SXSW 2019
Machine Learning and On-line Wildlife Trafficking
Description:
Wildlife trafficking is a booming, $19 billion online business, using social media platforms and e-commerce sites. In response, World Wildlife Fund (WWF) is partnering with Booz Allen Hamilton and Epidemico to apply a nuanced approach to this global problem. Borrowing from innovative tools designed to detect the origin and spread of disease, this team is deploying machine learning and artificial intelligence capabilities to predict and prevent wildlife trafficking on-line and in the dark web. Applying methods of epidemiology to detect early trends in wildlife trafficking enables WWF to respond with targeted, proactive campaigns that can reverse the market demand for threatened species, and better assist law enforcement and companies in taking preventive measures to deter illegal activity.
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Takeaways
- How can we borrow, modify, and apply innovative technologies in epidemiology detection to on-line wildlife trafficking?
- With the new insight these tools provide, how can we modify conservation campaigns and refocus resources in law enforcement to prevent trafficking?
- How can wildlife conservation organizations and the tech industry partner in the future to expand the capabilities of these predictive tools?
Speakers
- Crawford Allan, Senior Director TRAFFIC, World Wildlife Fund
- Sumiko Mekaru, Senior Associate, Epidemico
- Christopher Round, Climate Change Specialist, PhD Candidate, George Mason University
- Emilee Ritchie, Lead Associate, Climate Consulting, Booz Allen Hamilton
Organizer
Crawford Allan, Senior Director TRAFFIC, World Wildlife Fund
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