Methods
We use two well-established methods in dance – improvisation and scores – in a virtual focus-group style format. No prior experience with these methods is required to participate in this project, but openness to moving and digging into embodied knowledge is!
Improvisation
We use improvisation and scores to investigate data professionals' responsibility and ability to mitigate algorithmic harms. This project understands improvisation as:
Attending to the patterns our bodyminds are thinking.
"Patterns our bodyminds are thinking" are deeply engrained experiences and perspectives (e.g., masculinity, safety, racism) that can be so familiar “that they are taken for granted and even recede from view” (Hare-Mustin 1994, p. 20). Studies have shown that arts methods like dance, drawing, or music among others help people “see what they are feeling or thinking” (Rubin 1999, p. 1) by surfacing preverbal patterns (Malchiodi 2011, p. 2).
This project uses improvisation to surface preverbal patterns our bodyminds may be thinking as data professionals in relation to various steps in algorithm design, implementation, and application. This method helps us identify where in our work our perspectives as people might be affecting our decision-making without our conscious awareness in ways that might perpetuate algorithmic harms down the road.
This project uses scores in the tradition of Fluxus, Judson Theater Group, and affiliated artists of multiple disciplines. These artists developed scores in the 1960s as structures for interdisciplinary collaboration that allowed for some type of spontaneity in collaborators' participation.
The images below show that a score can look like a set of text-based instructions like in Noticing Economic Transactions, abstract markings like in IBM for Merce Cunningham, or even be a pieces of tissue paper placed in a dance studio like in Tactile-auditory prompt. A score can really be anything – the arrangement of particular objects in space, a smell, or a taste experience among many other options!
What makes a score a score and not a set of instructions or object that assumes we'll engage with it according to particular social conventions, is our interpretation of something as an invitation to engage in improvised action. Importantly, when we encounter something to interpret, we are not only encountering its materiality, we are also encountering all of the economic, social, and political ideas built into it: an infrastructure. So all together, this project thinks of a score as:
An interpretation of an infrastructure as an invitation to engage in improvised action.
This project thus uses scores as a way to structure and frame our collective reflection as data professionals on our work and responsibilities for algorithmic harm in algorithmic design, implementation, and application.
Scores
Noticing Economic Transactions by iLanding Laboratory, 2015 (Monson, 2017).
IBM for Merce Cunningham conceptualized by Toshi Ichiyanagi, drawn and typed by George Maciunas (Carter 2012).
Tactile-auditory (TKI) prompt. (Batson & Sentler 2017)
Noticing Economic Transactions by iLanding Laboratory, 2015 (Monson, 2017).
References
Hare-Mustin, R. T. (1994). Discourses in the mirrored room: a postmodern analysis of therapy. Family Process, 33(1), 19–35. https://doi.org/10.1111/j.1545-5300.1994.00019.x
Malchiodi, C. A. (2011). Handbook of Art Therapy, Second Edition. Guilford Press. https://play.google.com/store/books/details?id=y6PY4hv47I0C
Rubin, J. A. (1999). Art Therapy: An Introduction. Psychology Press. https://play.google.com/store/books/details?id=JRRZqETdwMEC