Data, Privacy, and Ethics
Paying for items at the grocery store has become automated thanks to self-checkout stations. Grabbing a coffee at McDonalds involves plugging an order onto a screen. These and other new technologies positively and negatively impact society. For instance, many of these now automated procedures were once occupations, and research shows that automation is displacing jobs that would normally serve underrepresented communities. What's more is that these machines store your information: what you bought, how many items, and at what time you made the purchases. The internet and various social media websites store even more information that is bought and sold to companies and organizations. Thus, should it be permissible for automation to replace workers? What is and isn't moral use of such information? Who is responsible if a machine does something wrong? Are there scenarios in which an organization should not have access to data? In this class, we will explore these questions and other normative questions on data-driven technologies by way of case studies on particular topics. We will the explore the following topics: data ownership, surveillance and privacy, algorithmic bias and its solutions, misinformation, 'the black box problem,' opacity in machine learning, and societal implications of automaton. Authors to be read include Emmanuel Mesthene, Cathy O'Neil, Wendell Wallach, Frances Haugen, Sina Fazelpour, David Boonin, and more. Some relevant movies that touch on these topics include Chappie, Coded Bias, the Minority Report, and the Great Hack.
|Gen Ed Area Dept:
|Course Format: Lecture
|Grading Mode: Student Option
|Fulfills a Major Requirement for: (SISP)(SISP-ScieDblMjr)
|Past Enrollment Probability: 75% - 89%