CyberWell sends social media companies recommendations to improve antisemitism moderation
By Alex Carson
The guidance was submitted as a public comment this month in response to a call for input from Meta's Oversight Board regarding the use of large language models in content moderation
CyberWell released new guidance for social media companies earlier this month on improving artificial intelligence content moderation to better target antisemitism, while protecting free expression.
The guidance was submitted as a public comment this month in response to a call for input from Meta’s Oversight Board on the use of large language models (LLMs) in content moderation, addressing both the potential efficiencies of automated review and the persistent challenges of interpreting nuanced content at scale.
“AI gives platforms an unprecedented opportunity to improve the enforcement of their own rules at scale, moving beyond slur lists toward context-based decisions that can help reduce human error. However, expert input is crucial to ensuring these systems can effectively address specific forms of online hate,” CyberWell founder and CEO Tal-Or Cohen Montemayor said.
“Antisemitism constantly evolves through coded language, symbols, cultural references, and forms of ‘algospeak’ designed to evade automated detection. AI moderation systems must draw on contextual, linguistic, and subject-matter expertise to recognize the antisemitic message, not just the words, while protecting legitimate expression. Social media platforms have also struggled to draw the line between anti-Jewish scapegoating – a classic form of antisemitism– and misinformation and disinformation campaigns that receive different moderation treatment,” Cohen Montemayor added.
In its submission, Cyberwell detailed several technical challenges that automated systems frequently fail to catch.
