Charting the Moral Universe: Capturing Virtues and Values of Data Visualization Practice
Authors
Chloe Hudson Prock (Northeastern University), Enrico Bertini (Northeastern University), Michael Correll (Northeastern University)
Presentation
- Session
- How you show it makes a difference!
- Time
- Tuesday, Nov 10, 14:00 – 14:12 (US/Eastern) · session 13:00 – 14:30
- Location
- Hall Essex north
Links
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Keywords
Visualization ethics, Virtue ethics, Data visualization, Expert interviews, Qualitative research
Abstract
What do we value in our visualizations, and in the people who design them? Despite a growing body of work on critical data visualization, the conception of what it is to do ethical data visualization work can often be narrow (for instance, holding that our ethical duties are discharged merely by avoiding overtly lying or manipulating data), or entangled with potentially problematic implicit value structures (such as the assumption of the objectivity and neutrality of data, and so the designer’s role being merely the passive conveying of numbers as efficiently as possible). Yet, what it means to act ethically in data visualization is broad and multifaceted, and the virtues to which we should aspire as data visualization researchers and designers are worth explicating. We conducted an interview study with a broad spectrum of 20 experienced data visualization researchers, practitioners, and data artists to solicit their values and ethical considerations around doing visualization work. We report on a list of 68 values, organized into nine virtue clusters, that we encountered in our interviews. These virtues and values together describe a diverse space of matters of care and concern in data visualization: from the unease around the best use of visualization as a tool for persuasion, to the tightrope that visualization practitioners often walk between their professional responsibilities and their personal moral commitments. The virtues themselves, as well as our interviewees’ reflections on ethical practice, offer practitioners, researchers, and educators in data visualization a richer vocabulary for ethical reflection and provide a broader foundation for considering and applying visualization ethics.
For Practitioners
This paper may be interesting to a broad range of data visualization practitioners, including data journalists, visualization designers, data artists, freelance visualization consultants. It may also be of interest to data scientists more broadly. Practitioners could employ the papers values and virtue clusters as a reflective tool during the design process in order to prompt themselves to ask which values they are prioritizing and which they might be sacrificing. Rather than providing rigid ethical rules, the paper is meant to support building practical wisdom over time. To this end, it can also support practitioners by providing a shared vocabulary to recognize and openly discuss the tensions in their work.