![\"\"](\"https:\/\/golancourses.net\/fall23\/wp-content\/uploads\/2023\/11\/jeremijenko_suicidebox_842x725-1024x882.jpg\")
<\/p>\n<\/p>\n
Create a machine that asks a question of the world. Your machine should either measure\/detect something interesting, measure\/detect something in an interesting way, or create an interesting provocation by bringing an uncommon measurement\/detection to our attention. The focus here is on the selection and collection of intriguing data, rather than on the production of an attractive interpretation or visualization. What overlooked dynamics or invisible rhythms can you discover?<\/em><\/p>\n In this speed project<\/em>, you are asked to create a “situated eye<\/strong>” – a “contextualized classifier<\/strong>” – a “purposeful detector<\/strong>” – a “poetic surveillant<\/strong>“. You are asked to create a camera-based system:<\/p>\n This is a speed project, due Monday 11\/6.<\/strong><\/span> The project values your inventiveness about where you point your camera<\/em>, your cleverness in choosing a subject on which to train an AI system<\/em>, and your care in actually training the AI system<\/em>. Although you will be working in p5.js, almost no code is required or expected.<\/strong><\/p>\n What is an interesting subject to study<\/em> with a video camera?<\/strong> You will be provided a webcam, and potentially a tripod and\/or USB extension cable.<\/p>\n Here’s a dumb example\u2014you can do better:<\/strong><\/em> Put the camera in your fridge. Train it to recognize when the fridge is open and closed. Perhaps you can train it to recognize the face of which roommate is opening the fridge. Use this system to create a system that records which of your roommates opened the fridge, when. Other examples:<\/strong> Cheese<\/em> by Christian Moeller; Suicide Box<\/em> by Natalie Jeremijenko.<\/p>\n Demonstrations of the following AI systems will be given in class. It is strongly recommended you use one of these.<\/p>\n Classification:<\/strong><\/p>\n Regression:<\/strong><\/p>\n Census historian James C. Scott points out that measurement is a political act. Artists like Natalie Jeremijenko collect measurements in order to prompt evidence-driven discussion; others, like Mimi Onuoha, point out that what is not measured is equally revealing of a culture\u2019s biases and indifferences (the study of which is called agnotology<\/em>). In the weird world of quantum physics, the term \u201cobserver effect\u201d refers to the idea that the very act of measurement changes the subject being measured. Measurement, or the collection of data, alters the world and the way we see it.<\/p>\n Data collection has become a key practice across many fields. \u201cCitizen science\u201d is an educational and political movement that enlists everyday people in scientific activities and often focuses on monitoring local environmental conditions through distributed DIY sensing. For example, in the aftermath of the Fukushima disaster, radiation sensors were distributed to a concerned public, who transmitted readings to a central server.<\/p>\n Scholars Catherine D\u2019Ignazio and Lauren Klein outline ways to responsibly work with data, taking philosophical ideas from feminist thought and applying them to data collection and visualization practices. The principles of feminist data visualization include acknowledging that data represents an incomplete perspective; emphasizing the context and the situation in which data was collected; and providing a way for those represented in the data to respond to it.<\/p>\n There is often something absurd, poignant, or whimsically futile about the act of measurement \u2014an attempt to reduce an infinitely complex experience to a handful of numbers. In the arts, measurement can explicitly remind us that our understanding of reality is only ever an approximation.<\/p>\n","protected":false},"excerpt":{"rendered":" Create a machine that asks a question of the world. Your machine should either measure\/detect something interesting, measure\/detect something in an interesting way, or create an interesting provocation by bringing an uncommon measurement\/detection to our attention. The focus here is on the selection and collection of intriguing data, rather than on the production of an … Continue reading “08. Situated Eye”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":10,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-515","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/golancourses.net\/fall23\/wp-json\/wp\/v2\/pages\/515","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/golancourses.net\/fall23\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/golancourses.net\/fall23\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/golancourses.net\/fall23\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/golancourses.net\/fall23\/wp-json\/wp\/v2\/comments?post=515"}],"version-history":[{"count":10,"href":"https:\/\/golancourses.net\/fall23\/wp-json\/wp\/v2\/pages\/515\/revisions"}],"predecessor-version":[{"id":529,"href":"https:\/\/golancourses.net\/fall23\/wp-json\/wp\/v2\/pages\/515\/revisions\/529"}],"up":[{"embeddable":true,"href":"https:\/\/golancourses.net\/fall23\/wp-json\/wp\/v2\/pages\/10"}],"wp:attachment":[{"href":"https:\/\/golancourses.net\/fall23\/wp-json\/wp\/v2\/media?parent=515"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
and which\u00a0responds<\/em> to what it sees, in an interesting way.<\/del> (NOPE<\/strong>)<\/li>\n<\/ul>\n
\nWho, What, When, Where, Why<\/h3>\n
\nFor this subject, what are some interesting observations you can automate<\/em>?
\nHow might a system respond<\/em> in an interesting way to these observations?<\/strong><\/p>\n\n
\nDesign Considerations<\/h3>\n
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\nTemplate Code<\/h3>\n
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\nThoughts<\/h3>\n