COMMENT SCIENCE FICTION Six giants of the POLLUTION A call for Pakistan TECHNOLOGY AI developers need LAB LIFE Here’s to coffee- genre reflect on their role in a and India to craft air-quality a checklist for human-rights room chat, catalyst of world unhinged p.329 policy together p.334 violations p.334 collaborations p.334 COURTESY OF MICROSOFT COURTESY Microsoft, in collaboration with others, is using algorithms to convert satellite images into information about categories of land cover, such as forests. AI for Earth Create an artificial-intelligence platform for the planet, urges Lucas N. Joppa. arlier this year, I became Microsoft’s business. And the time is right: applications at least once a month. Nearly one-fifth do first chief environment scientist. I’ve of the type that I and others have long been so daily (see go.nature.com/2bwmejp). been tasked with deploying the com- developing can now work at scale. That is Those data are fed to increasingly power- Epany’s deep investments in artificial intelli- why, in 2017, Microsoft put US$50 mil- ful algorithms that link people to others, gence (AI) research and technology to help lion into a 5-year programme called AI products or information. Yet we are flying people around the world monitor, model and for Earth (see ‘Microsoft for Earth’ and blind when it comes to understanding the ultimately manage Earth’s natural systems. www.microsoft.com/aiforearth). natural world. Most people I meet are surprised that one Scientists still struggle to predict the of the world’s leading technology companies FLYING BLIND effects of climate change at the resolution has a role such as mine. Yet I believe that in Today, we know more than ever about of cities or regions, or over timeframes of the next few years, every major tech firm will human activity. More than one-quarter of months or weeks — largely because they be working on applying AI to sustainability. the 7.6 billion people on Earth post detailed don’t have the kinds of data needed to It is the ethical thing to do. It is good for information about their lives on Facebook make such predictions, or because they ©2017 Mac millan Publishers Li mited, part of Spri nger Natu21/28re. All ri gDECEMBERhts reserved. 2017 | VOL 552 | NATURE | 325 COMMENT lack the algorithms to convert data into understand, and at appropriate spatial and together with where and how often it’s useful information. In the United States, the temporal resolution. With enough data photographed, these algorithms are provid- best available data sets on land cover, at a on which to train, and with human feed- ing new ways of producing global popula- resolution of 30 metres, were last updated back, these systems can learn to tag photos, tion estimates for endangered species4. nearly 7 years ago. Globally, the picture is acoustic recordings and genetic informa- Environmental applications of AI are much less complete. Yet without accurate tion with species names; or to convert sat- already attracting the attention of invest- information, housing developers, foresters ellite imagery into information on water ment firms, particularly in the agriculture or other land planners can’t make evidence- availability at a landscape scale. sector. Using data from high-resolution based decisions about which parcels of land Various organizations are already making satellites orbiting Earth, the tech company to use for which purposes, and how much impressive advances in Earth applications. Descartes Labs in Santa Fe, New Mexico, to leave untouched. iNaturalist and eBird, for instance, are iden- is monitoring crop production globally. Meanwhile, almost 95% of oceans — tifying species using communities of citizen Through the application of neural-network which cover more than two-thirds of Earth’s scientists. So far, iNaturalist’s 575,000 mem- algorithms to more than three petabytes of surface — remain unexplored. And scien- bers have recorded nearly 7 million obser- satellite and weather data (1 petabyte is tists have described only around 1.5 mil- vations of more than 128,000 species (see 1015 bytes), users can obtain information lion of the estimated 10 million species on ‘Assisted identification’). about projected yields that outperform all Earth, and know little more than the names iNaturalist relies on experts to validate other available forecasts in resolution and and collection locations for most of those1. users’ recordings, but deep convolutional accuracy. Likewise, Blue River Technology, AI systems could help in all of these neural networks are reducing the amount a California start-up, is using AI algorithms domains. In fact, after seven years of work- of expert input required — one of the big- combined with high-resolution cameras ing at the intersection of environmental and gest bottlenecks in attached to tractors and other field equip- computer science, I’m convinced that the the organization’s “The global ment to produce automatic weed-detection technology is now mature enough and the growth. Currently, environmental and weed-removal systems. In my view, global environmental crisis acute enough for more than crisis is acute the recent acquisition of Blue River by the to justify the creation of an AI platform for 5,000 species of enough to justify US agricultural company John Deere for the planet. plant and animal, the creation of $300 million represents just the beginning What I’m envisioning is a portfolio of its algorithms are an AI platform of the agricultural industry’s AI transfor- AI-infused ‘Earth applications’ available to able to make an for the planet.” mation. people in diverse domains, from forestry to accurate identifi- Others are using AI to inform land-use fisheries. These would be analogous to the cation four out of management decisions — such as how application programming interfaces (APIs), every five times, on average. And when the to establish wildlife corridors for species such as those for searching or mapping, that algorithms’ top five predictions are consid- such as lynxes and wolverines across the have enabled people to build software ser- ered for each sighting, the correct species is US Rocky Mountains as effectively and vices using components already made by included 95% of the time3. efficiently as possible. This is a difficult engineers at technology companies. The same types of deep-learning algo- computational problem because there rithm now used by iNaturalist’s vast com- are so many possible solutions. But AI EARTH APPLICATIONS munity of users are also helping ecologists advances from operations research, devel- AI and environmental-science researchers to classify millions of underwater snapshots oped for instance to work out how best to are now applying algorithms to topics as of corals. Other non-profit organizations, route traffic along a network of roads with varied as pollution modelling, agricultural- such as WildBook, are scouring the pho- the least cost and delay, are offering guid- yield optimization, animal-migration tographs of a particular species posted ance5. Likewise, game-theory researchers tracking and Earth-system modelling. on social-media platforms such as Flickr. are using AI to help law-enforcement offic- (Many of them will come together next By identifying each individual animal, ers to efficiently monitor the vast protected month in Austin, Texas, at the 17th Annual areas they are typically assigned to cover6. Conference on Artificial and Computa- (AI algorithms identify what monitoring tional Intelligence and its Applications to ASSISTED IDENTIFICATION strategy will maximize the probability of the Environmental Sciences.) Experts validate species identications made patrols detecting illegal activity in a way by users of the iNaturalist app, which Numerous advances in these areas are launched when the organization was founded that minimizes the probability of criminals coming from AI breakthroughs in non- in 2008. Articial intelligence is reducing the working out what that strategy is.) environmental ones. For instance, the amount of expert input required. But these inspirational examples need to SOURCE: INATURALIST increasing demand for low-cost cam- 8 be the norm, not the exception. Too often, era systems for smartphones and other researchers publish exciting results about devices has necessitated cheaper algorith- the application of AI to an environmental mic (instead of hardware) approaches to problem and those results are never trans- 6 improving image resolution. These ‘super Algorithms are now lated into applications. Or an AI system helping members resolution’ AI techniques can be used to to identify more is handed to a non-profit organization or improve Earth-system models by statisti- than 5,000 species government agency that lacks the resources 4 with an average of cally ‘downscaling’ low-resolution projec- 81% accuracy. and expertise to take advantage of it. Worse, tions of around 100 square kilometres to traditional AI innovators in industry and high-resolution ones of around 12 square academia rarely consider working on km that are more relevant to local land-use 2 environmental applications. planners2. Numbers of observations (million) Numbers of observations In short, AI systems can now be trained TWO QUESTIONS to classify raw data from sensors on the 0 I believe that for every environmental prob- ground, in the sky or in space, using cat- 2010 2015 lem, governments, non-profits, academia egories that both humans and computers and the technology industry need to ask two 326 | NATURE | VOL 552 | 21/28 DECEMBER©2017 Mac m il2017lan Publishers Li mited, part of Spri nger Nature. All ri ghts reserved. ©2017 Mac millan Publishers Li mited, part of Spri nger Nature. All ri ghts reserved. COMMENT Computer scientists generally publish their work in conference proceedings. (Conference organizers use a peer-review process similar to that used by editors at traditional academic journals.) Awarding prizes at leading conferences for the best solution, rather than for the best paper, could motivate students and faculty mem- bers to invest more efforts in engineering.