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Partnerships in AI Drive Conservation Efforts: WWF’s Dave Thau

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Content provided by MIT Sloan Management Review and Boston Consulting Group (BCG), MIT Sloan Management Review, and Boston Consulting Group (BCG). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by MIT Sloan Management Review and Boston Consulting Group (BCG), MIT Sloan Management Review, and Boston Consulting Group (BCG) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

Wildlife conservation efforts may not be the first thing that comes to mind when one thinks about opportunities to use artificial intelligence and machine learning. But Dave Thau, data and technology lead scientist at the World Wildlife Fund (WWF), can share myriad examples of how these technologies are helping our planet.

On this episode, Dave joins Sam and Shervin to discuss WWF’s many uses of AI and machine learning. Among them are applications that predict deforestation, analyze images from motion-sensitive cameras to identify species, optimize wildlife patrols to catch poachers, and reduce the illegal wildlife trade online. These conservation efforts are not only supported by nonprofit partners with shared goals but by tech-company partners that are sharing advanced AI technologies. Read the episode transcript here.

NEW! For specific takeaways from this episode and guidance on how you can implement them in your own work, download our episode toolkit here.

Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.

Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.

Guest bio:

Dave Thau is the World Wildlife Fund’s data and technology global lead scientist, focusing on applying artificial intelligence in conservation and using technology for long-term impact monitoring.

Previously, he worked at Google, where he helped launch Google Earth Engine and managed developer relations. He also helped to develop the Global Forest Watch nature monitoring platform with the World Resources Institute, and the Map of Life species data platform.

Thau’s work in data management, sustainability, AI, and remote sensing has been published in several journals. He is also a member of the Knowledge and Data Task Force for the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.

Thau has a doctorate in computer science from the University of California, Davis.

We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.

  continue reading

86 episoade

Artwork
iconDistribuie
 
Manage episode 361600520 series 2803274
Content provided by MIT Sloan Management Review and Boston Consulting Group (BCG), MIT Sloan Management Review, and Boston Consulting Group (BCG). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by MIT Sloan Management Review and Boston Consulting Group (BCG), MIT Sloan Management Review, and Boston Consulting Group (BCG) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

Wildlife conservation efforts may not be the first thing that comes to mind when one thinks about opportunities to use artificial intelligence and machine learning. But Dave Thau, data and technology lead scientist at the World Wildlife Fund (WWF), can share myriad examples of how these technologies are helping our planet.

On this episode, Dave joins Sam and Shervin to discuss WWF’s many uses of AI and machine learning. Among them are applications that predict deforestation, analyze images from motion-sensitive cameras to identify species, optimize wildlife patrols to catch poachers, and reduce the illegal wildlife trade online. These conservation efforts are not only supported by nonprofit partners with shared goals but by tech-company partners that are sharing advanced AI technologies. Read the episode transcript here.

NEW! For specific takeaways from this episode and guidance on how you can implement them in your own work, download our episode toolkit here.

Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.

Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.

Guest bio:

Dave Thau is the World Wildlife Fund’s data and technology global lead scientist, focusing on applying artificial intelligence in conservation and using technology for long-term impact monitoring.

Previously, he worked at Google, where he helped launch Google Earth Engine and managed developer relations. He also helped to develop the Global Forest Watch nature monitoring platform with the World Resources Institute, and the Map of Life species data platform.

Thau’s work in data management, sustainability, AI, and remote sensing has been published in several journals. He is also a member of the Knowledge and Data Task Force for the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.

Thau has a doctorate in computer science from the University of California, Davis.

We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

We want to know how you feel about Me, Myself, and AI. Please take a short, two-question survey.

  continue reading

86 episoade

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