How can we know what algorithms do? While much contemporary debate around software in scholarly, journalistic, and popular discourse addresses the prevalence of algorithmic mechanisms in shaping our lives, less attention is given to specific algorithms and the precise processes by which they pattern our culture, communication, and socioeconomic activity. This class will endeavor to develop a toolbox of techniques for interpreting algorithms, including reading code, black box testing, interactive debugging tools, variable value tables, diagrams, various methods of visualization & sonification, and other experimental practices like embodied movement or dance. The course will launch with study of Alan Turing’s abstract machine and the notion of the algorithm itself, then step through several units, each focused on a specific algorithm drawn from computer science’s rich library. Examples may include: searching, sorting, and encrypting data; determining routes and paths in a network; making recommendations for objects like songs or films; or generating realistic texts and images. Students will foster their algorithmic literacy, learning how to read and understand computer program code to develop a hermeneutics of the algorithm, while also attending to broader social, cultural, and political questions such as: How do we know when algorithms are biased? Should we have law and policy mandating algorithmic audits? How should data journalism report on algorithmic operations? No prior coding experience is required but students are advised to first take LCOD 2000, as well as LCOD 2010, 2012, or 2013. Access to a working laptop will be expected throughout the semester.