DiscoverConsequentialEnron, Wikipedia and the Deal with Biased Low-Friction Data
Enron, Wikipedia and the Deal with Biased Low-Friction Data

Enron, Wikipedia and the Deal with Biased Low-Friction Data

Update: 2020-12-16
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The Enron emails helped give us spam filters, and many natural language processing and fact-checking algorithms rely on data from Wikipedia. While these data resources are plentiful and easily accessible, they are also highly biased. This week, we speak to guests Amanda Levendowski and Katie Willingham about how low-friction data sources contribute to algorithmic bias and the role of copyright law in accessing less troublesome sources of knowledge and data.

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Enron, Wikipedia and the Deal with Biased Low-Friction Data

Enron, Wikipedia and the Deal with Biased Low-Friction Data

Block Center for Technology and Society