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