This course covers issues in the practices of translating phenomena to data and algorithmic description. What happens, what is gained, what is lost, when things that happen in the world are recorded and made into information or recorded as a document? The course explores representation, modeling, correctness, reliability, and bias in different types of data and algorithms. We will learn about diverse topics such as cultural and algorithmic bias, challenges of big data, what happens when the world is transformed into images, what are the implications of having your social status determined by data and scores on your social media profile, and what we gain or miss when we deal with geographical information systems.
Pre-requiste courses: INF301H1 – Introduction to Information
and Power and INF302H1 – Integrative Approaches to Technology and Society, or permission from the instructor