Vectoral Spring

Diagrams for Critical Algorithmic Practice

David Benqué
Hybrid Futures
25.11.2020

image: Divergent vector field with embedded sphere Math Insight

A diagram is a perfect visual schema for posing impossible things, invisible forces, enigmas like the future—all posed as perfectly plausible vectors.

Sillman, A. (2020) ‘Notes on the Diagram’, The Paris Review. Available at: https://www.theparisreview.org/blog/2020/11/12/notes-on-the-diagram/.

Was the diagram also a form of violence?

Sillman, A. (2020) ‘Notes on the Diagram’, The Paris Review. Available at: https://www.theparisreview.org/blog/2020/11/12/notes-on-the-diagram/.

It is not a question, however, of two fundamentally different types of diagram; rather, this oscillation between systematising and openness is inherent in the diagram.

Leeb, S. (2017) ‘A Line with Variable Direction, which Traces No Contour and Delimits No Form’, in Gansterer, N. (ed.) Drawing a Hypothesis. de Gruyter.

this talk is about diagrams as a language for engaging critically with algorithmic systems and their predictions, especially from a position in creative practice, and especially in a moment where AI is being hyped up, including by Adobe the main provider of design software.

diagrams are useful because they:

are compatible with the computer science
speak to an art/design sensibility
they provide an entry point and a frame for critical practice

By language I mean a way to read algorithmic systems as diagrams,
and a way to write when producing new work.

This language is not limited to making diagrammatic images, you can think/speak/research/design in diagrammatic ways.

diagrams are not just pictures, they should not be confused with schemas or visualisations, the key difference being that they do not claim a likeness to the object they represent but only describe a set of relations

a lot has been written about diagrams in computer science, semiotics, even philosophy

from a position in design, I draw from some of these in order to inform practice. What I find particularly generative is this stretchy nature of the diagram that allows it to extend from the very core of algorithmic operations all the way to critical theory.

what Kenneth Knoespel calls: the schozophrenic nature of diagram

Vectors

sepal_length	sepal_width	petal_length	petal_width	species
5.9	3.0	4.2	1.5	versicolor
4.4	2.9	1.4	0.2	setosa
7.7	2.8	6.7	2.0	virginica
6.4	2.8	5.6	2.1	virginica
5.4	3.0	4.5	1.5	versicolor
…	…	…	…	…

Excerpt from the Iris dataset
Anderson, E. (1936) ‘The species problem in Iris’, Annals of the Missouri Botanical Garden, 23(3), pp. 457–483. doi: 10.2307/2394164.

a) vector, b) matrix, c) tensor

Redrawn from Goodfellow, I., Bengio, Y. and Courville, A. (2018) ‘2.1 Scalars Vectors Matrices and Tensors’, Deep Learning Book Series. Available at: https://hadrienj.github.io/posts/Deep-Learning-Book-Series-2.1-Scalars-Vectors-Matrices-and-Tensors/.

>>> iris.data[:10]
array([[5.1, 3.5, 1.4, 0.2],
[4.9, 3. , 1.4, 0.2],
[4.7, 3.2, 1.3, 0.2],
[4.6, 3.1, 1.5, 0.2],
[5. , 3.6, 1.4, 0.2],
[5.4, 3.9, 1.7, 0.4],
[4.6, 3.4, 1.4, 0.3],
[5. , 3.4, 1.5, 0.2],
[4.4, 2.9, 1.4, 0.2],
[4.9, 3.1, 1.5, 0.1]])
>>> iris.data.shape
(150, 4)

Maaten, L. van der and Hinton, G. (2008) ‘Visualizing data using t-SNE’, Journal of machine learning research, 9(Nov), pp. 2579–2605.

redrawn from O’Neil, C. and Schutt, R. (2013) Doing Data Science. Sebastopol, CA,USA: O’Reilly Media, Inc. (Straight Talk from the Frontline).

‘[vector] space is granted a privileged relationship to reality: to exist is to be in space.’

Seaver, N. (forthcoming) ‘Everything Lies in a Space: Cultural Data and Spatial Reality’, Journal of the Royal Anthropological Institute, (Special Issue: The Anthropology of Data).

‘[data science] resonates with a belief in a hidden mathematical order that is ontologically superior to the one available to our everyday senses.’

McQuillan, D. (2017) ‘Data Science as Machinic Neoplatonism’, Philosophy and Technology, 3(1), pp. 253–272. doi: 10.1007/s13347-017-0273-3.

Framed and Framing

Gitelman, L. (2013) Raw data is an oxymoron. Cambridge, MA, USA and London, UK: The MIT Press.

Wark, M. (2015) ‘The Vectoralist Class’, e-flux, 65. Available at: http://supercommunity.e-flux.com/texts/the-vectoralist-class/.

diagram redrawn from: Anthony, B. (2017) ‘Socio-cultural Dynamics between the Eras of Commodity Economy: Pastorialism, Capitalism, Vectorialism’. Available at: https://borisanthony.net/diagrams/vectorialism/.

Operations

Operative Images

‘These are images that do not represent an object, but rather are part of an operation.’

Farocki, H. (2004) ‘Phantom Images’, Public, 0(29). Available at: https://public.journals.yorku.ca/index.php/public/article/view/30354.

What is principal component analysis?
https://liorpachter.wordpress.com/2014/05/26/what-is-principal-component-analysis/

Kim, E. (2013) ‘Everything You Wanted to Know about the Kernel Trick’, eric-kim.net. Available at: http://www.eric-kim.net/eric-kim-net/posts/1/kernel_trick.html.

Bernhardsson, E. (2015) ‘Nearest neighbor methods and vector models part 1’, Erik Bernhardsson. Available at: https://erikbern.com/2015/09/24/nearest-neighbor-methods-vector-models-part-1.html.

Classifier comparison - scikit-learn
https://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html

Pedregosa, F. et al. (2011) ‘Scikit-learn: Machine Learning in Python’, Journal of Machine Learning Research, 12, pp. 2825–2830.

Joler, V. (2020) New Extractivism. Available at: extractivism.work.

Crawford, K. and Joler, V. (2018) ‘Anatomy of an AI System’. Available at: http://www.anatomyof.ai.

The foreclosure of the future

Angwin, J. et al. (2016) ‘Machine Bias: There’s software used across the country to predict future criminals. And it’s biased against blacks.’, Propublica. Available at: https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.

Oscillations

Image: Police Tech: Predictive technology - Feb. 2019 - American Police Officers Alliance
https://americanpoliceofficersalliance.com/police-tech-predictive-technology

Aradau, C. (2015) ‘The signature of security’, Radical Philosophy, (191).

Clifton, B., Lavigne, S. and Tseng, F. (2017) ‘White Collar Crime Risk Zones’, The New Inquiry, 59: ABOLISH. Available at: https://whitecollar.thenewinquiry.com.

Atelier de dessin - B.A.C. du 14e arrondissement de Paris - Julien Prévieux
https://www.previeux.net/fr/works-atelierbac.html

Parrish, A. (2015) ‘Exploring (Semantic) Space With (Literal) Robots’. Available at: https://vimeo.com/134734729.

Quantum V_ trading algorithm, by Suzanne Treister
part of: RYBN (2015) ‘ADMXI’. Available at: http://www.rybn.org/ANTI/ADMXI/.

Counter Practice

We do not react like those who reject [statistics] wholesale and shout: ”No to quantification! No to numbers! Yes to qualities!” because, in doing so, they leave a monopoly over these instruments to the powerful. There is no reason for quantification to always be on the side of the state and of capital.

Didier, E. and Tasset, C. (2013) ‘Pour un statactivisme. La quantification comme instrument d’ouverture du possible’, Tracés, (24), pp. 123–140. doi: 10.4000/traces.5660. my translation

Box, G. E. P. (1976) ‘Science and Statistics’, Journal of the American Statistical Association, 71(356), pp. 791–799. doi: 10.1080/01621459.1976.10480949. with added annotations in green

The true method of speculation is like the flight of an airplane. It starts from the ground of particular observation; it makes a flight in the thin air of imaginative generalization; and it again lands for renewed observation rendered acute by rational interpretation.

Whitehead (1929) quoted in Parisi, L. (2012) ‘Speculation: A method for the unattainable’, in Lury, C. and Wakeford, N. (eds) Inventive Methods. Routledge, pp. 232–244.

Digital Humanities	Speculative Computing
Information technology/formal logic	Pataphysics/the science of exceptions
Quantitative methods (Problem-solving approaches)(practical solutions)	Quantum interventions (Imagining what you do not know)(imaginary/imaginative solutions)
Induction/Deduction	Abduction
Discrete representations (Static artifacts)	Heteroglossic processes (Intersubjective exchange/discourse fields)
Analysis/observation (Mechanistic)	Subjective deformance/intervention (Probabilistic)

Drucker, J. (2009) SpecLab; Digital Aesthetics and Projects in Speculative Computing. Chicago, IL, USA: University of Chicago Press.

Sleuthing

‘an inability to cognitively map the gears and contours of the world system is as debilitating for political action as being unable mentally to map a city would prove for a city dweller.’

Toscano, A. and Kinkle, J. (2015) Cartographies of the Absolute. Lanham, MD, USA: Zero Books.

Jameson, F. (1988) ‘Cognitive Mapping’, in Nelson, C. and Grossberg, L. (eds) Marxism and the interpretation of culture. Basingstoke: Macmillan Education.

‘cognitive prostheses’

Srnicek, N. (2012) ‘Navigating Neoliberalism: Political Aesthetics in an Age of Crisis’, The Matter of Contradiction: Ungrounding the Object. Available at: https://www.wdw.nl/files/Navigating_Neoliberalism_Political_Aesth.pdf.

Diagrams of the Future DOTF.XYZ

Anderson, E. (1936) ‘The species problem in Iris’, Annals of the Missouri Botanical Garden, 23(3), pp. 457–483. doi: 10.2307/2394164.

Fisher, R. A. (1936) ‘The Use of Multiple Measurements in Taxonomic Problems’, Annals of Eugenics, 7(2), pp. 179–188. doi: 10.1111/j.1469-1809.1936.tb02137.x.

scikit learn documentation

Probing

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.

‘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.

Architectures of Choice: Vol.1 YouTube
https://davidbenque.com/projects/architectures-of-choice/

Atlas des Recommandations https://adr.diagram.institute

Fluo-Green project, Université de Namur
https://sites.google.com/site/fluogproject/

Divining

Chicane comes to signify both an element within symbolic and divinatory performance, and the game of interpretation for both insider and outsider concerning the mysterious phenomena involved.

Cornelius, G. (2016) ‘Chicane: Double-Thinking and Divination among the Witch-Doctors’, in Curry, P. (ed.) Divination; Perspectives for a New Millennium. Routledge.

Divination, like deal making, is paradoxically a form of sincere bluffing genuinely intended to help the client, rather than insincere or vicious bluffing, intended to hurt the client. The bluff is not in the diviner who pretends to know something that the client does not know.

Ramey, J. (2016) Politics of divination: Neoliberal endgame and the religion of contingency. London, UK: Rowman & Littlefield International (Reinventing critical theory).

O’Neil, C. and Schutt, R. (2013) Doing Data Science. Sebastopol, CA,USA: O’Reilly Media, Inc. (Straight Talk from the Frontline).

almanac.computer https://almanac.computer

Cosmic Commodity Charts - https://almanac.computer

FIN

David Benqué
@diagram.studies
@davidbenque
@air_pump@post.lurk.org