21-Mitigating algorithmic bias Flashcards

1
Q

What is out-group homogeneity bias?

A

Humans tend to perceive out-group members as less nuanced than in-group members

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2
Q

What is correlation fallacy?

A

Humans mistake correlation with causality

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3
Q

What is historical bias?

A

A randomly sampled dataset reflects the world as it was including existing biases which should not be carried forward

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4
Q

What is representation/reporting bias?

A

Datasets do not faithfully represent the whole population

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5
Q

What is measurement bias?

A

Bias within the dataset, due to:
- Noisy measurement
- Noisy proxy
- Oversimplification of quality of interest

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6
Q

What are biased loss functions?

A

Blind to certain types of errors

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7
Q

What is evaluation bias?

A

Bias where the test set is not representative of the target population

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8
Q

What is deployment bias?

A

Use of systems in ways that they weren’t intended to be used

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9
Q

What is the machine learning pipelien?

A

World -> measure -> data
data -> learn -> model
model -> action -> individual
individual -> feedback -> model

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10
Q

What are sensitive attributes?

A

Attributes that we don’t want to decision on

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11
Q

What is fairness through unawareness?

A

Hide all sensitive features from classifier

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