Welcome to INFO 88 Data and Ethics

This course provides an introduction to critical and ethical issues surrounding data and society. It blends social and historical perspectives on data with ethics, policy, and case examples—from Facebook’s “Emotional Contagion” experiment to search engine algorithms to self-driving cars—to help students develop a workable understanding of current ethical issues in data science. Ethical and policy-related concepts addressed include: research ethics; privacy and surveillance; data and discrimination; and the “black box” of algorithms. Importantly, these issues will be addressed throughout the lifecycle of data—from collection to storage to analysis and application.

Course Objectives

Upon completion of the course, students will 1) identify and articulate some basic ethical and policy-based frameworks; 2) understand the relationship between data, ethics, and society; and 3) be able to critically assess their own work and education in the area of data science. In particular, course assignments will emphasize researcher and practitioner reflexivity, allowing students to explore their own social and ethical commitments as future data scientists and information professionals.

For more information on the Data Science Education Program at UC Berkeley, please visit databears.berkeley.edu


Instructor: Anna Lauren Hoffmann

Email: annalauren@berkeley.edu

Office Hours: Tuesdays 2:00-3:30 PM

Office Hours Location: South Hall 302

Course Schedule

Module 1- Situating "Data" I: What is data?

Objective: to "shake loose" the idea of data as an object for critical and ethical inquiry

Reading(s): Module 2- Situating "Data" II: A pre-history of data

Objective: to explore some historical precedents of today's "big data" moment

Case(s): Censuses & Area Codes

Reading(s): Module 3- Ethical Toolbox I: Research and applied ethics

Objective: introduce and explore applied ethical frameworks for thinking about data

Case(s): Facebook’s emotional contagion experiment; OK Cupid match rank testing


Short Writing Assignment #1 due before start of class

Module 4- Ethical Toolbox II: Concepts of privacy and publicity

Objective: explore basic concepts of privacy and anonymity (access, control, and context)

Case(s): 2006 AOL search data release; Facebook “Taste, Ties, Time” data release

Reading(s): Module 5- Lifecycle of Data I (Part I): Issues in data collection and data mining

Objective: attend to ethical questions in the collection and mining of online data

Case(s): data mining, social games, consent, Terms of Service

Reading(s): Module 6- Lifecycle of Data I (Part II): Issues in data collection and data mining

Objective: (cont’d from Module 5)

Case(s): data collection, personal fitness trackers, and the Quantified Self


Short Writing Assignment #2 due before the start of class

Module 7- Lifecycle of Data II: Issues in data storage and security

Objective: explore ethical and privacy issues in data, information, and computer security

Case(s): educational data and students’ privacy

Reading(s): Module 8- Lifecycle of Data III (Part I): Issues in analyzing and exploring data

Objectives: building on discussions from Module 5, tackling ethical issues in data analysis

Case(s): “Spurious Correlations,” app design, data inclusion

Reading(s): Module 9- Lifecycle of Data III (Part II): Issues in analyzing and exploring data

Objectives: (cont’d from Module 8)

Case(s): Hurricane Sandy, marginalized populations, data exclusions


Final Essay Proposals due before the start of class


Module 10- Lifecycle of Data IV (Part I): Ethics of algorithms and automated systems

Objectives: building on Modules 8/9, examining consequences of automation and implementation

Case(s): algorithmic cruelty, data and discrimination

Reading(s): Module 11- Lifecycle of Data IV (Part II): Ethics of algorithms and automated systems

Objectives: (cont’d from Module 10)

Case(s): Google search, redlining, race, and gender

Reading(s): Module 12- Lifecycle of Data V: Issues in dissemination and evaluation of data

Objectives: Trace ethical challenges in the evaluation and communication of results

Case(s): Google Flu trends, United Nation Waste Crimes report

Reading(s): Module 13- Interrogating Data Science: Asking critical and ethical questions

Objectives: strategies for thinking pragmatically about ethics as an info professional

Student-generated session – readings to be chosen and lecture to be led by student groups, facilitated by instructor

Module 14- Data Futures: Thinking ethically, thinking ahead

Objectives: identify and explore ethical issues on data science’s horizons

Student-generated session – readings to be chosen and lecture to be led by student groups, facilitated by instructor

Module 15- Course Reflection: Revisiting our Data Doubles

Final Essay Projects due


Course assignments revolve around short, accessible styles of writing. Emphasis is placed not on writing for academics, but in writing for the broad potential audiences a data scientists or information professional might have the opportunity to engage—for example, co-workers, clients, or the general public. Assignments include both reflective writing (to get students thinking through their own ethical commitments and practices) and compelling argumentation (as in the form of a critical or persuasive blog post or newspaper op-ed).

Academic Integrity

The high academic standard at the University of California, Berkeley, is reflected in each degree that is awarded. As a result, every student is expected to maintain this high standard by ensuring that all academic work reflects unique ideas or properly attributes the ideas to the original sources. Individual departments often have their own ways of citing and attributing work, so it is the responsibility of each student to seek that information out if it is not otherwise provided through a syllabus, course website, or other means.

These are some basic expectations of students with regards to academic integrity:

Do not collaborate or work with other students on assignments or projects unless you have been given permission or instruction to do so. For more information visit: http://sa.berkeley.edu/conduct/integrity

UC Berkeley Statement on Diversity

These principles of community for the University of California, Berkeley are rooted in a mission of teaching, research and public service and will be enforced in our classroom this term.

For more information, visit UC Berkeley's Division of Equity, Inclusion & Diversity page: http://diversity.berkeley.edu/vcei

Learning Accomodations and Access

If you need accommodations for any physical, psychological, or learning disability, please speak to me after class or during office hours.

Additional Campus Resources

These additional campus units may, at times, prove helpful during the course of the semester: