (bottom) 12 CEE NEWS
Autonomous systems generally have three layers, and CMU researchers will start their project by addressing concerns in each one individually. The first layer is sensing, which involves collecting information about the outside environment. Next is planning, when the system learns from and analyzes data
