Practical implementations of AI & ML in conservation contexts

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Resources Shared

• Presentation Slides
• NetHope’s Emerging Technologies Initiative
• NetHope Global Summit
• [Summit] October 23: How to get started with AI
• [Summit] October 23: Turning Ideas Into AI-Enabled Solutions
• AI primer webinar
• AI for Good Framework
• Artificial Intelligence and Machine Learning tools, services, training
• Mapping Ocean Wealth
• The Nature Conservancy
• Project Home Page: Mapping Ocean Wealth
• Project Publications:
  • Spalding et al. (2017). Mapping the Global Value and Distribution of Coral Reef Tourism. Marine Policy. 82, pp 104-113. https://doi.org/10.1016/j.marpol.2017.05.014
  • Spalding et al. (2019). Estimating Reef-Adjacent Tourism Value in the Caribbean. Report.
• Videos:
  • Transforming Our World: Mapping Ocean Wealth
  • Mapping Ocean Wealth With The Power of AI

Learn about Artificial Intelligence (AI) and Machine Learning and how to incorporate AI into your programs and projects. This session will provide an introduction to two practical implementations of AI in the conservation context, highlight lessons learned from some of the early implementations of AI in our sector, and inspire new ideas and partnerships.

• Protection Assistant for Wildlife Security (PAWS) helps park rangers design effective patrol routes to prevent poaching of wildlife in large national parks.  Developed by Carnegie Mellon University in partners with WCS, WWF, and other partners.
• Mapping Ocean Wealth (MOW) is a global initiative to map coastal and ocean ecosystem services and the benefits nature provides to people. AI techniques in image recognition, such as Deep Learning, were used to classify geo-tagged photos from Flickr combined with global data provided by the tourism industry to map tourism benefits provided by coral reefs in the Caribbean region. Developed by The Nature Conservancy in partners with UCSC and Critigen.

Each presentation will answer several questions from the framework that was developed by NetHope and NetHope members in collaboration with the University of California in Irvine, USAID, MIT, and several other partners.

• What problem are you trying to solve?
• How is the problem being addressed today?
• Why is AI better than the current solution?
• What is the solution?
• What kinds of data does your solution need?
• What resources do you need to support the development, implementation, and maintenance of the solution?
• What are the potential biases that AI may introduce or amplify in your context?
• What is your approach to maintaining the solution?

Note: This is the second of two webinars we have planned before the Summit with the goal to prepare for the conversations at the Summit.

• [Pre-Summit] August 27: AI Primer
• [Summit] October 21: AI for Good Working Group meeting, with the focus on ethical AI and AI tools and services. All NetHope members are welcome, partners are by invitation-only.
• [Summit] October 23: How to get started with AI
• [Summit] October 23: Turning Ideas Into AI-Enabled Solutions

Host

Leila Toplic, Lead for Emerging Technologies at NetHope

Speakers

	Fei Fang, Assistant Professor, Carnegie Mellon University
	Francesco Tonini, Geospatial Data Scientist, The Nature Conservancy

Photo: Lorenzo Mittiga/TNC Photo Contest 2019

Collateral

• September_19_Webinar.pdf
• 20190919_NetHopeWebinar_PAWS_CMU.pdf
• NetHope_AI4G_FrancescoTonini.pdf

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