File:Deploying and maintaining AI in a socio-technical system -- Research Showcase (August 2016).pdf
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Summary
| Description |
English: 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 learned about and addressed these issues in 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. |
| Date | |
| Source | Own work |
| Author | EpochFail |
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 18:03, 17 August 2016 |  | 1,500 × 843, 105 pages (6.21 MB) | EpochFail | Added credit to Zeynep's photo |
| 16:44, 17 August 2016 |  | 1,500 × 843, 105 pages (6.21 MB) | EpochFail | User created page with UploadWizard |
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