Reminder that this starts in a few minutes. Pine
On Tue, Aug 16, 2016 at 1:50 PM, Sarah R <[email protected]> wrote: > Hi Everyone, > > The next Research Showcase will be live-streamed this Wednesday, Aug 17, > 2016 at 11:30 AM (PST) 18:30 (UTC). > > YouTube stream: http://youtu.be/rsFmqYxtt9w > > As usual, you can join the conversation on IRC at #wikimedia-research. > And, you can watch our past research showcases here > <https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase#Archive>. > > This month's showcase includes. > > Computational Fact Checking from Knowledge NetworksBy *Giovanni Luca > Ciampaglia <https://www.mediawiki.org/wiki/User:Junkie.dolphin>*Traditional > fact checking by expert journalists cannot keep up with the enormous volume > of information that is now generated online. Fact checking is often a > tedious and repetitive task and even simple automation opportunities may > result in significant improvements to human fact checkers. In this talk I > will describe how we are trying to approximate the complexities of human > fact checking by exploring a knowledge graph under a properly defined > proximity measure. Framed as a network traversal problem, this approach is > feasible with efficient computational techniques. We evaluate this approach > by examining tens of thousands of claims related to history, entertainment, > geography, and biographical information using the public knowledge graph > extracted from Wikipedia by the DBPedia project, showing that the method > does indeed assign higher confidence to true statements than to false ones. > One advantage of this approach is that, together with a numerical > evaluation, it also provides a sequence of statements that can be easily > inspected by a human fact checker. > > > Deploying and maintaining AI in a socio-technical system. Lessons learned > By *Aaron Halfaker <https://www.mediawiki.org/wiki/User:Halfak_(WMF)>*We > should exercise great caution when deploying AI into our social spaces. The > algorithms that make counter-vandalism in Wikipedia orders of magnitude > more efficient also have the potential to perpetuate biases and silence > whole classes of contributors. This presentation will describe the system > efficiency characteristics that make AI so attractive for supporting > quality control activities in Wikipedia. Then, Aaron will tell two stories > of how the algorithms brought new, problematic biases to quality control > processes in Wikipedia and how the Revision Scoring team > <https://meta.wikimedia.org/wiki/R:Revision_scoring_as_a_service> learned > about and addressed these issues in ORES > <https://meta.wikimedia.org/wiki/ORES>, a production-level AI service for > Wikimedia Wikis. He'll also make an overdue call to action toward > leveraging human-review of AIs biases in the practice of AI development. > > We look forward to seeing you! > > -- > Sarah R. Rodlund > Senior Project Coordinator-Engineering, Wikimedia Foundation > [email protected] > > _______________________________________________ > Analytics mailing list > [email protected] > https://lists.wikimedia.org/mailman/listinfo/analytics > >
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