Improved transportation is a key predictor for upward economic mobility, and the relationship between transportation and economic mobility is stronger than that between economic mobility and factors like crime, the percentage of two-parent families, and elementary-school test scores. Real-time ridesharing services (e.g., Uber and Lyft) are often touted as sharing-economy leaders and dramatically lower the cost of transportation. However, how to make these services work better among low-income and transportation-scarce households, how these individuals experience these services, and whether they encounter barriers in enlisting these services is unknown. This presentation will uncover the feasibility, challenges, and opportunities of deploying real-time ridesharing services in underserved and transportation-scarce areas in Detroit, MI. This presentation will also discuss opportunities for new transportation models to address the unemployment needs of low-resourced populations.
Tawanna is an Assistant Professor at the University of Michigan’s School of Information and holds a courtesy appointment with the Electrical Engineering and Computer Science Department. Tawanna received her Ph.D. in Human-Computer Interaction (HCI) from Carnegie Mellon University. She also holds a M.S. in Human-Computer Interaction from Carnegie Mellon, a M.S. in Computer Science from the Oregon Graduate Institute School of Science and Engineering at the Oregon Health and Science University, and a B.S. in Computer Engineering from North Carolina State University. In collaboration with colleagues, Tawanna uses human-centered and participatory design approaches, and research from multiple disciplines (i.e., psychology, ubiquitous computing, law, sociology, economics, design, and health) to explore the ways in which technology can be used to solve real-world problems, particularly among disadvantaged communities.