Contribution to the handbook
Supporting · Assessed 2026-10-27
The distinction helps prevent a narrow account of algorithmic opacity from being mistaken for a privacy issue alone, and it connects opacity to participation and public authority. It provides useful framing, but does not itself specify a governance mechanism.
Does this challenge the goal?
In-scope gap
The question distinguishes privacy-related hiddenness from opacity understood as difficulty participating in or understanding public procedures. This clarifies risks within the existing scope without contesting the goal.
The source presents a conceptual distinction; it does not establish how the concerns overlap in particular systems.
Why this category?
- Clarifies a consequential risk concept
- Useful framing for scrutiny and safeguards
- Limited direct mechanism or implementation detail
This is a conceptual account from the supplied source interpretation, not evidence about the frequency or effects of opacity in public systems.
This is an AI assessment of contribution to the goal, separate from whether the question has an answer.
Authority, accountability and resilience →
Read the exploration goalState what the author says opacity is about and how he says some theorists had framed it.
What we can say so far
Danaher says opacity concerns whether people can understand algorithmic decision processes and, politically, whether algorithmic systems undermine their participation in public procedures. He distinguishes this from privacy: some theorists had framed opacity in terms of privacy and control over personal information, whereas he treats those as concerns associated with hiddenness, not opacity itself.
What remains open
- The supplied material does not assess how often privacy and opacity overlap in particular systems.
Conditions and limits
- This reports the author's position as represented in a readable manuscript mirror, not the publisher's typeset version.
- The answer describes a conceptual distinction; the supplied evidence does not establish how often privacy and opacity concerns overlap in practice.
Evidence and related ideas
Supporting evidence, qualifications and context play different roles in this answer.
supports
Understanding may be the deeper problem Danaher says difficulty understanding how an algorithm shapes a decision may be as serious as, or more serious than, the fact that its role is hidden. He uses opacity to mean that people may find a process hard to understand through human reasoning.
Adds that opacity can mean difficulty understanding how a decision process works.
The Threat of Algocracy: Reality, Resistance and Accommodation
Read full source: The Threat of Algocracy: Reality, Resistance and Accommodation (opens in a new tab) ↗Read source discussion: The Threat of Algocracy: Reality, Resistance and Accommodation →
context
Some systems are hard to explain Some data-mining systems are interpretable: people can explain their reasons and factors in ordinary language. Others are non-interpretable because their workings are too complex for people to understand.
Explains the related distinction between interpretable and non-interpretable systems, but does not address theorists' privacy framing.
The Threat of Algocracy: Reality, Resistance and Accommodation