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I’ve long believed the most profound technology innovations are ones we take for granted on a day-to-day basis until "suddenly" they are part of our daily existence, such as computer-aided navigation or camera-endowed smartphones, says Heather Clancy, GreenBiz editorial director.
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| Photo: GreenBiz |
Perhaps that’s why I’m so fascinated by the intersection of artificial intelligence and sustainability: the applications being made possible by breakthroughs in machine learning, image recognition, analytics and sensors are profoundly practical. In many instances, the combination of these technologies completely could transform familiar systems and approaches used by the environmental and sustainability communities, making them far smarter with far less human intervention.
Take the camera trap, a pretty common technique used to study wildlife habits and biodiversity — and one that has been supported by an array of big-name tech companies. Except what researcher has the time or bandwidth to analyze thousands, let alone millions, of images? Enter systems such as Wildlife Insights, a collaboration between Google Earth and seven organizations, led by Conservation International...
Where will AI-enabled applications really make a difference for environmental and corporate sustainability? Here are five areas where I believe AI will have an especially dramatic impact over the next decade.
- Automating energy management. Considering that the system of record for tracking sustainability data today is a technology that first showed up on personal computers 40 years ago (here’s looking at you, VisiCalc), we could use a reboot. Two of my favorite early examples of how AI is helping with energy management come from Google, which is using it to improve efficiency and the renewables mix in its data centers; and cold storage company Lineage Logistics, which entrusts AI with the power schedules for its warehouses.
- Improving soil conditions and crop yields. Drones and sensors that monitor fields are seen as a key component of helping the agricultural sector make better decisions about hydration and plant nutrition, and in fighting disease. One recent example is a crop emergence solution tested by John Deere-backed AI startup Taranis, along with drone spraying firm Rantizo, soil health company Continuum Ag and additives company Phytobiotics. The intelligence behind the system comes from Taranis, which uses AI to monitor and analyze aerial imagery. Watch for AI to help scale agtech solutions.
- Modeling future climate risks. A great example of what’s possible is AT&T’s collaboration with Argonne National Laboratory. It’s mashing up its proprietary database of information about the AT&T telecommunications network with Argonne climate models to predict how impacts of climate change — such as sea-level rise, high-intensity winds and coastal and inland flooding — might affect operations 30 years into the future. Anticipate the big financial services and insurance firms to invest substantially in extending analytics capabilities using AI.
- Protecting biodiversity. The Wildlife Insights project is just one example of how scientists are using imagery combined with insanely powerful data-analysis technologies to get a better picture of how the planet is changing. Google is at the center of many projects, but so is Microsoft, with its well-funded AI for Earth project. One initiative it funded on Christmas Eve is Wildbook, a collaboration between Oregon nonprofit Wild Me and researchers from Princeton, Rensselaer Polytechnic and the University of Chicago.
- Verifying provenance across supply chains. The headline for many next-generation traceability systems being piloted across different industries — from cotton to coffee to seafood — is the blockchain, which is really a fancy name for electronic ledger technology. The reality is that a whole lot of machine learning is behind the most sophisticated of these applications, and that means AI will be integral for scale.
Source: GreenBiz
