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Cited by 519Ethics and Social Impacts of AIPolitical Theory and DemocracyE-Government and Public Services

The threat of algocracy: reality, resistance and accommodation

Open access
Danaher, John·2016·Philosophy & Technology
DOI 10.1007/s13347-015-0211-1
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Crossref · 10.1007/s13347-015-0211-1

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61 of 61 references verified0 citation errors · 0 not checkable

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  • Algorithms are increasingly being used to nudge, bias, guide, provoke, control, manipulate and constrain human behaviour.

    “Whether we like it or not, algorithms are increasingly being used to nudge, bias, guide, provoke, control, manipulate and constrain human behaviour.”

    From Algorithmic governance: Developing a research agenda through the power of collective intelligence (2017) · cites this paper as Danaher, 2016

    The Abstract describes increasing reliance on algorithms in public decision-making and warns that algocratic systems may constrain human participation. Section 3 also says self-tracking apps can help with goal setting and habit formation. These passages support the broad point that algorithms increasingly guide or constrain behaviour, but they do not establish the full list of effects, particularly provoking and manipulating people. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • The concern is not only whether AI improves efficiency but also whether algorithmic assistance remains compatible with accountable justification, discretionary control, and rule-of-law legitimacy.

    “In public-law terms, the concern is not only whether AI improves efficiency but also whether algorithmic assistance remains compatible with accountable justification, discretionary control, and rule-of-law legitimacy (Danaher, 2016;Binns, 2018;Busuioc, 2021).”

    From From Human Oversight to Cognitive Sovereignty: A Process-Based Governance Standard for AI-Assisted Legal Reasoning (2026) · cites this paper as Danaher, 2016

  • Cognitive Sovereignty responds to the threat of algocracy: the risk that governance becomes dependent on decision systems whose operation is not meaningfully contestable by the persons subject to them.

    “In this sense, Cognitive Sovereignty responds to the threat of algocracy: the risk that governance becomes dependent on decision systems whose operation is not meaningfully contestable by the persons subject to them (Danaher, 2016).”

    From From Human Oversight to Cognitive Sovereignty: A Process-Based Governance Standard for AI-Assisted Legal Reasoning (2026) · cites this paper as Danaher, 2016

  • Lack of interpretability may lead to 'algocracy', in which the legitimacy of public decision-making processes is thwarted by the opacity of certain algocratic governance systems.

    “This may lead to ‘algocracy’, in which ‘the legitimacy of public decision-making processes’ is thwarted by ‘the opacity of certain algocratic governance systems’ (Danaher, 2016).”

    From Algorithmic Accountability and Public Reason (2018) · cites this paper as Danaher, 2016

  • The concepts of 'legitimacy' and 'effectiveness' were similar to concepts used in pre-existing literature on the problems of algorithmic governance.

    “were similar to concepts used in the pre-existing literature on the problems of algorithmic governance (e.g. Danaher, 2016; Zarsky, 2016)”

    From Algorithmic governance: Developing a research agenda through the power of collective intelligence (2017) · cites this paper as Danaher, 2016

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Cites

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11 of the 72 references couldn’t be matched to a known paper.

Research works printed but not linked: 6

  1. Clark, A. 2010. Supersizing the Mind. Oxford: OUP.
  2. Crawford, K. and Schultz, J. 2014. Big Data and Due Process: Towards a Framework to Redress Predictive Privacy Harms. Boston College Law Review 55: 93
  3. Habermas, J. 1990. Discourse Ethics: Notes on a Program of Philosophical Justification. In Moral Consciousness and Communicative Action. Trans. Christian Lenhart and Shierry Weber Nicholson. Cambridge, MA: MIT Press.
  4. Pentland, A. 2014. Social Physics. London: Penguin Press.
  5. Seaver, N. 2013. Knowing Algorithms. In Media in Transition 8, Cambridge MA.
  6. Zarsky, T. 2013. Transparent Prediction. University of Illinois Law Review 4: 1504

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Authors
Danaher, J.
Affiliations
Ollscoil na Gaillimhe – University of Galway (IE)
Corresponding author
Danaher, John
ORCID
Danaher, John
Venue
Philosophy & Technology
Publisher
Springer Science and Business Media LLC
Published
2016-01-09
Volume
29
Issue
3
Pages
245-268
ISSN
  • 2210-5433 (ISSN-L)
  • 2210-5441
DOI
10.1007/s13347-015-0211-1
OpenAlex
W2242985385
Cited by
519
References
72
Citations by year
2026: 85 · 2025: 57 · 2024: 59 · 2023: 64 · 2022: 74 · 2021: 58 · 2020: 40 · 2019: 36 · 2018: 27 · 2017: 13 · 2016: 6
FWCI
66.79
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Philosophy & Technology (publishedVersion)
  • PhilPapers (PhilPapers Foundation) (submittedVersion)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Political Science and International Relations › Political Theory and Democracy
  • Social Sciences › Political Science and International Relations › E-Government and Public Services
Keywords
algocracy, algorithmic governance, algorithmic decision-making, political legitimacy, epistocracy, public decision-making, human participation, social decision-making

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