Profiling vandalism in Wikipedia: A Schauerian approach to justification
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  • 作者:Paul B. de Laat
  • 刊名:Ethics and Information Technology
  • 出版年:2016
  • 出版时间:June 2016
  • 年:2016
  • 卷:18
  • 期:2
  • 页码:131-148
  • 全文大小:709 KB
  • 刊物类别:Computer Science
  • 刊物主题:Management of Computing and Information Systems
    Technology Management
    Ethics
    User Interfaces and Human Computer Interaction
    Library Science
  • 出版者:Springer Netherlands
  • ISSN:1572-8439
  • 卷排序:18
文摘
In order to fight massive vandalism the English-language Wikipedia has developed a system of surveillance which is carried out by humans and bots, supported by various tools. Central to the selection of edits for inspection is the process of using filters or profiles. Can this profiling be justified? On the basis of a careful reading of Frederick Schauer’s books about rules in general (1991) and profiling in particular (2003) I arrive at several conclusions. The effectiveness, efficiency, and risk-aversion of edit selection all greatly increase as a result. The argument for increasing predictability suggests making all details of profiling manifestly public. Also, a wider distribution of the more sophisticated anti-vandalism tools seems indicated. As to the specific dimensions used in profiling, several critical remarks are developed. When patrollers use ‘assisted editing’ tools, severe ‘overuse’ of several features (anonymity, warned before) is a definite possibility, undermining profile efficacy. The easy remedy suggested is to render all of them invisible on the interfaces as displayed to patrollers. Finally, concerning not only assisted editing tools but tools against vandalism generally, it is argued that the anonymity feature is a sensitive category: anons have been in dispute for a long time (while being more prone to vandalism). Targeting them as a special category violates the social contract upon which Wikipedia is based. The feature is therefore a candidate for mandatory ‘underuse’: it should be banned from all anti-vandalism filters and profiling algorithms, and no longer be visible as a special edit trait.KeywordsAlgorithmsBotsDiscriminationProfilingRulesVandalismWikipedia
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