While data and artificial intelligence are driving many changes to our economic, social, political, financial, and legal systems, we know surprisingly little about their foundations and governing dynamics. While the recombination and integration of diverse data creates vast new value, we currently have neither theory for how data can be combined nor an industrial policy for how to protect against the personal exposures and abuses that grow in proportion. Many of these issues call for treating data as a first-class citizen and thinking of it as an asset. What is the value of data? and how do we measure it? This course explores these questions from the perspective of different communities including computer scientists, economists, social scientists, among others. Students who complete the course will have defined and explored a topic related to ‘the value of data’ in-depth, including the motivation, execution, rigorous evaluation, and exposition of the work. Lectures will seek active discussion among peers and will be complemented with weekly readings.
The course can be taken pass-fail or for a letter grade. For a letter grade, you need to complete an individual, quarter-long, data science oriented project. You also need to attend classes, participate in discussions, and scribe for two/three classes. For pass-fail, you do not need to complete the individual project but all other requirements apply.
Instructor: Raul Castro Fernandez (email@example.com)
Lectures: Tuesday and Thursday 9:30am–10:50am (Central Time)
Prerequisites: Permission from the instructor.
Coursework: The bulk of the grade for this class corresponds to an individual, quarter-long project. See grading below.
Office Hours: You can use office hours to discuss any topic we cover in class. I expect most students will use office hours to discuss their individual projects. Times will be available soon.
Canvas Site: Go here
Zoom: We will use this zoom link for the lectures and discussions. Requires a uchicago account and a password you’ll receive separately.
- Course Project (80%). Quarter-long project based on seed ideas or proposed by the student and agreed upon during the first week.
- Class Participation (10%). Read the reading assignments and participate in discussions during class, office hours, and online.
- Class Scribing (10%). Students are responsible for scribing 2 classes. Good scribing should be organized, should capture the content and discussions during the class, and should be useful to other students.
The schedule is available here. Check it out frequently as it’ll likely change a bit throughout the quarter.
The schedule combines lectures with discussion-based sessions led by the instructor as well as workshops, where we all work together on an open question. Most lectures and discussion sessions require working on some readings before class. We will cover topics that include: data science, the 4th paradigm of science, data lifecycles, privacy, FAIR principles, the value of data from a macro perspective, the value of data from within an organization, sharing platforms, auction-based markets and other mechanism design topics, personal data markets, privacy, ethics, ownership of data, data unions cooperatives, data dividends, as well as other markets of information.
UChicago Health Pact
All students on campus are required to adhere to the guidelines in the UChicago Health Pact in order to promote a safe environment in the classroom.
Secure face coverings must be worn appropriately at all times at all times while in University buildings
Maintain a distance of 6 feet from others
Do not attend and in-person class if you feel unwell or are experiencing COVID-19 related symptoms
The complete text of the UChicago Health Pact along with additional information about COVID-19 protocols can be found here.
Any concerns over inappropriate PPE usage, physical distancing, cleaning/disinfection, or other COVID-19 related public health concerns should be directed to UCAIR. If there is an emergency, call 773-702-8181 or dial 123 on any campus phone.
If you were potentially exposed to COVID-19 or your COVID-19 test results come back positive, reach out immediately to C19HealthReport@uchicago.edu.