Facebook’s Algorithms Are Driving The Illegal Wildlife Trade

The illegal wildlife trade is one of the most immediate drivers of global biodiversity loss, pushing already vulnerable species toward extinction. Elephants are targeted for their ivory, rhinos for their horns, pangolins for their scales, and countless primates, parrots, small mammals, and reptiles are captured for the exotic pet trade.

Since the late 1990s, this trade has moved steadily online, migrating from early chat rooms and fragmented personal websites to mainstream social media platforms that make it easier for buyers and sellers to connect across international borders. More than a decade of public pledges from technology companies — including a 2018 coalition commitment, co-founded by Facebook, to reduce online wildlife trade by 80% by 2020 — hasn’t reversed the trend. This report argues the situation has only gotten worse.

The report, produced by the Global Initiative Against Transnational Organized Crime (GI-TOC), draws on the world’s most systematic ongoing dataset on online illegal wildlife trade to document Facebook’s dominant role in enabling that trade, assess why voluntary self-regulation has failed, and make the case for enforceable regulatory action.

How The Monitoring Works

The Global Monitoring System (GMS) is a collaborative program run by GI-TOC, the International Fund for Animal Welfare, the Wildlife Trust of India, and other partner organizations. Between April 2024 and March 2026, ten analytical data hubs spanning four continents conducted structured monitoring across sites including South Africa, Nigeria, Cameroon, Jordan, Thailand, Indonesia, India, Colombia, Brazil, and Mexico.

Each hub developed a basket of priority species to monitor. These included animals:

• Listed under Appendices I or II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES);
• Classified as endangered or critically endangered by the International Union for Conservation of Nature (IUCN) Red List of Threatened Species;
• Nationally or regionally protected by law; and/or
• Identified as local law enforcement priorities.

Every hub also monitored a shared global basket of widely trafficked species, including pangolins, tigers, rhinos, and elephants.

The hubs tracked their species across a curated list of platforms where active trading had been detected. Analysts used standardized search terms, including code words known to be used by traffickers to evade keyword filters, to locate suspected ads. All flagged posts were reviewed and quality-checked before entering the dataset.

Facebook Dominates The Illegal Trade In Wild Animals

Over the nearly two-year monitoring period, GMS analysts detected 21,904 ads across 61 platforms. Of these, 74% appeared on Facebook. The next top platform, WhatsApp, accounted for just 5%. The ads included 266,535 individual listings, 8,568 of which were live animals.

About 60% of ads included prices. The total advertised value of these listings exceeded US$66 million, of which Facebook accounted for 98%. The report notes these figures represent listed prices rather than confirmed transactions, but describe them as indicators of vast commercial scale and criminal intent.

The animals most frequently appearing in the ads were those with the strongest international protections. About 84% of Facebook detections involved species listed under CITES Appendix I, which carries a near-total international trade ban, and 58% involved species classified by the IUCN as endangered or critically endangered. Not a single ad included permits or documentation. Throughout the data, the analysts found persistent signals of illegal international activity: sellers advertising willingness to ship without paperwork, buyers and sellers communicating across multiple countries in 21 different languages, and users posting images of cross-border financial transactions and concealment methods.

Facebook groups were the primary venue for trading activity, accounting for 76% of all Facebook detections. These groups function as persistent buyer-seller communities organized around product themes, with administrators curating membership and sellers cross-posting simultaneously across many similar groups.

Most strikingly, 78% of Facebook detections were encountered without anyone actively searching for them. They appeared through the platform’s algorithm, which suggested related pages, groups, and content. The analysts also documented 542 instances where Meta’s own systems explicitly recommended illegal wildlife trade content to users — in sponsored ads, for instance.

In one documented case, a subscription-enabled Facebook page with roughly 195,000 followers — whose content centered on hunting and displaying protected animals including pangolins, clouded leopards, and gibbons — was earning revenue through Facebook’s formal monetization system and linked to a group dedicated to poaching with around 72,600 members. This appears to directly contradict Meta’s stated policies prohibiting the sale of animals and requiring policy compliance before monetization access is granted.

The report also documents consistent moderation failures. English-language posts made up only 12% of detected ads in the GMS data, yet the authors note that Facebook’s enforcement actions have largely focused on English-language content, with moderation described as sporadic in other languages. GI-TOC itself submitted a report about a publicly visible group selling pangolins and other protected species, which was reviewed and rejected by Facebook’s system.

Two structural factors help explain why Facebook’s enforcement failures have persisted. In the U.S., federal law has long shielded platforms from civil liability for user-posted content, limiting legal consequences there even as evidence of illegal wildlife trade has mounted for over a decade. Elsewhere, regulatory frameworks capable of holding platforms accountable are still catching up, though the report points to emerging legislation like the E.U. Digital Services Act as a more promising avenue.

Compounding this, in the aftermath of the Cambridge Analytica scandal (in which data from up to 87 million Facebook users was improperly accessed for political targeting), Facebook restricted the data tools that outside researchers and civil society organizations had been using to independently monitor the platform. The practical effect was to concentrate oversight in Meta’s own hands, leaving most detection work to the internal enforcement teams whose track record this report documents in detail.

What This Data Can And Can’t Tell Us

The GMS captures detected ads rather than confirmed transactions or actual stock levels. The monitoring program doesn’t cover every region or platform, and data from one hub (Czech Republic) was excluded because it had only been active for about a month when the analysis was conducted.

The report is a policy brief from an advocacy-aligned organization rather than a peer-reviewed study. Its quantitative findings are grounded in a systematic, quality-controlled dataset, but its interpretive conclusions and recommendations reflect the authors’ analytical judgment. The authors also note they don’t yet systematically track which accounts have access to Facebook’s subscription monetization tools, limiting the breadth of conclusions about that specific mechanism.

Time For Enforceable Platform Accountability

According to the authors, Facebook’s role in the illegal wildlife trade extends far beyond passive hosting. Its recommendation algorithms actively surface and amplify illegal content, its group architecture enables persistent trafficking communities to form and scale, and its monetization tools have extended to accounts centered on poaching — in direct contradiction of Meta’s stated policies. The authors argue that voluntary self-regulation has had ample time to work and has failed. They call on governments to impose enforceable duties of care on large platforms, require multilingual and multimodal proactive detection, mandate independent audits and transparency, and coordinate enforcement across borders.

For animal advocates, these findings provide a data-rich foundation for demanding regulatory action. The animals most at risk — critically endangered species protected by international trade bans — are among those appearing most frequently in Facebook ads. The platform isn’t incidentally connected to the wildlife trade; the authors argue it’s the central infrastructure through which that trade is concentrated, encountered, and scaled. Advocates working on wild animal protection have an opportunity to take this evidence directly to policymakers. The illegal trade in wild animals is a platform governance failure, and one with a known address. These animals have no voice in debates about tech regulation, but the data clearly shows that the cost of inaction falls on them.

This summary was drafted by a large language model (LLM) and closely edited by our Research Library Manager for clarity and accuracy. As per our AI policy, Faunalytics only uses LLMs to summarize very long reports (~50+ pages) that are not appropriate to assign to volunteers, studies that contain graphic descriptions of animal cruelty or animal industries, and research on niche topics. We remain committed to bringing you reliable data, which is why any AI-generated work will always be reviewed by a human.