Automated Decision Systems 1, 2018

10 principles for public sector use of algorithmic decision making

United Kingdom

Actors

Nesta

Tags

Bias, Impact assessment, Accountability, Transparency, Redress, Testing/Sandboxes

Resources


In response to the growing prominence and critical nature of using automated decision systems in the delivery of government services, this proposal formulates 10 broad principles for a Code of Standards for Public Sector Algorithmic Decision Making.

  1. “Every algorithm used by a public sector organisation should be accompanied with a description of its function, objectives and intended impact, made available to those who use it.”

  2. “Public sector organisations should publish details describing the data on which an algorithm was (or is continuously) trained, and the assumptions used in its creation, together with a risk assessment for mitigating potential biases.”

  3. “Algorithms should be categorised on an Algorithmic Risk Scale of 1-5, with 5 referring to those whose impact on an individual could be very high, and 1 being very minor.”

  4. “A list of all the inputs used by an algorithm to make a decision should be published.”

  5. “Citizens must be informed when their treatment has been informed wholly or in part by an algorithm.”

  6. “Every algorithm should have an identical sandbox version for auditors to test the impact of different input conditions.”

  7. “When using third parties to create or run algorithms on their behalf, public sector organisations should only procure from organisations able to meet Principles 1-6.“

  8. “A named member of senior staff (or their job role) should be held formally responsible for any actions taken as a result of an algorithmic decision.”

  9. “Public sector organisations wishing to adopt algorithmic decision making in high risk areas should sign up to a dedicated insurance scheme that provides compensation to individuals negatively impacted by a mistaken decision made by an algorithm.”

  10. “Public sector organisations should commit to evaluating the impact of the algorithms they use in decision making, and publishing the results.”

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