Contribution to the handbook
Set aside · Assessed 2026-10-27
The Massachusetts facial-recognition licensing example is peripheral here: the evidence identifies its stated use but supplies no further detail that would change a design choice, risk assessment, or test decision.
Does this challenge the goal?
None identified
This asks for a specific example from the source; it does not challenge the handbook’s goal, beneficiary boundary, or assumptions.
The supplied answer gives only a brief description of the example.
Why this category?
- Specific reason for low contribution: isolated example with no supplied operational detail or design implication
The example could be useful in a fuller discussion of automated licensing, but this packet does not provide that context.
This is an AI assessment of contribution to the goal, separate from whether the question has an answer.
Identify the automated bureaucratic system the author mentions and its stated use.
What we can say so far
The author gives a Massachusetts facial-recognition system used to revoke driving licences as an example of automated bureaucracy.
What remains open
- The footnote gives no further information about the system.
Conditions and limits
- This answer relies on the readable author manuscript from an accessible mirror, rather than the publisher’s typeset version.
Evidence and related ideas
Supporting evidence, qualifications and context play different roles in this answer.
context
Human control in tax enforcement In the author’s tax-enforcement example, an algorithm can select audit targets only if a human agent requests or demands it. Another system could sort data continuously and issue recommendations, arrest warrants, or court summonses for human agents to accept or reject. A system with no human involvement would leave everything to machines.
Describes tax-enforcement examples of human control and automation, but does not identify the specific system and use given in the footnote.
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 →
supports
Facial recognition and driving licences A footnote gives a Massachusetts facial-recognition system used to revoke driving licences as an example of automated bureaucracy.
Directly identifies the Massachusetts facial-recognition system and its use in revoking driving licences.
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
Algorithms may help find tax audit leads The author proposes that algorithms could help tax agencies find patterns in financial data and recommend audits, especially when agencies have limited staff or struggle to connect information across datasets.
Describes algorithms recommending tax audits, a separate example that does not identify the system and use given in the footnote.
The Threat of Algocracy: Reality, Resistance and Accommodation