Seven principles for algorithmic accountability for product teams.

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Algorithmic Accountability Principles
Awareness
Users know where automated decisions have been made, and owners
are aware of the potential harm automated decision making can do.
Access and redress
Users have a access to a way to correct wrong decisions.
Accountability
If you deploy an algorithm you are responsible for its decisions.
Explanation
You should be able to explain the algorithm in human terms.
Data provenance
You should be able to say where did the data come from (and also
where did training set data come from).
Auditability
You need to keep records of decisions made.
Validation and testing
Keep checking the algorithm is behaving as it should.
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