Originele artikel van Dr Lucas Joppa is gepubliceerd op theguardian.com op 30 januari 2017.
In many respects, 2016 was the year of artificial intelligence (AI). Innovations such as big data, advances in machine learning and computing power, and algorithms capable of hearing and seeing with beyond-human accuracy have brought the benefits of AI to bear on our daily lives. By working together with machines, people can now accomplish more by doing less.
Yet the power of AI can address far bigger challenges than helping organise our calendars, order our groceries or play games. In collaboration with AI, people can help to solve some of the world’s most urgent and difficult problems. One of the most fundamental of these is how to stem the ongoing catastrophic loss of biodiversity.
We know that species are becoming extinct at a rapid pace – at least 1,000 times more quickly than would be expected in the absence of human activities. These extinctions have devastating impacts on the ecosystem services on which humans rely. Species loss wreaks havoc on pollination services, which puts our global agriculture system at risk. Clean water depends on healthy forests and wetlands, themselves the result of a complex web of species.
What we don’t know is even more worrying. Scientists have discovered and described only 1.5m species of the estimated 10m on earth. And some estimates range much higher than that, up to 50m or more. As a result, the number of species included on the IUCN Red List – the world’s repository of information on the conservation status of species – includes 1% or less of all species on Earth.
We are not on pace to close this gap very quickly. At current rates, we will have to wait almost 500 years to collect all of the estimated species on Earth – and by then, most of them may be extinct.
There are two resource factors that are currently impeding the pace of progress. The first is money. Speeding up the species discovery timeline to a more reasonable 50-year pace is estimated to be on the order of $1bn (£1.2bn) annually. The second is time. It takes a great deal of time and effort to collect, sort and analyse the data we have and even more time to collect new datasets on yet to be discovered species in the world.
AI and associated technologies have the ability to close this information gap cost-effectively and efficiently. Hardware is increasingly cheap and power-efficient enough to deploy monitoring systems on the ground, on animals, in the sky, and up in space. Early work is proving that algorithms can sift through the massive amounts of data streaming back from these monitoring systems. In turn, humans and machines can begin to identify the plants, birds, fish, and other species captured by these remotely deployed cameras, microphones, and more – sometimes down to the unique individual. And we’re finding new ways to deploy these technologies every day. For example, Microsoft is working on ways to use organisms such as mosquitos as small, self-powered data collection devices that can help us better understand an ecosystem through the animals they feed on.
Artificial intelligence can help us understand land use patterns as well. Microsoft and others are experimenting with ways to turn high-resolution imagery into land cover maps. These maps provide an unprecedented view of what is where, and how it is changing. This in turn helps governments, organisations and researchers make more informed decisions about when, where and how to most effectively deploy conservation efforts for the greatest impact. And it creates a virtuous cycle of learning, as all of this information can then be fed back into AI systems, making them smarter.
It is now clear that AI methods make it is possible to build a digital dashboard for the planet, allowing us to monitor, model, and manage environmental systems at a scale never before possible. This effort should begin now – time is too short and resources too thin to achieve environmental goals without the transformative impacts of AI. We need more information, more frequently, and at greater resolution than what is currently available. For example, the UN recently announced a plan to publish a global assessment of Earth’s biodiversity and ecosystem services in 2019, nearly 15 years after the last global assessment.
How, then, do we make this vision a reality? To date we’ve only scratched the surface of what collaboration between people and machines can accomplish for the conservation of biodiversity. To realise the full scope of what is possible will take a coordinated effort from all of us, including industry, government, and the academic and nonprofit sectors. It won’t be an easy journey, but by applying the power of AI to help both humans and our natural systems thrive, we can help provide a better and healthier future for the planet.
HU Media Analysis 2017/2018 
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