Abstract
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IN THEIR COLUMN “Learning
Machine Learning” (Dec. 2018),
Ted G. Lewis and Peter J. Denning
raised a crucial question about
machine learning systems: “These
[neural] networks are now used for critical
functions such as medical diagnosis …
fire-control systems. How can we trust the
networks?” They answered: “We know
that a network is quite reliable when its
inputs come from its training set. But
these critical systems will have inputs
corresponding to new, often unanticipated
situations. There are numerous
examples where a network gives poor
responses for untrained inputs.”