Data-ing and Un-Data-ing
Angelika Strohmayer, Michael J. Muller · interactions · 2023
What if we start with the paper we wrote last year.In "Forgetting Practices in Data Sciences" [1], we talked about a lot of things related to Mimi Onuoha's [2] concept of data silences-systematic gaps in an otherwise rich dataset.In our analysis, datasets can be seen as dangerous or beneficial, but seldom neutral.We talked about selective legibility, or how data are ignored or suppressed; we picked up Joni Seager's idea that "what gets counted counts," and we built on that by talking about data genocide, where people say, "Oh well, there's not enough of those people to include in the dataset, or we certainly wouldn't separate them out and look at the differences in their circumstances."While all of this is happening, in an attempt to remain "objective" in data science work, we simultaneously want to assert that almost everything in our world is now data-data that is monetized-and that monetization and objectivity are often in service of different or even opposed priorities.Below is the outcome of a meandering conversation we had over a video call.We covered many different topics from a variety of perspectives and disciplines.After recording our chat, we tried to edit it into a more structured conversation for this piece, but we also wanted to keep some of the meandering.Michael Muller: Hi, Angelika!Would you be interested in talking a bit about "data-ing" and "un-data-ing" in HCI?In our CHI 2022 paper, we called into question the "objectivity" of data in machine learning.Along with Naja Holten Møller and Melanie Feinberg, we showed that humans shape the data in many ways.What are the implications for the "grand narratives" of data science, if the data are chosen, transformed, and even created by humans, and if the data are correspondingly dynamic and changeable?Angelika Strohmayer: Hi, Michael!Following on from that work, I'd like to think with you about what were to happen if we looked at data, in the data work and data science sense, differently?Data-ing and Un-Data-ing