Ideas mingle and interfere within the mind of an agent to collectively form a complex and multifaceted will. We traverse our lives swimming through a piping hot soup of diverse ideas. Figuring out what to do next consists of giving that soup a good stir, and spooning out a random sample of the rich, mixed broth. I recently attended a class called Intelligent Machinery, where the students formally underwent this process with a smaller soup bowl than usual; we were challenged to collate the ideas from course readings and lectures into a single, expressive response.
Rather than attempt this on my own, I enlisted the help of a machine. The following page contains the work of a recurrent neural network who, after reading the ~3000 pages of assigned course material, produced their own written work. Thus, this piece is a cooperative venture. I have produced a portion of it — namely this cover page and some formatting for the output — while the rest has been produced by my machine collaborator. Obviously, the text produced by the machine is gibberish. But also, if you had attended the class, then you would find parts of the text eerily and humorously reminiscent of the style and ideas from the readings.
This generated text serves both as an analogy for how human students approach their assignments, and also as an example of messy authorship, where the traditional concept of a person doing something with the help of a machine is flipped on its head. I hope the reader can use the text as a kind of rough mirror to reflect on the information processing methods of their own human brain, as well as to ponder the the agency and authorial contribution carried by non-human entities.
Judging by its attempt at a title, I believe the machine's name is Brev.te’haposymble Joudd, and the essay is called νI2UAn.
νI2UAn
Brev.te’haposymble Joudd
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