A year after ADL's "Editing for Hate," bias still shapes Wikipedia, and even banned editors' work remains unreviewed.

Examining antisemitism, exclusion and representation in higher education unions, and how stronger democratic practices can better serve all members.

A classroom RCT experiment shows that teaching antisemitism as a recurring conspiracy reduces teens' endorsement of antisemitic tropes.

Examining trends in faculty-driven antisemitism and how classroom practices, academic structures and institutional dynamics shape Jewish student experiences.

This report details the real human impact of some of the sites Cloudflare sustains and evaluates the systemic policy and enforcement gaps that allow them to remain operational.

ADL study finds popular open-source LLMs can easily be manipulated by malicious actors to produce antisemitic, extremist, and dangerous content amid weak safety guardrails.

A groundbreaking study supported by ADL found that fact-based dialogues with a trained AI chatbot durably reduced antisemitic conspiracy beliefs and increased favorability toward Jews.

ADL examined the strategic evolution of anti-Israel activism on U.S. campuses and provides recommendations for universities to respond proactively to changing tactics.

This joint ADL-Jewish Federations research shows the normalization of antisemitism and its effects on American Jews’ mental health and feelings of safety.

Surveyed faculty report widespread antisemitism on campuses and in associations, with growing professional, emotional, and mental health impacts.

Research by the ADL Center for Tech & Society (CTS) found that the term ‘false flag’ ranked as the second most popular term on Reddit in a sample of conversations about the antisemitic Boulder attack and the fifth most popular following the D.C. Capitol Jewish Museum attack.

A new ADL survey found that a substantial number of Americans justify or excuse violence against Jews while most still reject antisemitism and want action taken against it.

On social media and gaming platforms, hate and harassment thrive in closed online spaces, which lack the visibility and accountability of more open or public ones.

ADL’s RAI and CCAE found high rates of antisemitism in independent K-12 schools, especially within curricula, with insufficient response from administrators.

Artificial intelligence is rapidly reshaping how people consume and trust information—including what books they read. Amazon, the world’s largest bookseller, uses Large Language Models (LLMs) to generate short, snappy summaries of customer reviews. While this may be useful when applied to bedsheets or kitchen appliances, applying AI to book reviews—without human oversight—is proving to be deeply problematic. We found that AI-generated reviews are promoting books that…

 Co-produced with Builders For Tomorrow  Executive SummaryADL research shows that four leading LLMs, particularly Llama, display bias against Jews and Israel. LLM bias in other areas has already been highlighted; this report provides the most comprehensive evaluation to date of anti-Jewish and anti-Israel bias in major LLMs—GPT (OpenAI), Claude (Anthropic), Gemini (Google), and Llama (Meta).     In 2025 and beyond, the importance of large language model (LLM)…

Co-produced with Builders For Tomorrow Executive Summary ADL has identified extensive issues with antisemitic and anti-Israel bias on Wikipedia in multiple languages. These issues include 1) a coordinated campaign to manipulate Wikipedia content related to Israel, the Israeli-Palestinian conflict, and similar issues, in which a group of editors systematically evade Wikipedia’s rules to shift balanced narratives toward skewed ones, spotlighting criticism of Israel and downplaying…