Listen: Difference between revisions
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[https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/II%20-%2004.%20Natural%20language%20for%20artificial%20intelligence.mp3 Natural language for artificial intelligence] | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/II%20-%2004.%20Natural%20language%20for%20artificial%20intelligence.mp3 Natural language for artificial intelligence] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/III%20-%2000.%20ORACLES.mp3 '''Oracles'''] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/III%20-%2001.%20Racial%20AdSense.mp3 Radical AdSense] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/III%20-%2002.%20What%20is%20a%20good%20employee%3F.mp3 What is a good employee?] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/III%20-%2003.%20Quantifying%20100%20years%20of%20gender%20and%20ethnic%20stereotypes.mp3 Quantifying 100 years of gender and ethnic stereotypes] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/III%20-%2004.%20Wikimedia's%20ORES%20service.mp3 Wikimedia's ORES service.mp3] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/III%20-%2005.%20Tay.mp3 Tay] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/IV%20-%2000.%20CLEANERS.mp3 '''Cleaners'''] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/IV%20-%2001.%20Project%20Gutenberg%20and%20Distributed%20Proofreaders.mp3 Project Gutenberg and Distributed Proofreaders] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/IV%20-%2002.%20An%20algoliterary%20version%20of%20the%20Maintenance%20Manifesto.mp3 An algoliterary version of the Maintenance Manifesto] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/IV%20-%2003.%20A%20bot%20panic%20at%20Amazon%20Mechanical%20Turk.mp3 A bot panic at Amazon Mechanical Turk] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/V%20-%2000.%20INFORMANTS.mp3 '''Informants'''] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/V%20-%2001.%20Dataset%20as%20representation.mp3 Dataset as representation] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/V%20-%2002.%20Labeling%20for%20an%20oracle%20that%20detects%20vandalism%20on%20Wikipedia.mp3 Labeling for an oracle that detects vandalism on Wikipedia] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/V%20-%2003.%20How%20to%20make%20your%20dataset%20known.mp3 How to make your dataset known] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/V%20-%2004.%20The%20ouroboros%20of%20machine%20learning.mp3 The ouroboros of machine learning] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/VI%20-%2000.%20READERS.mp3 '''Readers'''] | ||
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+ | [https://gitlab.constantvzw.org/algolit/mundaneum/blob/master/exhibition/data%20workers%20podcast/EN%20for%20mp3/VI%20-%2001.%20Character%20n-gram%20for%20authorship%20recognition.mp3 Character n-gram for authorship recognition] | ||
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Revision as of 11:19, 24 May 2019
listen here!
We create 'algoliterary' works
Programmers are writing data workers into being
Natural language for artificial intelligence
Quantifying 100 years of gender and ethnic stereotypes
Project Gutenberg and Distributed Proofreaders
An algoliterary version of the Maintenance Manifesto
A bot panic at Amazon Mechanical Turk
Labeling for an oracle that detects vandalism on Wikipedia
How to make your dataset known