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daviddao/awful-ai: Awful AI - 2021 Edition

Authors: Dao, David; Hugo, W.; Alf-André Walla; VocalFan; Rubiel, Eric; Schreiber, Fabian; Jaworski, Jan; +10 Authors

daviddao/awful-ai: Awful AI - 2021 Edition

Abstract

2021 Edition 🎉 This is the initial release of the Awful AI list. The list was created in 2018 after more and more awful AI applications appeared in the wild. In 2019 we added the annual Awful AI prize to raise more awareness and keep a record of an outstanding incident. Over the years we added more examples and three new categories: Misleading platforms, and scams Accelerating the climate emergency Autonomous weapon systems and military Release strategy In order to keep track of major changes, we will aim to release an annual version of the list to keep things updated and citable at Zenodo.

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Keywords

machine learning, fairness, artificial intelligence, ethics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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1
Average
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345
36
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