Special Subject: Encoding Culture
MW 2:30-4, 1-277
Computers allow scholars and artists to study and play with media such as texts, images, audio, and numerical datasets with unprecedented scale and speed. These affordances open a world of opportunity for cultural production: artists can sketch, remix, and make on machines, and an individual scholar can access and analyze more and more varied cultural artifacts than ever before.
But what does it mean to model, create, or analyze these media on a computer? The humanities and arts are built on the fundamental understanding that nothing is binary, but computers only understand 1s and 0s!
What happens when we digitally encode culture?
This course explores this question, in the technical sense of how we represent these media as bits on a hard drive, and by considering the consequences of doing so. Students will learn the history and current practice of digitally encoding text, images, audio, and tabular datasets, along with the cultural and social issues implicit in these systems. They will apply computational methods for manipulating and analyzing encoded media, drawing from a wide range of practices including computational linguistics, audio processing, computer vision, and machine learning. In doing this work, students will confront underlying issues of what is lost and gained when we encode culture, and equip themselves to think critically about their own computing work.
After taking this course, you should be able to:
- Think and write critically about the opportunities afforded by and challenges inherent in digitally encoding and analyzing culture
- Describe the digital encoding schemes for the most common kinds of cultural artifacts
- Write Python programs that use common libraries to perform quantitative analyses on text, audio, image, and tabular datasets, and interpret and present the results of such analyses
Visit https://encodingculture.dhlab.mit.edu for more info!