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 decision-making systems that regulate a domain of activity in order to manage risk or alter behaviour 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.

It provides a descriptive analysis of algorithmic regulation, classifying these decision-making systems as either reactive or pre-emptive, and offers a taxonomy that identifies 8 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 behavioural standards); information-gathering and monitoring (historic data vs. predictions based on inferred data) and at the level of sanction and behavioural 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.

The contributors come from a broad range of disciplinary perspectives including law, public administration, applied philosophy, data science, and artificial intelligence
1: Algorithmic Regulation: An Introduction, Karen Yeung and Martin Lodge
Part I: Normative concerns
2: Why worry about decision-making by machine?, Karen Yeung
3: Machine decisions and human consequences, Teresa Scantamburlo, Andrew Charlesworth and Nello Cristianini
4: Digital discrimination, Natalia Criado and Jose M Such
5: The ethics of algorithmic outsourcing in everyday life, John Danaher
Part II: Public sector applications
6: Administration by Algorithm? Public Management meets Public Sector Machine Learning, Michael Veale and Irina Brass
7: The Practical Challenges of Implementing Algorithmic Regulation for Public Services, Alex Griffiths
8: Reflecting on Public Service Regulation by Algorithm, Martin Lodge and Andrea Mennicken
Part III: Governing algorithmic systems
9: Algorithms, regulation and governance readiness, Leighton Andrews
10: Legal practitioners' approach to regulating AI risks, Jason D Lohr, Winston J Maxwell and Peter Watts
11: Minding the machine v2.0: The EU General Data Protection Regulation and Automated Decision Making, Lee A Bygrave