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Fixed typo

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Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens
2019-03-10 11:49:46 +01:00
parent 89fa915e33
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body_expose.tex
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@ -12,9 +12,9 @@ the design of so called algorithms, a term often used in public
discourse for applied neural networks, is the question of
algorithmic accountability\cite{Diakopoulos2014}.
The charme of supervised neural networks, that they can learn from
The charm of supervised neural networks, that they can learn from
input-output relations and figure out by themselves what connections
are necessary for that, is also their achilles heel. This feature
are necessary for that, is also their Achilles heel. This feature
makes them effectively black boxes. It is possible to question the
training environment, like potential biases inside the data sets, or
the engineers constructing the networks but it is not really possible