DB @ IMPAKT

Youtube & Chill

(it’s a trap)

David Benqué
Speculative Interfaces
IMPAKT Festival 2019

Covington, P., Adams, J. and Sargin, E. (2016) ‘Deep Neural Networks for YouTube Recommendations’, in Proceedings of the 10th ACM Conference on Recommender Systems. Boston, MA, USA: ACM (RecSys ’16), pp. 191–198. doi: 10.1145/2959100.2959190.

a user-friendly interface that maintains the perception of choice but also directs the viewer toward content more likely to keep them engaged and subscribed

Arnold, S. (2016) ‘Netflix and the Myth of Choice/Participation/Autonomy’, in McDonald, K. and Smith-Rowsey, D. (eds) The Netflix Effect: Technology and Entertainment in the 21st Century. Bloomsbury Publishing USA.

Seaver, N. (2018) ‘Captivating algorithms: Recommender systems as traps’, Journal of Material Culture, p. 1—16. doi: 10.1177/1359183518820366.

image: Nets & More

the funnel is starting to look a bit more bleak

Anthropologist Nick Seaver characterises these recommendation systems as traps.

and he talks in particular about traces.

the move away from predicting explicit ratings,

e.g. NETFLIX trying to predict how many stars, to using implicit data.

traces left by users unwittingly, gathered through interaction logs,

much more abundant data, you can gather more and more aspects rather than one score

more accurate than explicit ratings, this is a classic of digital positivism, the algorithm knows you better than you know yourself, has been repeated quite a few times about facebook.

I want to try and do some justice to Seaver’s argument, he actually argues that we should go beyond a simple polarity between control and freedom. so hold this thought and I will come back to this at the end.

Tufekci, Z. (2018) ‘YouTube, the Great Radicalizer’, The New York Times. Available at: https://www.nytimes.com/2018/03/10/opinion/sunday/youtube-politics-radical.html (Accessed: 1 October 2018).

Landrum, A. (2019) ‘YouTube as the Primary Propagator of Flat Earth Philosophy’, in Symposium at the American Association for the Advancement of Science (AAAS). Washington, D.C. Available at: http://www.asheleylandrum.com/uploads/4/7/8/3/47833717/landrum_2019_02.18_aaas_online.pdf.

Paolillo, J. C. (2018) ‘The Flat Earth phenomenon on YouTube’, First Monday, 23(12). doi: 10.5210/fm.v23i12.8251.

#YouTubeRegret, Mozilla

Roose, K. (2019) ‘The Making of a YouTube Radical’, The New York Times. Available at: https://www.nytimes.com/interactive/2019/06/08/technology/youtube-radical.html (Accessed: 12 July 2019).

Chaslot, G. (2016) ‘Youtube-explore’. Available at: https://github.com/pnbt/youtube-explore (Accessed: 17 October 2018).

‘the world’s first window into YouTube’s opaque recommendation engine’

Lewis, P. and McCormick, E. (2018) ‘How an ex-YouTube insider investigated its secret algorithm’, The Guardian. Available at: https://www.theguardian.com/technology/2018/feb/02/youtube-algorithm-election-clinton-trump-guillaume-chaslot (Accessed: 1 October 2018).

Lewis, P. (2018) ‘’Fiction is outperforming reality’: How YouTube’s algorithm distorts truth’, The Guardian. Available at: https://www.theguardian.com/technology/2018/feb/02/how-youtubes-algorithm-distorts-truth (Accessed: 17 October 2018).

SEEING ≠ KNOWING

Ananny, M. and Crawford, K. (2016) ‘Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability’, New Media & Society, pp. 1–17. doi: 10.1177/1461444816676645.

https://davidbenque.com/projects/architectures-of-choice/

I challenge the authors to pull out 1 single compelling path of content, so I can map this global diagrammatic contouring, with what actually matters to ME, the USER.

— Reviewer 1

[hunters] by interpreting a series of traces, reconstruct the appearance of an animal they have never seen

Ginzburg, C. (1980) ‘Morelli, Freud and Sherlock Holmes: Clues and Scientific Method’, History Workshop, 9, pp. 5–36. Available at: www.jstor.org/stable/4288283.

Fluo-Green project, Université de Namur

https://sites.google.com/site/fluogproject/

Marenko, B. (2018) ‘How to Speculate: AI and the FutureCrafting of the Algorithmic Imagination’, in DRS2018 [NOT ACCEPTED].

dat://yt-trace.davidbenque.com

↳ Open in Beaker Browser
↳ Turn on live-reloading ⚡

https://adr.diagram.institute

More to Love, Angèle Cottet, AliExpress

Road to Coca-Cola, Ferdinand Benguigui, Carrefour

Linked|nfiltration, Émile Rebours & Louise Viollet-Deval, Linkedin

Post-API methods

Spotify Teardown is, in part, a book about method: how does one study someone who doesn’t want to be studied and (unlike Spotify’s users) has the power to enforce that wish?

James, R. (2019) ‘Financial Music’, American Book Review, 40(6), pp. 13–14. doi: 10.1353/abr.2019.0116.

see also: Digital Methods Initiative (2019) ‘Post-API Research? On the contemporary study of social media data’, Digital Methods Initiative. Available at: https://wiki.digitalmethods.net/Dmi/WinterSchool2020 (Accessed: 10 October 2019).

a problem we had to think about, especially because it wasn’t a coding workshop is

how to collect data from platforms?

increasingly closing down APIs and access? (what was the access to in hte first place)

This is very well put by Robin James in her review of Spotify Teardown.

how does one study someone who doesn’t want to be studied?

digital methods initiative is setting up some work in what they call Post API research

THX: Silvio Lorusso, and Aymeric Mansoux for the links on mastodon

the important thing here is the HOW

coming back to conjectural knowledge,

important to not reduce WHAT we can know about platforms to access to data

but HOW we know, challenge digital positivism in the very way that we gaze back at these systems.

include and embrace speculation and conjecture

on way to summarise this critical position: you’re not gona tell us, fine we’ll imagine the worst things about you, or make fun of you, or whatever

this is not without its dangers, conjecture doesn’t mean good

but still there is an important line there

To be caught at this speed is not to be dead, rather it is to be enclosed, known, and subject to manipulation. […] But to be caught at this speed is also to be hosted—to be provided with conditions for existence that facilitate activity while constraining it.

Seaver, N. (2018) ‘Captivating algorithms: Recommender systems as traps’, Journal of Material Culture, p. 1—16. doi: 10.1177/1359183518820366., emphasis added

The question to ask of traps may not be how to escape from them, but rather how to recapture them and turn them to new ends in the service of new worlds.

Seaver, N. (2018) ‘Captivating algorithms: Recommender systems as traps’, Journal of Material Culture, p. 1—16. doi: 10.1177/1359183518820366.

FIN

David Benqué
davidbenque.com
@davidbenque
@air_pump@post.lurk.org

icons: forkaweso.me
font: Operator, Hoeffler & Co.