Neither Black Nor Box: Ways of Knowing Algorithms
Bucher uses the concept of the black box as a heuristic device to discuss the nature of algorithms in contemporary media platforms, and how we, as scholars and students interested in this nature, might attend to and study algorithms, despite, or even beca
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Neither Black Nor Box: Ways of Knowing Algorithms Taina Bucher Consider the following tweets: ‘The suggested algorithm on Facebook confuses me. It thinks I need to lose weight, am pregnant, broke, and single.’ ‘I hate Facebook’s algorithm so much. My followers aren’t seeing my posts on my FB page.’ ‘I feel like the Facebook algorithm doesn’t know me at all.’1 Every single day, social media users feel compelled to express their feelings and observations about the ways in which systems like Facebook work. Searching Twitter for mentions of the Facebook algorithm solicits an impressive list of beliefs, questions, opinions, and observations concerning the algorithms animating the platform. The stream provides a rare glimpse into the everyday experiences that people have with algorithmic media. I say rare, because as it stands we do not know much about the ways in which people experience algorithms in their everyday life. There are many reasons for this lack of knowledge about the contours of algorithmic life, some of which I will address as part of this chapter. The most straightforward reason, perhaps, is the only very recent uptake of algorithms as a field of research within the social science and humanities. During the past few years, however, there has been a significant upsurge in academic and public interest. Algorithms have been described as playing
T. Bucher () University of Copenhagen, Copenhagen, Denmark e-mail: [email protected] © The Author(s) 2016 S. Kubitschko, A. Kaun (eds.), Innovative Methods in Media and Communication Research, DOI 10.1007/978-3-319-40700-5_5
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an increasingly important role in shaping the world of finance (Karppi and Crawford 2015; Lenglet 2011), journalism (Anderson 2013; Diakopoulos 2015), the media sector, and social media in particular (Gillespie 2014). When computer scientists speak of software, they generally refer to machine-readable instructions that direct the computer to perform a specific task. The algorithm, simply put, is just another term for those carefully planned instructions that follow a sequential order (Knuth 1998). When a social scientist talks about software, however, it often has less to do with the mechanical term or the nature of those machine-readable instructions, and more with the ways in which ‘software conditions our very existence’ (Kitchin and Dodge 2011, p. ix). Thus, the nature of research into algorithms differs across these disciplinary boundaries. While computer scientists are generally concerned with the design and development of algorithms, aimed at making them more efficient, social scientists and humanities scholars tend to be interested in the ‘social phenomenon that is driven by and committed to algorithmic systems’ (Gillespie 2016). For the latter, what is at stake are not so much the mathematical-logical coded instructions per se, but how these instructions have the power to shape the world in specific ways. From the important work that has already emerged in the social study of algorithms (for example, Anderson 2013; B
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