ESR 2 Blog February 2022: Piu-Wai Chan

(A de-bias model built with the Fairmodel algorithm)

So, I finally made it to Zeppelin University this month. How very comforting it is to finally get my hands on a hard copy of Art and Cosmotechnics by Yuk Hui[1] from the university, and curl up on the sofa with my faux fur stole on a bright, crisp cold Sunday afternoon, as Bill Evan’s Quintessence plays softly at the background (It is often a difficult decision to pick between Chet and Bill.)  Oh, and of course, there is a cup of coffee made with beans from a local brewer—the smell of a latte mix with yesterday’s perfume lingered from the fur—it is warm, powdery, and cosy. This is probably my first quiet Sunday afternoon after a busy, buzzy period.

But busy is good (although my close ones did share a ‘How could you tell if you are burnt out’ article to me last month, interesting…)—it led you to have an energetic exchange with new ideas, new places and new people. For example, I was very honoured and (also fortunate, I believe) to be given an opportunity to offer classes on the topic of ‘socially engaged computing’ at Zeppelin University. I was pleasantly surprised when I found out the students who enrolled on the class are from a range of disciplines, namely politics, administration & international relations, sociology, economics & politics, and corporate management. This vibrant mix of research interests provides a very rich ground for critical and innovative exchanges—I must say that I was very impressed by how proactive the students were when it came to offering constructive critiques, challenges and supports to each final group project—they had to propose and present a new form of socially engaged computing. As I stressed at the start of the lecture, a concrete definition of socially engaged computing would not be ‘readily served on a plate,’ and the participants must work together to explore the possibility of constructively renewing social engagement with future technologies, maybe through theory, philosophy or even art.

In the spirit of conflicts and discussion as a form of engagement, we visited each oppositional discourse—such as Borgmann’s technological engagement[2] v.s. Verbeek’s technological mediation[3], Vallor’s technomoral virtue[4] v.s. Liu’s virtue-hoarding and professional managerial class[5] (one must listen to Liu’s interview with Chapo Trap House, where I first encountered the amusing term ‘SheEO,’) and Chun’s network science as a neoliberal construct[6] v.s. social computing studies. Then we did a technical and philosophical discussion on the very hot topic, data bias[7], where we looked at the leading de-bias algorithm line by line[8] (See header image. I modified and combined two scripts from the original source for demo purposes. The paper itself is also very fascinating, not only statistically speaking, but also in terms of political and ethical concerns—I must dissect this paper when I find the time.)

I asked:  ‘Is data bias a mathematical error?’ Many students responded by saying it is an innate industrial bias that is contributed by a racially hegemonic workforce. Yet, I found the answer from one student, Amelie, rather fascinating—‘It is a programmatic error not mathematical.’ That would inevitably lead us to the glorious debate on the essence and differences between mathematics and programming. But of course, it is a trick question in the first place—does neutrality exist?

It was a wild, conceptual roller coaster ride and I turned out to be a clumsy lecturer who often forgot to offer the students snack breaks – ( nonetheless, they perform brilliantly and propose all types of new techno-engagement including military technology, animal exploitation, disinformation, online dating, infused with high quality, energetic, critical debate through and through).

By merely looking back at that intensive weekend, I already have a smile on my face and cannot wait for the next collective, philosophical and technical adventure – however, before that, just let me stay on the sofa just a bit longer, and please pass me my perfume.


[1] Hui, Y. (2021) Art and Cosmotechnics. University of Minnesota Press.

[2] Borgmann, A. (1999) Holding On to Reality: The Nature of Information at the Turn of the Millennium. University of Chicago Press.

[3] Verbeek, P.-P. (2005) What Things Do: Philosophical Reflections on Technology, Agency, and Design. Pennsylvania State University Press.

[4] Vallor, S. (2016) Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting. 1st edition. New York, NY: Oxford University Press.

[5] Liu, C. (2021) Virtue Hoarders: The Case against the Professional Managerial Class. U of Minnesota Press.

[6] Chun, W.H.K. (2017) Updating to Remain the Same: Habitual New Media. MIT Press.

[7] Kantayya, S. et al. (2020) Coded Bias. 7th Empire Media, Chicken And Egg Pictures, Ford Foundation – Just Films.

[8] Wiśniewski, J. and Biecek, P. (2022) ‘fairmodels: A Flexible Tool For Bias Detection, Visualization, And Mitigation’, arXiv:2104.00507 [cs, stat] [Preprint]. Available at: (Accessed: 27 February 2022).

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