Keeping it Real: From Faces and Features to Social Values in Deep Learning Algorithms on Social Media Images

Bechmann, Anja2016-12-292016-12-292017-01-04978-0-9981331-0-2http://hdl.handle.net/10125/41372This paper wants to supplement computational tests of deep learning vision algorithms with a sociologically grounded performance test of three widely used vision algorithms on Facebook images (Clarifai, Google Vision and Inception-v3). \ \ The test shows poor results and the paper suggests the use of a two-level labeling model that combines features with theoretically inspired accounts of the social value of pictures for uploaders. The paper contributes a suggestion for labeling categories that connects the two levels, and in conclusion discusses both advantages and disadvantages in accelerating user profiling through a better understanding of the incentives to upload images in the data-driven algorithmic society.9 pagesengAttribution-NonCommercial-NoDerivatives 4.0 Internationaldigital sociologyDNNpicture recognitionsocial media imagesvision algorithmsKeeping it Real: From Faces and Features to Social Values in Deep Learning Algorithms on Social Media ImagesConference Paper10.24251/HICSS.2017.218