Is data science truly the “fourth scientific paradigm” and the harbinger of a new scientific revolution? If so, what moral implications does this revolution have for individuals and social groups in search of desirable futures? How should we conduct our lives in a datafied world? Should we be excited, grateful, apprehensive, or defensive? It is no secret that data science is armed with powerful computation technology, custom-tailored algorithms, advanced machine learning, and constantly expanding data sets. It uses optimization techniques that affect your personal life, your family, and your community. From college admissions to online purchases to medical information to music preferences to predictive policing, hundreds of decisions about you are made daily. Are these decisions ethical? Is data collected, managed, and interpreted in ways conducive to human dignity and autonomy? What steps can we take to mitigate the damaging effects of algorithmic biases? Is data justice possible in a surveillance state? What does it look like in practice? Can we become active participants in creating, managing, visualizing, and telling stories with our own data? We will examine these and other questions in our inquiry into the world of moral dilemmas posed by Big Data. We will read Cathy O’Neil’s Weapons of Math Destruction; investigate Joy Buolamwini’s work in The Algorithmic Justice League; watch and discuss documentary films examining human contexts of data science; conduct independent research; and create data art. You will gain a better understanding of how to become educated consumers of data, ethically grounded designers of future technologies, and responsible citizens in our data-driven world.
1. Students will be able to apply ethical theories to practices and real-world examples of datafied societies.
2. Students will be able to analyze cultural values and norms that shape the development of data-driven tools.
3. Students will be able to identify specific assumptions made through data-enabled algorithms and critically examine current and future opportunities for data justice.
4. Students will be able to create data visualizations using student-produced data sets.