Combatting Online Extremism: Algorithmic Amplification of Counter-Speech.

Terrorists and violent extremists have historically used social media to share terrorist and violent extremist content (TVEC), which can be algorithmically amplified in certain contexts (Alvari et al., 2019). Therefore, it is suggested that algorithms should be utilised to amplify
counter-speech to target audiences, as a countering violent extremism (CVE) strategy (Schmitt et al., 2018). This PhD will explore the effectiveness and ethics surrounding the algorithmic amplification of counter-speech. By exploring the research questions, this research aims to gain a better understanding of the effectiveness of counter-speech at dissuading individuals from extreme narratives, identify counter-speech measurement, monitoring and evaluation (MME) challenges, and determine the effectiveness and limitations of algorithms in amplifying counter-speech to target
audiences. Additionally, this research will identify the key ethical principles that should underpin the algorithmic amplification of counter-speech, and determine what ethical principles currently underpin campaigns. This research is important to inform policymakers, practitioners, and tech companies of how to ethically and effectively use algorithms to amplify counter-speech, to dissuade individuals from extreme narratives. This is particularly timely given recent regulatory efforts as evidenced by the Online Safety Bill. Furthermore, this research will identify where resources
and research can address existing challenges. This will aid in combatting online extremism, and mitigate against potential negative impacts associated with counter-speech including; reinforcing extremist views, and increased polarisation.