What is Algorithmic Regulation anyway?
The term of “algorithmic regulation” was first proposed by Tim O’Reilly in his blog post, Open Data and Algorithmic Regulation. However, he didn’t provide a definite definition. He only listed four characters he believed various technology systems bear:
- A deep understanding of the desired outcome
- Real-time measurement to determine if that outcome is being achieved
- Algorithms (i.e. a set of rules) that make adjustments based on new data
- Periodic, deeper analysis of whether the algorithms themselves are correct and performing as expected.
Karen Yeung later managed to lay out a more detailed definition for algorithmic regulation. In her 2017 work, Algorithmic Regulation: A Critical Interrogation, algorithmic regulation has been defined as “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.”
She further proposed an algorithmic regulation taxonomy with 3 stages/facets of cybernetic process, 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).
Karen stated that her definition of regulation was based on Julia Black’s view that regulation (or regulatory governance) are “intentional attempts to manage risk or alter behaviour in order to achieve some pre-specified goal.”
Besides Karen’s definition, Mireille Hildebrandt laid out another definition in her piece, Algorithmic regulation and the rule of law. Algorithmic regulation refers to “standard-setting, monitoring and behaviour modification by means of computational algorithms.”
If all that is too long, Karen Yueng did provide a shorter definition in the same article.
Algorithmic decision-making refers to the use of algorithmically generated knowledge systems to execute or inform decisions, and which can vary widely in simplicity and sophistication.
Algorithmic regulation refers to regulatory governance systems that utilise algorithmic decision making.
And if you are interested to learn about some discussion regarding the difference between algorithmic regulation and algorithmic governance, be sure to check out Algorithmic regulation: A maturing concept for investigating regulation of and through algorithms, where Ulbricht and Karen talked about why they chose the word regulation instead of governance.
Hildebrandt, M. (2018). Algorithmic regulation and the rule of law. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2128), 20170355.
Ulbricht, L., & Yeung, K. (2022). Algorithmic regulation: A maturing concept for investigating regulation of and through algorithms. Regulation & Governance, 16(1), 3–22.
