Defamation by Algorithms: When Platform Recommendations Spread False Content

When a platform's recommendation algorithm pushes defamatory content from a few hundred views to millions, who is responsible for the amplified harm? This is one of the most important frontier questions in UK defamation law — and the answer is rapidly evolving.

How Algorithms Amplify Defamatory Content

Social media algorithms are designed to maximise engagement. Content that provokes strong reactions — including false allegations that generate outrage — is often algorithmically amplified, pushed to new audiences, and surfaced in recommendation feeds and "related content" sections. This creates a perverse dynamic: the more defamatory and emotionally charged the content, the more widely the platform may distribute it.

The Publisher vs Conduit Distinction

Under UK defamation law, a platform that merely hosts third-party content without editorial input is treated as a secondary publisher — with more limited liability than a primary publisher. But where a platform's algorithm actively selects specific content and promotes it to additional users, the platform is arguably making an editorial decision: it is choosing to amplify this content rather than that content. That editorial role may expose the platform to greater liability than a passive host.

The Online Safety Act 2023 and Algorithmic Amplification

The Online Safety Act 2023 imposes duties on regulated platforms to address illegal content — including defamatory content — and to have accessible, effective complaints systems. Where a platform's algorithm is actively amplifying defamatory content and the platform has been notified but fails to act, both the regulatory compliance framework and civil defamation liability are engaged simultaneously.

Evidence: Documenting the Amplification

The most important practical step is gathering evidence of the amplification. Screen recordings showing view counts, shares, and recommendation placement are valuable. Analytics data — where accessible — is even better. Evidence that content was algorithmically promoted to a much larger audience than it would have reached organically strengthens both the serious harm case and any argument for platform liability.

Injunctions Against Algorithmic Amplification

In principle, an interim injunction can restrain a specific harmful act — including the continued algorithmic promotion of identified defamatory content. The first step is serving formal notice on the platform identifying the content and demanding de-amplification or removal. This creates the evidential record of the platform's knowledge that is essential for any subsequent injunction application or liability argument.

Related reading: AI search overview defamation | Online Safety Act 2023 | Pile-on defamation