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English: "Engineering at the Intersection of Productive Efficiency, Ideology, and Ethical AI in Wikipedia". BIDS Data Science Lecture Series | February 24, 2017 | 1:10-2:30 p.m. | 190 Doe Library, UC Berkeley

Speaker: Aaron Halfaker, Principal Research Scientist, Wikimedia Foundation; Senior Scientist, University of Minnesota

Wikipedia has become a dominant source of reference information for more than half a billion people every month. Through its improbable rise to popularity, this "free encyclopedia that anyone can edit" has become a synecdoche for open production communities online. In order to operate at massive scales (~160k edits per day), Wikipedians have embraced algorithmic technologies that bring efficiency and consistency to the wiki's complex, distributed processes. These algorithms mediate social processes, governance decisions, and editors' perceptions of each other. Specifically, so-called "black box" artificial intelligences have proven invaluable for supporting curation activities at scale, but they also have the potential to silence voices and introduce ideologically founded biases in insidious ways. Despite Wikipedians' open/audit-able processes, that's exactly what's been happening. In this talk, I'll introduce "ORES," an open AI platform that is designed to enable Wikipedia's technologists to enact alternative ideological visions and to enable researchers to easily perform audits. I'll share some lessons that we've learned maintaining a large-scale, generalized AI service and discuss a call to action direct towards critical algorithms researchers to take advantage of this platform for their studies.

0:00-7:00 General introduction to Wikipedia
7:00-13:00 Part 1: Wikipedia a a socio-technical system (biological metaphor)
13:00-19:33 Summarizing governance of Wikipedia
19:33-22:08 Quality control
22:08-23:40 Community management
23:40- Adaptation and the future
36:35- Part 3: Infrastructure for socio-technical change
52:35-55:34 Empowerment vs. Power over
55:34-56:29 Summary
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Source YouTube: Engineering at the Intersection of Productive Efficiency, Ideology, and Ethical AI in Wikipedia – View/save archived versions on archive.org and archive.today
Author Berkeley Institute for Data Science (BIDS)

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Attribution: Berkeley Institute for Data Science (BIDS)
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This file, which was originally posted to YouTube: Engineering at the Intersection of Productive Efficiency, Ideology, and Ethical AI in Wikipedia – View/save archived versions on archive.org and archive.today, was reviewed on 5 March 2017 by reviewer INeverCry, who confirmed that it was available there under the stated license on that date.

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Date/TimeThumbnailDimensionsUserComment
current01:54, 1 March 201756 min 29 s, 1,920 × 1,080 (239.56 MB)Atlasowa (talk | contribs)Imported media from https://www.youtube.com/watch?v=LYF-3t14CSc

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