A starting point for discussion
The idea
The author separates two concerns about systems used to guide public decisions. Hiddenness means concern about how data is collected and used. Opacity means concern about whether people can understand the reasons behind decisions.
Place in the reasoning
AI assessment · Connected to reasoning
Distinguishes hiddenness about data collection and use from opacity about understanding decision reasoning, a distinction relevant to the narratives’ focus on explanation and scrutiny.
People need to understand decisions before they can check them
The distinction clarifies that reviewability and understanding address opacity, not necessarily hidden data practices or privacy.
What this means and why it matters
What this means
Hiddenness concerns data practices that may happen without people’s knowledge or agreement. Opacity concerns decisions that people cannot understand.
Why it matters
This distinction helps show that concerns about personal information and concerns about understanding decisions are not the same problem.
Conditions & assumptions
Source coverage: The full readable author manuscript from an online copy, not the publisher’s formatted version. The passage names hiddenness, concern about how data is collected and used, and opacity, concern about whether people can understand decisions. It treats them as distinct concerns. Addresses: The moral and political concerns in the discussion.
Questions this connects to
AI-suggested relationships. Authors have not necessarily responded to one another.
How strong is this claim?
AI assessment · not a probability or a final resolution
The passage explains both concerns and how they differ.