When good intentions are combined with a lack of knowledge and naive expectations.
See also: Filterbubbles.
There are two types:
Because people don't question decisions from a "neutral" algorithm, this faith can be abused.
Facebook: "We are just a platform".
NEW TECHNIQUES LIKE "MACHINE LEARNING" ARE MAKING MATHWASHING A BIGGER PROBLEM:
These learning algorithms teach themselves to clasify things by looking at huge amounts of example data.
This data will reflect current societal inequalities, like women getting paid less than men, which the algorithms will consider the norm.
Algorithms pick up on current inequalities, and amplify them.
"Old-boys Algorithms" create feedback loops that perpetuate current inequalities.
Even their designers cannot exactly explain how self-learning parts of their algorithms make their final decisions. This offers a clever path to avoiding responsibility.
Algorithms can evaporate accountability.
"The algorithm did it"