Programming Methodology

Learning goal: Gaining familiarity with ethical thinking about computing technology.

Topic: Values

Description: This lecture introduces students to the distinction between descriptive and normative language, the concepts of bias and fairness, the ethical implications of problem formulation, issues of representation in data, and the ethics of image manipulation.

Learning goal: Learn the history and basics of encryption and consider how it protects end user privacy.

Topic: Privacy

Description: This lecture introduces students to the basics of encryption as a way to protect end-user privacy. The lecture introduces students to basic encryption terminology and how encryption is used to send messages privately over the internet. Students are also introduced to end-to-end encryption, and the different privacy guarantees of various encryption protocols. Students consider the limitations of encryption’s ability to resolve certain privacy concerns.

Learning goal: Consider how values impact the entire life cycle of the scientific and engineering process, from problem formulation, to data collection, to data interpretation.

Topic: Values

Description: This lecture introduces students to values and how they are encoded within different parts of the scientific and engineering process. Students will learn the distinction between descriptive and normative language and data biases.

Learning goal: Understanding the biases that can manifest in AI-generated text.

Topic: Fairness/Bias

Description: In this assignment, students write a choose-your-own-adventure game that harnesses the power of generative AI. In the end, they are asked to think about the ethical implications of using generative AI in storytelling applications.