Jennifer Pan, Professor of Communication and FSI Senior Fellow at Stanford University, began the series with her talk, “Uncovering Online Censorship and Propaganda in China”. In her talk, Pan shares that we can learn about the goals of authoritarian regimes, like China, by studying their censorship practices at scale. She and her team of researchers have gathered and analyzed millions of social media posts to identify when–and why–censorship occurs in China.
Trina Reynolds-Tyler, Director of Data for the Invisible Institute, a Pulitzer Prize-winning investigative journalism organization, delivered a talk, “(Dis)Proportionate Impacts of Policing in Chicago”. Reynolds-Tyler described her work on Beneath the Surface, an initiative that she leads in collaboration with HRDAG (see Megan Price, below) which combines narrative justice with data science to investigate the intersection of gender-based violence and police misconduct. With Beneath the Surface, Reynolds-Tyler delves deeper into the data to more accurately identify and categorize shared experiences with police misconduct.
Megan Price, Executive Director of Human Rights Data Analysis Group (or HRDAG), followed with a talk that asks, “What is the Cost of Being Wrong”. HRDAG is a small non-profit with a team of data scientists that partners with human rights advocacy organizations such as the United Nations, Amnesty International, Human Rights Watch, and the Invisible Institute to answer questions or advance arguments that can be made better through rigorous data analysis. In her talk, Price highlights work done in Mexico to predict locations of mass graves and work done to predict the need for additional policing, comparing and contrasting the different costs and consequences if inaccurate predictions are made. At HRDAG, they strive to use technology carefully and assume a moral obligation to do the best and most accurate work possible in order to honor and respect the people that have shared their stories.
After the series of technical talks, Megan Price moderated a discussion panel, “Putting Our Values Into Practice in Data Science”, with panelists Jennifer Pan and Trina Reynolds-Tyler. Each described how important it is to have direct experiences and proximity to the people who are represented in the data, and in the absence of that, to seek out others who have those direct connections. Otherwise, you run the risk of missing an important question, or worse, misinterpreting what you’re finding in the data. Pan and Reynolds-Tyler also stressed the importance of shared experiences to galvanize collective action.
The use of data science to identify authoritarian censorship and human rights abuses is a powerful tool in the fight for justice and accountability. These talks and discussions from the WiDS Stanford conference shed light on the important work being done to uncover and address these issues. Data science has the potential to drive real change and to give a voice to those who have been silenced or overlooked.
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