When scholars sprint, bad algorithms are on the run
Author: | Kettemann, M. C., & Pirang, A. |
Published in: | Digital society blog |
Year: | 2020 |
Type: | Other publications |
In response to increasing public pressure to tackle hate speech and other challenging content, platform companies have turned to algorithmic content moderation systems. These automated tools promise to be more effective and efficient in identifying potentially illegal or unwanted material. But algorithmic content moderation also raises many questions – all of which eschew simple answers. Where is the line between hate speech and freedom of expression – and how to automate this on a global scale? Should platforms scale the use of AI tools for illegal online speech, like terrorism promotion, or also for regular content governance? Are platforms’ algorithms over-enforcing against legitimate speech, or are they rather failing to limit hateful content on their sites? And how can policymakers ensure an adequate level of transparency and accountability in platforms’ algorithmic content moderation processes?
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Connected HIIG researchers
Matthias C. Kettemann, Prof. Dr. LL.M. (Harvard)
Alexander Pirang