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SUMMARY:The Social Impact of Automatic Hate Speech Detection - Dr. Stefani
 e Ullmann\, Postdoctoral Research Associate\, Centre for Humanities and So
 cial Change
DTSTART:20191022T121000Z
DTEND:20191022T130000Z
UID:TALK133069@talks.cam.ac.uk
CONTACT:Dr Nanna K L Kaalund
DESCRIPTION:In this talk\, I explore quarantining as a more ethical method
  for delimiting the spread of Hate Speech via online social media platform
 s. Currently\, companies like Facebook\, Twitter\, and Google generally re
 spond reactively to such material: offensive messages that have already be
 en posted are reviewed by human moderators if complaints from users are re
 ceived. The offensive posts are only subsequently removed if the complaint
 s are upheld\; therefore\, they still cause the recipients psychological h
 arm. In addition\, this approach has frequently been criticised for delimi
 ting freedom of expression\, since it requires the service providers to el
 aborate and implement censorship regimes. In the last few years\, an emerg
 ing generation of automatic Hate Speech detection systems has started to o
 ffer new strategies for dealing with this particular kind of offensive onl
 ine material. Anticipating the future efficacy of such systems\, the prese
 nt article advocates an approach to online Hate Speech detection that is a
 nalogous to the quarantining of malicious computer software. If a given po
 st is automatically classified as being harmful in a reliable manner\, the
 n it can be temporarily quarantined\, and the direct recipients can receiv
 e an alert\, which protects them from the harmful content in the first ins
 tance. The quarantining framework is an example of more ethical online saf
 ety technology that can be extended to the handling of Hate Speech. Crucia
 lly\, it provides flexible options for obtaining a more justifiable balanc
 e between freedom of expression and appropriate censorship.\n
LOCATION:The Richard King Room\, Darwin College
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