Leon G. Ho (University of North Carolina Law) has posted “Countering Personalized Speech” (Northwestern Journal of Technology and Intellectual Property, Vol. 20, Issue 1, 2022) on SSRN. Here is the abstract:
Social media platforms use personalization algorithms to make content curation decisions for each end user. These “personalized instances of content curation” (“PICCs”) are essentially speech conveying a platform’s predictions on content relevance for each end user. Yet, PICCs are causing some of the worst problems on the internet. First, they facilitate the precipitous spread of mis- and disinformation by exploiting the very same biases and insecurities that drive end user engagement with such content in the first place. Second, they exacerbate social media addiction and related mental health harms by leveraging users’ affective needs to drive engagement to greater and greater heights. Lastly, they help erode end user privacy and autonomy as both sources and incentives for data collection.
As with any harmful speech, the solution is often counterspeech. Free speech jurisprudence considers counterspeech the most speech-protective weapon to combat false or harmful speech. Thus, to combat problematic PICCs, social media platforms, policymakers, and other stakeholders should embolden end users’ counterspeech capabilities in the digital public sphere.
One way to implement this solution is through platform-provided end user personalization tools. The prevailing end user personalization inputs prevent users from providing effective countermeasures against problematic PICCs, since on most, if not all, major social media platforms, these inputs confer limited ex post control over PICCs. To rectify this deficiency and empower end users, I make several proposals along key regulatory modalities to move end user personalization towards more robust ex ante capabilities that also filter by content type and characteristics, rather than just ad hoc filters on specific pieces of content and content creators.