Course:LIBR559A/Janssen, M., & Kuk, G. (2016).

Citation

Janssen, M., & Kuk, G. (2016). The challenges and limits of big data algorithms in technocratic governance. Government Information Quarterly, 33(3), 371-377. doi:10.1016/j.giq.2016.08.011

Annotation

The purpose of this article is to show the inherent biases in the use of algorithms in big data and how moving forward developers, companies, and governments can understand the issues surrounding the use of algorithms. The authors in this article examine how algorithms play a key role in society. They note that the common belief is that algorithms are impartial and drive society through what they call technocratic governance (Janssen, M., Kuk, G., 2016, pg.371). Janssen and Kuk (2016) say technocratic governance in “The challenges and limits of big data algorithms in technocratic governance,” “... assumes that complex societal problems can be deconstructed into neatly defined, structured and well-scoped problems that can be solved algorithmically and in which political realities play no role” (pg.371-372). The authors note algorithms are open to abuse (Janssen, M, Kuk, G., 2016, pg.373).

The authors examine algorithms and draw parallels to Michel Foucault’s depiction of governmentality to show how algorithms, through government agencies and institutions, wield power over individuals (Janssen, M., Kuk, G., 2016, pg.375-376). They promote algorithms have a lack of transparency and can be used by governments and organizations for their own gains (Janssen, M., Kuk, G., 2016, pg.374). They used the example of Facebook and its trending practices through hired human curators. These human curators can use algorithms to promote what will trend (Janssen, M., Kuk, G., 2016, pg.375). The examples and framework are used to promote their conclusion that algorithms need to be democratized. The democratization Janssen and Kuk (2016) in “The challenges and limits of big data algorithms in technocratic governance” state, “need to engage users to co-create alongside with expert practitioners in areas of design, software development and machine learning. To build this knowledge network, we purport to broaden the emphasis from building technical solutions and public disclosure of known attacks to a more socially inclusive innovation approach” (pg.376).

The critique of Janssen and Kuk’s article is the relative shallowness of their study. The information presented is not new or novel. The conclusion is what other authors are promoting that there needs to be a cultural change, and understanding, between the ways algorithms, are used in computing. The potential of this article to add to the body of literature in LIS studies is the understanding of how technological determinism is problematic and how it needs to be reexamined at its core.

Keywords

Big Data, Inequality, Algorithm, Transparency

Page Author: Elizabeth Moyer