Topics in the social, political, and cultural aspects of data and datafication. Explores social and philosophical implications of gathering, interpreting, and managing data. Topics include: data protection, visualization or sonification, data activism, big data, algorithmic bias and decision making, AI harms, big data, and the political economy of data. This course can be repeated twice for credit if the topics are different (up to a maximum of three times). Prerequisite: 17 CMNS units with a minimum grade of C- or 45 units with a minimum CGPA of 2.00.
Topics in the social, political, and cultural aspects of data and datafication. Explores social and philosophical implications of gathering, interpreting, and managing data. Topics include: data protection, visualization or sonification, data activism, big data, algorithmic bias and decision making, AI harms, big data, and the political economy of data. This course can be repeated twice for credit if the topics are different (up to a maximum of three times). Prerequisite: 17 CMNS units with a minimum grade of C- or 45 units with a minimum CGPA of 2.00.
