Course Description
‘Data is the new oil.’ ‘AI democratizes wisdom.’ ‘The internet of the future will run on the blockchain.’ ‘Fusion can solve all our energy problems.’ ‘Luddism has never worked.’ The history of technological change is rich with such metaphors, narratives, frames, and future imaginaries. These ideological elements are essential for understanding the course and character of technological change itself, as they shape how actors perceive and conceive its promises and pitfalls, its possibilities and problems. In this course, we examine both the theory of ideas in politics and society, and the qualitative and quantitative methods used to empirically study them. For different ideational concepts—such as narratives—we will read both theoretical and empirical studies, and practically explore methodological approaches to studying them. These approaches range from qualitative frameworks such as grounded theory, to mixed methods like discourse network analysis, to computational techniques such as transformer-based topic modeling and classification. While some of these approaches require some background in R or Python and this course cannot substitute for an introduction to either, knowledge of them is not strictly required to successfully participate in this course.
