Community science observational datasets are useful in epidemiology and ecology for modeling species distributions, but the heterogeneous nature of the data presents significant challenges for standardization, data quality assurance and control, and workflow management. In this paper, we present a data workflow for cleaning and harmonizing multiple community science datasets, which we implement in a case study using eBird, iNaturalist, GBIF, and other datasets to model the impact of highly pathogenic avian influenza in populations of birds in the subantarctic. We predict population sizes for several species where the demographics are not known, and we present novel estimates for potential mortality rates from HPAI for those species, based on a novel aggregated dataset of mortality rates in the subantarctic.

I recently gave an informal talk to a class of botany students at Gavilan College. The original topic was nature photography, but I also talked about the data science techniques that I used to create my recently completed photo book, Portraits of Birds: Shoreline Park. The concept for the book was to try to personally take photos of all of the bird species in a particular area, in this case Shoreline at Mountain View Park in Mountain View, California, which I later expanded to include the Palo Alto Baylands. To enumerate the species that have been seen in this area, I turned to two citizen science sites, iNaturalist and eBird, both of which have application programmatic interfaces (APIs). Note that while eBird is specific to birds, iNaturalist contains data on plants and other animals as well.

Artificial Intelligence (AI), defined as the capability of machines to imitate intelligent human behavior and learn from data, is considered by many to be the final frontier of computing. And environmentalists and tech companies are now harnessing the power of AI to service to the environment. To wit, Microsoft announced in December 2017 that it is expanding its "AI for Earth" program and committing $50 million over the next five years to put AI technologies in the hands of individuals and organizations working to solve global environmental challenges, including climate change as well as water, agriculture and biodiversity issues. Lucas Joppa, Microsoft's first chief environmental scientist, is convinced that AI is now mature enough and the global environmental crisis acute enough to justify the creation of an AI platform for the planet. "I believe that for every environmental problem, governments, non-profits, academia and the technology industry need to ask two questions: 'How can AI help solve this?' and'How can we facilitate the application of AI?'," Joppa said.

Dear EarthTalk: What are some ways Artificial Intelligence (AI) is being used to fight climate change and otherwise protect the environment? Artificial Intelligence (AI), defined as the capability of machines to imitate intelligent human behavior and learn from data, is considered by many to be the final frontier of computing. And environmentalists and tech companies are now harnessing the power of AI to service to the environment. To wit, Microsoft announced in December 2017 that it is expanding its "AI for Earth" program and committing $50 million over the next five years to put AI technologies in the hands of individuals and organizations working to solve global environmental challenges, including climate change as well as water, agriculture and biodiversity issues. Lucas Joppa, Microsoft's first Chief Environmental Scientist, is convinced that AI is now mature enough and the global environmental crisis acute enough to justify the creation of an AI platform for the planet.

Artificial Intelligence (AI), defined as the capability of machines to imitate intelligent human behavior and learn from data, is considered by many to be the final frontier of computing. And environmentalists and tech companies are now harnessing the power of AI to service to the environment. To wit, Microsoft announced in December 2017 that it is expanding its "AI for Earth" program and committing $50 million over the next five years to put AI technologies in the hands of individuals and organizations working to solve global environmental challenges, including climate change as well as water, agriculture and biodiversity issues. Lucas Joppa, Microsoft's first Chief Environmental Scientist, is convinced that AI is now mature enough and the global environmental crisis acute enough to justify the creation of an AI platform for the planet. "I believe that for every environmental problem, governments, non-profits, academia and the technology industry need to ask two questions: 'How can AI help solve this?' and'How can we facilitate the application of AI?'," Joppa said.

Dear EarthTalk: What are some ways Artificial Intelligence (AI) is being used to fight climate change and otherwise protect the environment? Artificial Intelligence (AI), defined as the capability of machines to imitate intelligent human behavior and learn from data, is considered by many to be the final frontier of computing. And environmentalists and tech companies are now harnessing the power of AI to service to the environment. To wit, Microsoft announced in December 2017 that it is expanding its "AI for Earth" program and committing $50 million over the next five years to put AI technologies in the hands of individuals and organizations working to solve global environmental challenges, including climate change as well as water, agriculture and biodiversity issues. Lucas Joppa, Microsoft's first Chief Environmental Scientist, is convinced that AI is now mature enough and the global environmental crisis acute enough to justify the creation of an AI platform for the planet.

Published Sunday, Jun. 24, 2018, 12:48 pm Dear EarthTalk: What are some ways artificial intelligence is being used to fight climate change and otherwise protect the environment? Artificial intelligence (AI), defined as the capability of machines to imitate intelligent human behavior and learn from data, is considered by many to be the final frontier of computing. And environmentalists and tech companies are now harnessing the power of AI to service to the environment. To wit, Microsoft announced in December 2017 that it is expanding its "AI for Earth" program and committing $50 million over the next five years to put AI technologies in the hands of individuals and organizations working to solve global environmental challenges, including climate change as well as water, agriculture and biodiversity issues. Lucas Joppa, Microsoft's first Chief Environmental Scientist, is convinced that AI is now mature enough and the global environmental crisis acute enough to justify the creation of an AI platform for the planet.

We call this a human/computer learning network, whose core is an active learning feedback loop between humans and machines that dramatically improves the quality of both and thereby continually improves the effectiveness of the network as a whole. In this article we explore how human/computer learning networks can leverage the contributions of human observers and process their contributed data with artificial intelligence algorithms leading to a computational power that far exceeds the sum of the individual parts. For example, projects such as Galaxy Zoo, eBird, and FoldIt demonstrate the power of engaging the public in the investigation of a variety of large-scale scientific problems. These and similar projects leverage emerging techniques that integrate the speed and scalability of mechanical computation, using advances in artificial intelligence (AI), with the real intelligence of human computation to solve computational problems that are beyond the scope of existing algorithms (Law and von Ahn 2011). Human computational systems use the innate abilities of humans to solve certain problems that computers cannot solve (Man-Ching, Ling-Jyh, and King 2009).

The idea seems wonderful - a phone app that allows you to take a photo of a plant or animal and receive immediate species identification and other information about it. A "Shazam for nature" so to speak. We are building huge repositories of data related to our natural environments, making this idea a reality. But there are ethical concerns that should be addressed: about how data is collected and shared, who has the right to share it and how we use public data for machine learning. And there's a bigger concern – whether such apps change what it means to be human.

The sea and ocean environment has long been explored using some of the most sophisticated technology tools. Today's technologies make it child's play to explore natural environments under the sea. The American Goddard Space Flight Center, which belongs to NASA, relies on machine learning to track microscopic algal growth in oceans. The microalgae, which float on the water's surface, are largely responsible for producing oxygen, an element essential for supporting life. Many underwater observations rely on advanced detection technologies.