Social, Political and Ethical Dimensions of Data Science
A team led by Inés Valdez (Political Science) and Mark Moritz (Anthropology) is creating curriculum and tools for training data science students, researchers and professionals that consider how big data and algorithms might amplify pre-existing inequalities, discriminatory practices and power disparities. The team includes TDAI core faculty member Dennis Hirsch (Law), Dana Howard (Medicine/Philosophy), Samantha Krening (Engineering), Samuel Malloy (Public Policy) and Srinivasan Parthasarathy (Engineering).
The team is supported by the Translational Data Analytics Institute (TDAI) and the Kirwan Institute for the Study of Race and Ethnicity. Read more about the award here.
“As data science technology like artificial intelligence is adopted in every aspect of our society, ensuring that the people creating it are vigilant about its social implications is paramount,” said Berger-Wolf. “Something as seemingly straightforward as choosing data for training new tools can lead to biased outcomes that cause irreparable damage to people’s lives.”