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

Author(s)
Danaher, John  
Hogan, Michael J.  
Noone, Chris  
Shankar, Kalpana  
et al.  
Uri
http://hdl.handle.net/10197/9193
Date Issued
2017-12-01
Date Available
2018-01-23T17:44:07Z
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 governance structures are both? This article shares the results of a collective intelligence workshop that addressed exactly this question. The workshop brought together a multidisciplinary group of scholars to consider (a) barriers to legitimate and effective algorithmic governance and (b) the research methods needed to address the nature and impact of specific barriers. An interactive management workshop technique was used to harness the collective intelligence of this multidisciplinary group. This method enabled participants to produce a framework and research agenda for those who are concerned about algorithmic governance. We outline this research agenda below, providing a detailed map of key research themes, questions and methods that our workshop felt ought to be pursued. This builds upon existing work on research agendas for critical algorithm studies in a unique way through the method of collective intelligence.
Sponsorship
Irish Research Council
Other Sponsorship
Whitaker Institute, NUI Galway
Type of Material
Journal Article
Publisher
Sage
Journal
Big Data and Society
Volume
4
Issue
2
Copyright (Published Version)
2017 the Authors
Subjects

Big data

Technology and data

Privacy

Equity

DOI
10.1177/2053951717726554
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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Big_Data_and_Society_2017.pdf

Size

654.44 KB

Format

Adobe PDF

Checksum (MD5)

c0ff75b875809696ce87105e1dc3593d

Owning collection
Information and Communication Studies Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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