case study

Tackling wildlife trafficking
and exploitation in social
media and e-commerce

Industrial Area
Applied research
Global Challenges
Combating biodiversity loss
Delivered in 2023
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Battling crime against animals

The proliferation of social media and e-commerce platforms has inadvertently provided a virtual haven for illegal wildlife trafficking and animal abuse. These platforms facilitate covert transactions and exchanges, allowing criminals to operate with a global reach while remaining relatively anonymous. Machine learning algorithms can actively monitor these platforms, flagging content that exhibits signs of potential wildlife crime or animal abuse, such as the sale of endangered species or the showcasing of cruel acts.

Wildlife preservation is a central focus for the impact investment company Wild Around, particularly in the realm of conservation technologies. In pursuit of this goal, Magnetic Core has conducted initial research into existing machine learning algorithms and strategies aimed at combating the trafficking of wildlife and instances of animal abuse. This research not only assesses the advancements made by current stakeholders but also research a possible model that could serve as a framework for formalizing efforts within the domain of social media platforms and e-commerce.


How to create a stable model that allows the identification of wildlife exploitation in images and videos and connects it to the moderation process


A well-balanced data categorization algorithm serves as the cornerstone for an ethical model that can be open-sourced for extensive utilization


Wildlife crime trails identification

Automatic identification of unethical content and moderation can assist law enforcement agencies and special institutions by providing data and possible evidence for exposure of organized crime groups, deeper investigation or legal actions against wildlife traffickers and abusers

Public awareness

Successful implementation can raise awareness about wildlife crime and animal abuse issues among the general public so they potentially stay away from sharing unethical content and report suspicious cases more often


Shared open-source algorithm and strategies can facilitate collaboration among different platforms, NGOs, and law enforcement agencies, fostering a united front against wildlife crime.

Resource optimization

Automation frees up human moderators to focus on more complex cases, while machine learning handles routine tasks.

The successful implementation of machine learning algorithms and strategies can lead to a significant reduction in wildlife trafficking and animal abuse, thereby contributing to the preservation 
of endangered species and the well-being of animals. Moreover, it sends a strong message that the digital realm is not a safe haven for criminal activities.
We have to strive for a world where digital platforms contribute to the protection of our planet's precious biodiversity and the welfare of its inhabitants by harnessing the power of automation, data analysis, and global collaboration.
Elena Goldberg, Wild Around Founder and CEO

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