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        <div id="content-top1">Page 367 - The Black Box Book</div>
        <div id="content-top2">P. 367</div>
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    <pre style="white-space:pre-line"><code>IN                                                L IN E S


                     “In order for the AI to read the images and learn to recognize them, it
                     must first decompose them into rows, into individual pixels arranged
                     side by side. It then compares them to each other. If each image in our
                     dataset was decomposed into a single line that is 1 pixel high, and we
                     also wanted to rearrange the entire dataset in this way, print it out and
                     display it in a gallery, we would get a color print of 262,144 x 136,458
                     pixels, which is 53.33 GB. With current technology, however, it is not
                     possible to print such a huge image; it is not even possible to display
                     it on a regular computer. So, we can only approximate its visual
                     structure through a 100 times smaller preview to give you an idea.”
                     (Javůrek, T. & Meixnerová, M. & Trnková, B., 2022)

                     Another  opportunity  where  we  can  visually  evaluate  one  of
                the technical processes associated with AI learning is the decomposition
                of a dataset into rows. This step permanently breaks down the human-un-
                derstandable content of the image and creates a pure abstraction, which
                in turn begins to make sense to the machine on a mathematical level. As
                artists, however, we were intrigued by the colorfulness of this abstract
 S  H  O  W  C  A  S  E  result. We expected to see grey, as the dataset contains many black
                and white photographs, typographies, and records of graphic sheets of
 Artists understandably try to make the presentation of their art on    various graphic techniques and views of interiors where the predominant
 the internet look appealing. Their websites therefore often conform to   tonality is white and grey. However, green is also significantly represented
 contemporary ideas of an attractive web presence. My video is another   in the result. This is probably due to the photographs of the artworks on
 form of self-reflection on artistic practice. It is a dataset presentation in   the exterior. In the spirit of the project’s hyperbole, however, we can now
 which I situate myself in a kind of animated browser. In the language of   declare that Czech art is on average olive green, even grey (Figure 13).
 Youtube videos, I write and show the names of the artists represented on   The color analyses of the datasets provide another field for possible cor-
 camera with smiles. In this way I mimic the work of a ‘ring girl’ in a web   relations between artificial and artistic perception.
 presentation environment (Figure 12).
 Dataset analyses are another case of representing traditional and
 emerging images of social reproduction in the online context. The online
 space creates the illusion of a more democratic background for social
 interaction. For instance, it makes it easier to perform under multiple
 identities, and it liberates many forms of care that were previously unpaid
 for (ASMR videos, etc.). Even through the practice of a recommendation
 guide, which has been transformed in the online environment into an ac-
 tivity of learning algorithms, is not immune to the pervasiveness of gender
 stereotypes in our society. In addition, the gaze through the screen, or
 the gaze of the camera, is always extremely aestheticized, spectacular,
 and fetishizing. It imports an agenda derived from a cinematic language,
 that remains a vehicle for the sublimation of a range of hitherto unre-
 flected issues, and is closely linked to marketing strategies. The camera
 exploits the soft tissue of the people and creates a pressure for visibil-
 ity that escalates when combined with the apparent timelessness of
 the online environment.


 366                                           367</code></pre>
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