Institutional Transformation: Anticipating Undesirable Consequences of Computer Science Research

Computer Science research has greatly contributed to technological progress, but it has also led to developments that have had unintended and sometimes harmful effects on society. For the researchers designing computing innovations, anticipating undesirable consequences of those innovations can be difficult due to a lack of knowledge and support for how to investigate such consequences. Thus, the aim of this research project is to enable computer science researchers to identify and assess the potential undesirable consequences of their innovations. The project will develop and evaluate a new approach to anticipating undesirable consequences of digital technology. The approach will help computing science researchers better understand the processes and resources for examining the ethical dimensions of their work. The project has the potential to transform how computing programs and other academic departments integrate ethics into their curriculum. The research team aims to develop and test the effectiveness of interventions that incentivize anticipating undesirable consequences of computer science research projects as early as possible, when pivoting a project’s approach is still feasible. Specifically, the team will design a web-based system that enables computer science researchers to: (a) access and contribute case studies of negative societal impacts of computing research projects and lessons learned, (b) brainstorm about undesirable consequences of computing projects and preregister the outcome of the brainstorming activity including potential mitigation strategies, (c) involve other researchers in the brainstorming and review of the ethics preregistration, and (d) have access to an ethics advisory board of individuals with a broad range of scholarly backgrounds. A key component of the team’s approach is that ethics preregistrations will be reviewed by other research groups, which fosters knowledge sharing and collaboration among the groups. This project is funded by the Directorate for Computer and Information Science and Engineering and managed by the ER2 Program of the Directorate for Social, Behavioral and Economic Sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.