We develop statistical methods that can be used for development and evaluation of digital technologies in service of societal impact. We focus on tools that support personalization, experimentation, and effective innovation.
Our methods allow organizations to efficiently implement a data-driven approach to innovation. We use machine learning methods to provide insight about how digital technologies can better meet the needs of disadvantaged individuals, and we tailor AI algorithms to address the identified challenges. We develop methods to support the implementation of efficient experiments so that organizations can innovate more quickly, guided by measures of social impact.
Our work is anchored in social science, where we consider the context of the individuals served by digital technologies as well as the institutional environment. We draw on existing research as well as advance the social science literature in areas where it is needed to guide the development of effective interventions. Where relevant, we propose incentive schemes that can be implemented by governments, philanthropists, or investors that better align the incentives of private innovators with social impact.
Helping organizations understand their data and utilize it to make their organizations, products, and services more effective; developing algorithms that tailor digital services to individuals with a focus on social impact.
Developing new approaches to the design of experiments; defining outcome measures that represent short and long-term impact; analyzing the results of experiments to yield insights about heterogeneity of impact; accelerating innovation through adaptive experiments.
Using data together with social science to identify barriers to mobility and well-being that might be addressed through digital technology; developing evidence about what types of digital interventions and nudges are most effective in different settings.
Working with governments, philanthropists, and investors to design incentives for innovation to better align innovators with social returns; designing incentives for participants in digital platforms (such as peer-to-peer lending or labor marketplaces) to improve outcomes for disadvantaged groups.