Lost in translation: an interactive workshop mapping interdisciplinary translations for epistemic justice

There are gaps in understanding in and between those who design systems of AI/ ML, those who critique them, and those positioned between these discourses. This gap can be defined in multiple ways - e.g. methodological, epistemological, linguistic, or cultural. To bridge this gap requires a set of translations: the generation of a collaborative space and a new set of shared sensibilities that traverse disciplinary boundaries. This workshop aims to explore translations across multiple fields, and translations between theory and practice, as well as how interdisciplinary work could generate new operationalizable approaches.

We define 'knowledge' as a social product (L. Code) which requires fair and broad epistemic cooperation in its generation, development, and dissemination. As a "marker for truth" (B. Williams) and therefore a basis for action, knowledge circulation sustains the systems of power which produce it in the first place (M. Foucault). Enabled by epistemic credence, authority or knowledge, epistemic power can be an important driver of, but also result from, other (e.g. economic, political) powers.

To produce reliable output, our standards and methods should serve us all and exclude no-one. Critical theorists have long revealed failings of epistemic practices, resulting in the marginalization and exclusion of some types of knowledge. How can we cultivate more reflexive epistemic practices in the interdisciplinary research setting of FAT*?

We frame this ideal as 'epistemic justice' (M. Geuskens), the positive of 'epistemic injustice', defined by M. Fricker as injustice that exists when people are wronged as a knower or as an epistemic subject. Epistemic justice is the proper use and allocation of epistemic power; the inclusion and balancing of all epistemic sources.

As S. Jasanoff reminds us, any authoritative way of seeing must be legitimized in discourse and practice, showing that practices can be developed to value and engage with other viewpoints and possibly reshape our ways of knowing.

Our workshop aims to address the following questions: how could critical theory or higher level critiques be translated into and anchored in ML/AI design practices - and vice versa? What kind of cartographies and methodologies are needed in order to identify issues that can act as the basis of collaborative research and design? How can we (un)learn our established ways of thinking for such collaborative work to take place? During the workshop, participants will create, share and explode prototypical workflows of designing, researching and critiquing algorithmic systems. We will identify moments in which translations and interdisciplinary interventions could or should happen in order to build actionable steps and methodological frameworks that advance epistemic justice and are conducive to future interdisciplinary collaboration.