View on GitHub


Two computer scientists and a cultural scientist get hit by a driver-less car: A method for situating knowledge in the cross-disciplinary study of F-A-T in machine learning

FAT*‘2020 Translation Tutorial #4

This tutorial will build on the experiences gained in a previous workshop, where a group of artists, computer scientists, lawyers, activists, and social scientists collectively read and discussed a computer science paper. Here, we seek to replicate and test the practice of cross-disciplinary, collaborative paper-reading to a community interested in influencing, and being influenced by, the insights into methods that are available from fields external to their own. We will come to the tutorial having read a set of papers, and then have a discussion for about 40 minutes in small groups about what we read and how we read it. We will invite people to take on roles as ‘interpreters’ and ‘translators’; we will pair people from different disciplinary backgrounds to take on these roles in a group. We will then re-convene to share notes on how the discussions developed: the moments where the different standards, goals and epistemologies across disciplines emerged, and how we dealt with them; how and if this is relevant to working in F-A-T disciplines; and to critically assess how and if this method might work in a classroom or other pedagogical context.

Who will be delivering this tutorial?

Who is the target audience?

We welcome researchers from any discipline motivated by the challenges and opportunities in working on questions of technology and society. As multi-disciplinary insights are a key component to this workshop, the intended audiences range widely, and we actively seek to minimise barriers to entry, to facilitate as wide a conversation as possible. We believe that most participants at the FAT* conference stand to gain from the in-depth disciplinary insights which will become apparent through this conversation. We acknowledge that the variety of experiences and backgrounds in the room might create some challenges – but that is precisely the point of this exercise. We want to find ways to foster communication and understanding across our differences.

Instructions for participants

We have a set of papers that we would suggest participants read – or attempt to read – beforehand. With the time available for the tutorial, we have decided for thematic coherence over diversity. So we made F-A-T in NLP our focus. We encourage you to read two papers from this list – one in a discipline that appears completely new and unfamiliar and Donna Haraway’s paper on situated knowledge that has framed this tutorial, and is considered inspirational to many of us working on these topics. We would like you to highlight pieces of text that are important to you in the papers you read and tell us why they are important; make notes; write down questions you have. Also, try to pay attention to how you find it reading from another discipline. There might be some basic things that are obviously different like the length of the paper, referencing and how it is laid out; and more substantial things like the way arguments are framed, how other literature is referenced, how conclusions are arrived at. And that’s just aside from how something is difficult to follow because you are not familiar with the material. Try to make a note of what you find challenging, what surprised you, and what you did not understand. How do you think you might benefit from reading a paper about your topic or area of study written from another disciplinary perspective and position? We want to hear about your experiences of reading and how you think this might give you insight into working across disciplines.


13:00-13:20: Introductions

13:20-14:00: Small group discussions

14:00-14:20: Plenary discussion

14:20-14:30: Wrap up