Roderic Crooks writes from UCI’s Datafication + Community Activism workshop (March 2019):
“There’s a very useful difference here: some people believe we can develop a liberatory data science, others argue that the intent of data collection is always (and has always been) to harm. I’m calling this our Audre Lorde problem”
Here, Crooks is referring back to Audre Lorde’s famous denounciation in 1984 that “the master’s tools will never dismantle the master’s house”:
“Those of us who have been forged in the crucibles of difference – those of us who are poor, who are lesbians, who are Black, who are older – know that survival is not an academic skill. It is learning how to take our differences and make them strengths. For the master’s tools will never dismantle the master’s house. They may allow us temporarily to beat him at his own game, but they will never enable us to bring about genuine change. And this fact is only threatening to those women who still define the master’s house as their only source of support”
As Crooks intimates, this is a fault-line that runs throughout all progressively-minded efforts to think about data justice, data for good and the like. If the intent of data collection is not always to harm per se, it could be argued that data collection is always undertaken with the intention to control. Certainly, a key question to ask of any instance of data collection is ‘what the underlying intent here?’.
So, if we do reject the notion of hegemonic data science then are the realistic alternatives? What are our data-related ‘differences’ and how might we make them strengths? In terms of our own research project, what does this mean within the context of compulsory schooling – as coerced and as constrained as school is? On the flip-side, if we choose to retain a hope for the prospect of a liberatory data science, it well worth remaining mindful of the deeper connotations and collusions that are implicit in doing so.