Pablo Velasco
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    --- title: DS21S10 tags: class slideOptions: theme: white transition: slide --- ## <span class="censor">Data Studies 2021 // S10. Surveillance</span> <!--image for class--> <a href="https://pigeonsarentreal.co.uk/"><img src="https://i.imgur.com/ZOATdNB.png" width="85%"></a> <span class="censor">Pablo Velasco // Information Studies // [pablov.me](https://pablov.me)</span> --- ## Plan for the day: * Surveillance(s) * Digital Surveillance * Surveillance Capitalism --- <!-- .slide: data-background-image="https://i.imgur.com/qcsF5qq.jpg" data-background-size="100% auto" --> # <span class="censor">SURVEILLANCE(<span style="color:hotpink">S</span>)</span> ---- ### Classic approaches to surveillance * Sur-veillance: **watching-over** * **Disciplinary society** <span class="refs">Foucault, M. (1978). Discipline and Punish: The Birth of the Prison</span> * Panoptic surveillance <span class="refs">Elmer, G. (2003). A Diagram of Panoptic Surveillance</span> * few observing many ("**unequal** gaze") * **internalized** regulatory gaze (*governmentality*) * Sousveillance (**inverted** surveillance) <!-- real time tracking of the police in london protests--> * Panspectric veillance <span class="refs">Landa, M. D. (1991). War in the Age of Intelligent Machines</span> * enabled by **sensors and signals**, instead of human senses ---- ### But also surveillance as everyday practice * self-tracking <span class="refs">Lupton, D. (2016). The quantified self</span> * *participatory*: watching each other, being viral <span class="censor">Social surveillance is the ongoing eavesdropping, investigation, gossip, and inquiry that consitutes information gathering by people about their peers, made salient by the social digitalization normalized by social media (...) the nature of "surveillance" dynamically changes based on the social role played by observer and observant</span> <span class="refs">Marwick, A. E. (2012). Social Surveillance in Everyday Life</span> ---- <!-- .slide: data-background-image="https://gitlab.com/xpablov/data-studies/-/raw/master/DS19/S10/radiolab-surveillance.png" data-background-size="100% auto" --> <span style="color:white;font-size:2em">Persistent Surveillance Systems</span> <span><a href="https://www.wnycstudios.org/podcasts/radiolab/articles/eye-sky" style="color:white">e.g. Radiolab: Eye in the sky</a></span> ---- ## 1. Which devices/artifacts are tracking us now? ## 2. Which of them are obviously visible? Which are obfuscated? ## 3. Who is gathering this information? Do you know to what purpose? --- # <span style="color:hotpink">DIGITAL</span> SURVEILLANCE ---- <!-- .slide: data-background-image="https://hackmd.io/_uploads/ry8KEkN9D.png" data-background-size="auto 100%" --> * Digital Surveillance: * **Bigger** scope of data: CCTV, RFID, biometics... * "Liquid surveillance" <span class="refs">Bauman, Z., & Lyon, D. (2012). Liquid Surveillance: A Conversation</span> * fluid, uncontained, **pervasive** monitoring * *Dataveillance* <span class="refs">Dijck, J. van. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology</span> * continous tracking of (meta)data for **unstated** purposes ---- ### Let's look at the exhaust data captured from your browser 1. Go to Panopticlick: https://panopticlick.eff.org/ 3. Is your browser fingerprint unique? What does this mean? ---- | Surveillance model | Capture model | | -------- | -------- | | visual metaphors | linguistic metaphors | | non-disruptive watching | "parsing" of activities for re-organisation | | territorial metaphor (*invasion*) | **assembled from "parts"** | | centralized/bureaucratic | **decentralized and heterogenous** | | identification with the state | **mathematical formalism** | <span class="refs">Agre, P. E. (1994). Surveillance and capture: Two models of privacy</span> **NOT** mutually exclusive models! ---- <!-- .slide: data-background-image="https://pablov.me/pres/media/compstats.gif" data-background-size="auto 100%"--> ## <span style="color:white">Mathematical formalism</span> <span style="color:white"><small>*Compstats in Brooklyn Nine-Nine (S01E15)</small></span> ---- <!-- .slide: data-background-image="https://ccnmtl.columbia.edu/projects/caseconsortium/casestudies/127/casestudy/files/photos/900/appendix2.png" data-background-size="100% auto"--> ### <span class="censor">How do grammars of action happen?</span> <br> 1. <span class="censorw"><b>Analysis</b>: identification of fundamental units of activity</span> 2. <span class="censorw"><b>Articulation</b>: formal specifications (grammar)</span> 3. <span class="censorw"><b>Imposition</b>: normative force (organisation of action under grammar)</span> 4. <span class="censorw"><b>Instrumentalisation</b>: social and technical means for maintaining the grammar</span> 5. <span class="censorw"><b>Elaboration</b>: captured activity can be stored, inspected, audited, etc...</span> <span class="censor">"The crime rate itself became the boss" <br><br>"The people who started running CompStat didn't understand it"<br><br> </span> ### <span class="censorw">In the original design Data was the means, and eventually Data became the ends</span> ---- ![](https://i.imgur.com/sEPDJrO.png) <span class="refs">Agre, P. E. (1994). Surveillance and capture: Two models of privacy.</span> --- # SURVEILLANCE <span style="color:hotpink">CAPITALISM</span> ---- <!-- .slide: data-background-image="https://i.imgur.com/djZkBC9.jpg" data-background-size="100% auto" --> <h2 class="censor fragment">[Surplus (value): earnings minus costs of materials and labor]</h2> <h2 class="censor fragment">[Alienation: from products, but also of our own determination]</h2> ---- <!-- .slide: data-background-image="https://i.imgur.com/zPUnc57.png" data-background-size="auto 100%" --> ## <span class="censor">Behavioural data reinvestment cycle</span> <span class="censor">Every action a user performs is considered a signal to be analyzed and fed back into the system (Hal Varian)</span> * <span class="censor">"Surveillance Capitalism is not a technology; it is a logic that imbues technology and commands it into action" (15)</span> * <span class="censor">"Machine intelligence" -> analysis, Machine Learning, prediction, recognition, modeling...</span> <span class="pinky" style="background:white">Hmm… Machine intelligence seems to be used quite broadly and I can't quite wrap my head around where the borders are. Google themselves refer to things like language translation, speech recognition and prediction as machine intelligence (Mathilde)</span> ---- <!-- .slide: data-background-image="https://i.imgur.com/q2p2x3z.jpg" data-background-size="100% auto" --> <span style="color:black;font-size:2em">Recommendation systems</span> <span>[The Napoleon Dynamite problem](https://www.nytimes.com/2008/11/23/magazine/23Netflix-t.html?pagewanted=all)</span> <span class="pinky" style="background:white">When we predict a visualization based on a sample of data and then feed more data to test the accuracy of our prediction in the visualization (Laura) </span> ---- <img src="https://i.imgur.com/Sq0wu32.png" width="49%"> <img src="https://i.imgur.com/9JtFJ8l.png" width="49%"> https://www.visualcapitalist.com/how-big-tech-makes-their-billions-2020/ ---- ### Google's reinvesment cycle turns from "improving the product" towards "prediction of user behavour" <!-- no silicon valley enterprise knows how to make money --> * Instead of 'fordist' production, Google UPI (user profile information) extraction and analysis tailored to advertisment (<span style="color:red">*ends*</span>) * Unique mix (<span style="color:red">*means*</span>): behavioural surplus, data science, material infrastructure, computational power, algorithmic systems, and automated platforms ("machine intelligence") "instrumentarianism" power -> shape human behaviour to other's ends ---- <!-- .slide: data-background-image="https://i.imgur.com/fYToHa4.png" data-background-size="auto 100%" --> <span class="censor">Behavioural knowledge, manipulation, and prediction: microtargeting as a combination of politics and consumer marketing, and the capacity of manipulation of affective states (O'Neil 2017)</span> ---- <img src="https://i.imgur.com/rLfp9iP.png" width="100%"> https://firstdraftnews.org/long-form-article/trackers-gephi-dmi/ DMI version (in development, but you can export directly to gephi): https://github.com/digitalmethodsinitiative/brightbeam Also, tracker-tracker (exports to gephi): https://tools.digitalmethods.net/beta/trackerTracker/ ---- ### Short activity: *lightbeam* Install *Thunderbeam-Lightbeam* for chrome [here](https://chrome.google.com/webstore/detail/lightbeamchrome/hjkajeglckopdkbggdiajobpilgccgnj?hl=en-GB) 0. (remember to deactivate your blockers) 1. Navigate for a few minutes as you'll usually do. Try some google searches, news websites, or social media 2. How does your network look? Compare with others: are there trackers that repeat continually? (you may want to pay attention to the *bridges* and/or central nodes for this) Try doing the same with your adblockers on. Is there a substantial difference? You can try different adblockers. <style> .reveal{ font-family:mono; font-size: 25px; } .reveal .censor{ background:#333333; color:white; } .reveal .censorw{ background:white; color:black; } .reveal .pinky{ color:#e5157d; font-style:italic; font-size: .8em; } .reveal section img { border: none; box-shadow: none; } .reveal section left{ width:50%; } .reveal .refs { color: grey; font-size: small; text-align: left; } </style>

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