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Add Accountability and Auditability section

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Tobias Eidelpes 2021-12-17 20:43:01 +01:00
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trustworthy-ai.tex
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@ -430,6 +430,21 @@ noticeable impact on the information contained in the dataset.
\subsection{Accountability and Auditability}
Accountability of artificial intelligence systems refers to how much the system
can be trusted and who should be held accountable in case of errors. Due to the
black-box nature of some machine learning algorithms, accountability is
difficult to establish. With a lack of explainability knowing which part of the
system is responsible for which output is an impossible task. Auditability
partially relies on accountability to function properly. Without accountability
auditing an artificial intelligence system does not offer much insight as the
question of responsibility is not answered. Especially with regards to
widespread adoption of AI and the necessity for regulation of such systems,
auditability provides a basis from which decisions pertaining the use of AI are
made possible. If AI leaves an \emph{audit trail} behind every time it makes a
prediction, trust in the system is easier to establish since actions can be
traced and uncertainties in case the system does not behave as expected are
removed by proper regulations.
\subsection{Environmental Well-Being}