Prof. Laura Nelson to teach new course on the intersection between data and society



UBC Sociology Professor Laura Nelson’s new course, Data and Sociology, explores the many ways data and algorithms impact, and are impacted by, society. The course will particularly explore the ways in which data and algorithms are implicated in various forms of social inequality, in both positive and negative ways.

We spoke to Prof. Nelson about what students should expect from her class.

Prof. Laura Nelson


What will this class cover, and why did you choose to focus on the intersection between data and society?

Data, algorithms, AI – these buzzwords are seen everywhere these days. Some claim the world is on the precipice of revolutionary changes: AI, data, and algorithms will change for the better the way we do virtually everything, from shopping, to turning on our lights, to the way we work, to the way we administer health care. Others claim that we are on the precipice of societal and democratic collapse, due in no small part to the negative impact of data, algorithms, and “big tech” on society, from surveillance, to misinformation, to escalating polarization.

The reality is, of course, somewhere in between these two extremes. But understanding the multiple ways data and algorithms are intertwined with society is one of the most important questions facing society. This course focuses on this intersection, with a particular focus on how this intersection impacts various inequalities in society.

What do you hope students take away from this class?

Data shapes our lives in many ways. Some we are aware of, some not so much. I seek to help students become “digital citizens”: active participants in shaping how technology impacts society, whether from the technical side, the social or policy side, or both.

I hope the students will come away from this class with an informed and critical understanding of how and why data matters in contemporary society, the history leading up to this moment, how data might impact our future, and how we might intervene to construct a future we all not only want to to live in, but thrive in.

Additionally, understanding the intersection of data and society is crucial for many jobs. I thus designed the assignments with the hope that many of the completed assignments can be included in students’ general portfolios. The assignments will require creativity, with the goal of showcasing to future employers the skills and insights developed in the course

How would you describe your teaching style?

My main approach to teaching is experiential and active. I rarely lecture, but prefer to have students do hands-on activities with real-world implications.

This course is open to all majors. What should interested students not familiar with social or data science expect?

Absolutely no previous knowledge about computers, data, algorithms, and/or programming is expected or required to take this course (really truly!). The class will be of particular interest to those in the social sciences and humanities who are interested in learning more about how data and algorithms are intertwined with social systems, and to those in computer and data science who are interested in learning about the potential impact of algorithms on social systems and how to use algorithms for social good.

Activities and assignments in the class will mainly cover conceptual issues, but we will also do hands-on activities to learn a little bit more about the computers shaping our (and your!) lives, and we’ll implement and explore how algorithms process real-world data and the output from those algorithms.

Is there anything else you’d like students to know about this course?

I love having a mix of social science, humanities, and computer science students in class. In interdisciplinary classrooms students learn from seeing how other disciplines view and approach similar problems, and these spaces force us out of our disciplinary bubbles. I encourage those from across campus to consider taking this course!