In her TEDtalk, Fei Fei Li proposes to teach computers how to decipher images the way we teach children. Of course, the machines are unable to gather the needed data themselves, so the starting point of this experiment was to provide them with over billion categorized, described images that were meant to trigger the learning process in the computer. Using Big Data to train computer algorithms doesn’t seem as revolutionary to us now, but certainly it took some time to adjust to the idea that learning of computer could be similar to that of a child – if we tell it what the object is enough times, eventually it will learn how to do it by itself. But is it the right approach? I can see the appeal of such trained machine, how useful it could be in a research that looks at large data sets and how dramatically it could speed up the analysis process. Although I enthusiastically cheer for technological  progress I cannot help but worry that we might loose some of the most valuable information, one I keep going back to in nearly every post: socio-cultural context.

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