Algorithmic regulation: A critical interrogation

Abstract

Innovations in networked digital communications technologies, including the rise of “Big Data,” ubiquitous computing, and cloud storage systems, may be giving rise to a new system of social ordering known as algorithmic regulation. Algorithmic regulation refers to decisionmaking systems that regulate a domain of activity in order to manage risk or alter behavior through continual computational generation of knowledge by systematically collecting data (in real time on a continuous basis) emitted directly from numerous dynamic components pertaining to the regulated environment in order to identify and, if necessary, automatically refine (or prompt refinement of) the system's operations to attain a pre‐specified goal. This study provides a descriptive analysis of algorithmic regulation, classifying these decisionmaking systems as either reactive or pre‐emptive, and offers a taxonomy that identifies eight different forms of algorithmic regulation based on their configuration at each of the three stages of the cybernetic process: notably, at the level of standard setting (adaptive vs. fixed behavioral standards), information‐gathering and monitoring (historic data vs. predictions based on inferred data), and at the level of sanction and behavioral change (automatic execution vs. recommender systems). It maps the contours of several emerging debates surrounding algorithmic regulation, drawing upon insights from regulatory governance studies, legal critiques, surveillance studies, and critical data studies to highlight various concerns about the legitimacy of algorithmic regulation.

Public administration, public leadership and the construction of public value in the age of the algorithm and ‘big data’

“…Pasquale () says ‘authority is increasingly expressed algorithmically’. Yeung () speaks of ‘algorithmic power’. This is not, of course, to say that all algorithms require governance or regulatory intervention.…”

Traceability in global governance

“…In some cases, this could involve the creation of a formal intergovernmental organization or law, like the United Nations, and international treaties. Over time, an increasing variety of other forms of governance have been recognized, including informal norms among states that constitute international 'regimes' (Krasner 1983), rules established by private actors such as business associations (Cutler et al 1999;Hall and Biersteker 2002), or technical rules built into machine systems, such as the algorithmic governance that regulates activities on social media platforms such as Facebook (Yeung 2017).…”

Power at a distance: Organizational power across boundaries

“…Third, we draw on emerging research on big data, Artificial Intelligence, and algorithmic governance (Yeung, ) to sketch the contours of power expressed through “algorithmic distance.” Algorithmic distance refers to a space that is filled by automated, calculative routines that shape organizational decisions and practices. Scholars are beginning to examine the ways in which power is encoded into seemingly neutral algorithms and machine learning technologies, as well as technologies that increase surveillance of both individuals and organizations.…”

“…Third, we draw on emerging research on big data, Artificial Intelligence, and algorithmic governance (Yeung, 2018) to sketch the contours of power expressed through "algorithmic distance." Algorithmic distance refers to a space that is filled by automated, calculative routines that shape organizational decisions and practices.…”