An Introduction of Algorithmic Governance
When data is a form of capital in contemporary capitalism (Sadowski, 2019:1), algorithm is apparently the indispensable tool to manipulate and monetize that capital. And more powerfully, through data manipulation, algorithms are being used to "nudge, bias, guide, provoke, control, manipulate, and constrain human behavior" (Danaher et al., 2017:2). In other words, human behavior, both inside and outside the screen, is governed by algorithms. However, unlike regulation, governance is not necessarily intentional and purposeful (Black, 2001:140). Algorithmic governance encompasses the intentional and unintentional effects of algorithmic-selection systems in everyday life (Latzer & Festic, 2019:12).
Differing from regulation, governance also considers the multiplicity of social ordering concerning "actors, mechanisms, structures, degree of institutionalization and distribution of authority" (Katzenbach & Ulbricht, 2019:2). In essence, modern algorithms, deployed by commercial platforms and public services alike, generate automated decisions and assumptions by using "sophisticated computer technologies and aggregated sets of data" (Stucke & Ezrachi, 2017:1779-1805). Notably, algorithms are only applied to "augment and enhance everyday human decision-making but not fully replace it" (Latzer & Festic, 2019:5). To be specific, algorithms only co-govern society, together with and as part of other conventional governance systems (ibid.). Inside the screen, algorithms co-govern "what can be found, what is anticipated, consumed and seen, and whether it is considered relevant" (Just & Latzer, 2017:247). Outside the screen, algorithms co-govern user/consumer's emotion and behavior through contents recommended, filtered, or randomly presented by algorithms. Considering the above characteristics and built on Katzenbach and Ulbricht's (2019:2) definition of algorithmic governance, this short article proposes to define algorithmic governance as a multiplicity social ordering that intentionally and unintentionally co-governs human behavior inside and outside the screen, based on complex computer-based epistemic procedures.
Since algorithmic governance has been deployed by both government and private businesses, the extent and scale of algorithmic governance of daily life are historically unprecedented. Additionally, algorithmic governance technologies are built on top of the pre-existing structures, thereby taking advantage of previous mechanistic innovations and making the speed, scale, and ubiquity of algorithmic governance grander now than ever (Danaher et al., 2017:2). The pervasiveness of algorithmic governance is emerging in line with the demands and development of society "as part of a longer historical trend toward the mechanization of governance" (Danaher et al., 2017:2).
This governance by algorithms ranges from mundane digital communication and online shopping, to citizen management. For instance, with increasing user bases and growing political pressure, digital media companies resort to technical solutions to address platform governance obstacles such as hate speech, misinformation, and copyright (Gorwa, Binns & Kazenbach, 2019:1-15). Algorithmic governance is used by labor platforms to manage gig workers through ranking systems" (Wood et al., 2018:56-75). To maximize profit, algorithms automatically categorize consumers based on their purchasing power and disseminate them different marketing information. In the urban level, cities are equipped with an increasing number of sensing technologies to collect and transform urban dynamics into data flows that can be profiled and manipulated by algorithms (Smith, 2020:1-12). Invasively, algorithms are governing everyday life from social activities, business, to urban life.
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