This week the Center for Data Innovation held a panel discussion on “Data for Social Justice: The Impact of Data on Underserved Communities” to discuss how data can be used to better address the needs of underserved communities across different fields, such as health care and education. The panel featured Samir Goswami, the director of Government Professional Solutions at research firm LexisNexis; Linda Loubert, an affiliate researcher at Morgan State University’s Institute for Urban Research; Nicol Turner-Lee, the vice president and chief research & policy officer at the Minority Media and Telecommunications Council; Christopher Wolf, co-chair of the nonprofit Future of Privacy Forum think tank and national civil rights chair of nonprofit civil rights group the Anti-Defamation League; and Christopher Wood, executive director of research and advocacy nonprofit the Lesbian, Gay, Bisexual, and Transgender (LGBT) Technology Partnership & Institute.
First, the panelists discussed some of their favorite examples of how data can be used to promote social justice. Wolf discussed using data to identify discrimination. Specifically, he pointed to research from the Urban Institute that used Department of Education data to identify school segregation and the National School Board’s work using data to identify racial disparities in students pushed out of school by suspensions. Wood argued that the LGBT community has not been adequately counted in official statistics such as the Census and that better data is needed to understand the needs of the LGBT community. Goswami stressed that while big data analysis is a useful tool, political will is required to actually make use of insights that analysis generates. For example, he helped conduct a survey of homeless youth in Chicago with the Chicago Coalition for the Homeless, which found that the number of homeless youth far exceeded the number of beds available in local shelters. However, more than a decade after the research was published, the city has only marginally increased its supply of beds. Goswami also spoke about his experience working for Amnesty International and partnering with DataKind and Purdue University to use paper records on human rights violations to predict emerging hotspots of violations.
Next, the panelists turned specifically to data in education and health care. Wolf stressed the need for better communication around data use in these areas, citing public pushback on initiatives such as the Common Core curriculum standard and the now defunct InBloom education data consolidation nonprofit. Wolf also mentioned the importance of data de-identification in contexts where personal information is being shared, noting that organizations can also use contractual approaches to ensure data holders do not re-identify individuals. Turner-Lee mentioned that employer-sponsored fitness programs that use connected health devices have lowered premiums for employees. Wood suggested using data to investigate socioeconomic issues associated with community college dropout rates and improve student retention. Loubert stressed that social researchers are having difficulty putting big data to use and that more coordination in this area could help produce more data-driven insights.
Finally, the panelists discussed how policymakers can help close the “data divide,” the social and economic inequalities that may result from a lack of collection or use of data about individuals or communities. Turner said she is encouraged by Apple’s recent announcement of Apple Pay, a mobile banking app that will come with the new iPhone 6 models, because most people of color carry cell phones and access to such an app could help democratize banking. Wood and Wolf agreed that policies that limit data-driven innovation could widen the divide. Goswami urged the audience to consider the data divide in developing countries as well.
The wide range of examples the panelists drew from underscores the fact that data can be a force for social justice across multiple fields and industries. The panelists agreed that it was a good thing that government agencies have begun thinking through the relationship between data and social justice, but that much more needs to be done, particularly on the data collection side, to better meet the needs of underrepresented groups.