2017
DOI: 10.1177/2053951717726554
|View full text |Cite
|
Sign up to set email alerts
|

Algorithmic governance: Developing a research agenda through the power of collective intelligence

Abstract: We are living in an algorithmic age where mathematics and computer science are coming together in powerful new ways to influence, shape and guide our behaviour and the governance of our societies. As these algorithmic governance structures proliferate, it is vital that we ensure their effectiveness and legitimacy. That is, we need to ensure that they are an effective means for achieving a legitimate policy goal that are also procedurally fair, open and unbiased. But how can we ensure that algorithmic governanc… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
107
0
10

Year Published

2018
2018
2023
2023

Publication Types

Select...
5
4

Relationship

0
9

Authors

Journals

citations
Cited by 165 publications
(122 citation statements)
references
References 31 publications
1
107
0
10
Order By: Relevance
“…Some recent risk assessment instruments are beginning to incorporate machine learning (Berk, 2008;Berk, Sorenson, & Barnes, 2016), and there are discussions of incorporating dynamic data sets-where the instruments train on new incoming data in real time (Rothschild-Elyassi et al, 2019). Related to this, criminal justice institutions are increasingly working with computer scientists and software engineers trained in big data analytics to develop new ways of thinking about and assessing risk (Hannah-Moffat, 2018; see also Danaher, Hogan, & Noone, 2017). These developments open up new questions for research, and they point to new possibilities as well as new perils.…”
Section: Discussionmentioning
confidence: 99%
“…Some recent risk assessment instruments are beginning to incorporate machine learning (Berk, 2008;Berk, Sorenson, & Barnes, 2016), and there are discussions of incorporating dynamic data sets-where the instruments train on new incoming data in real time (Rothschild-Elyassi et al, 2019). Related to this, criminal justice institutions are increasingly working with computer scientists and software engineers trained in big data analytics to develop new ways of thinking about and assessing risk (Hannah-Moffat, 2018; see also Danaher, Hogan, & Noone, 2017). These developments open up new questions for research, and they point to new possibilities as well as new perils.…”
Section: Discussionmentioning
confidence: 99%
“…Traceable as early as McCulloch, Pitts, and von Neumann's pioneering of neural networks in 1943 (Halpern 2014: 233), cybernetics is a particularly useful framework for governmentality due to the way it lives on in the heart of contemporary technoscientific sensibilities, ethics, and ideas pertaining to the design and maintenance of purposive sociotechnical systems (Pangaro 2016: 9). From John Mashey's (1999) early conceptual pioneering of big data as the inextricable entangling of humans and machines into infinite feedback loops, cybernetics is immanently constitutive of big data itself (Rahebi 2015) and is responsible for a radical shift from biopolitical strategies to ones highly reminiscent of the cybernetic principles of maintaining efficient, reliable, and feedback-oriented control loops (Danaher et al 2017). As Lyon (2014: 7) argues, "what is assumed to be normal and correct behaviour is embedded in circuits of consumer (or employment, health, or education) practices.…”
Section: Part One: a Cybernetic Governmentalitymentioning
confidence: 99%
“…Information asymmetry between governance and regulatory institutions and technology companies is one of the factors affecting whether or not a problem might be defined as ‘wicked’ and solutions found (Danaher et al ). Power relationships between governments and private actors are unbalanced in the ‘depleted state’ (Lodge ), and private actors have the financial resources to recruit available talent with rewards packages that dwarf those on offer from government or academia.…”
Section: The Discursive Contextmentioning
confidence: 99%
“…Information asymmetry between governance and regulatory institutions and technology companies is one of the factors affecting whether or not a problem might be defined as 'wicked' and solutions found (Danaher et al 2017).…”
Section: The Discursive Contextmentioning
confidence: 99%