Mapping the Impact Universe of the Internet of Things

Information Technology/Law/Policy/Environmental Science/Computer Science/Engineering

Internet of Things (IoT) systems—self-driving cars, precision agricultural systems, smart home environments—are usually developed to optimize for business value and technical performance. Yet the design of these systems also has dramatic impacts on societal governance and planetary sustainability. For example, broad sharing and exchange of private consumer data gathered by smart systems has created momentum for new legal and policy controls on data access and use. Technical decisions about whether your networked appliance is upgraded via software or hardware may impact the planet’s supply of materials, level of e-waste, and sustainability.

In this project, students will work as a team to develop an impact universe for a specific IoT system—likely self-driving cars—to expose the impacts of key design decisions in the system’s life cycle. Each team member will be in charge of a particular area—social impact (relevant law and policy), environmental impact (impact on power, materials, and planetary sustainability) or technological impact (architecting systems for robustness, efficiency, safety, security, data management, and interoperability). Students will gather information from a broad set of readings, experts, and resources to explore their area. We will work together to create a synergistic impact universe that both exposes key decisions and shows their trade-offs. Although we have distinct goals for our work, we will draw inspiration from the multi-perspective approach of Anatomy of an AI System (https://anatomyof.ai/).

Ideal students for this project are curious, independent, multidisciplinary, thorough, and collaborative. Familiarity with information technology and expertise in (one or more of) law/policy, environmental science, computer science, or engineering would be ideal. The project should provide great experience in doing research—navigating the unknown and learning how to structure information to make sense of it—to answer important questions.