In Spring 2020, Dr Emily Shuckburgh OBE delivered our first virtual Turing Lecture on sustainability and the climate crisis on the 50th anniversary of Earth Day, Wednesday 22 April.
Dr Emily Shuckburgh is Director of Cambridge Zero at the University of Cambridge and Reader in Environmental Data Science at the Department of Computer Science and Technology. She is a mathematician and climate scientist and a Fellow of Darwin College, a Fellow of the Cambridge Institute for Sustainability Leadership, an Associate Fellow of the Centre for Science and Policy and a Fellow of the British Antarctic Survey. In 2016 she was awarded an OBE for services to science and the public communication of science. She is co-author with HRH The Prince of Wales and Tony Juniper of the Ladybird Book on Climate Change.
How will Covid-19 impact the environment? What lessons from this unprecedented pause in activity can we apply to the current climate crisis?
Emily Shuckburgh: Perhaps the most obvious immediate impact is that the lockdowns in place now in so many parts of the world are resulting in substantially improved levels of air quality as polluting activities are curtailed. That said, worrying levels of air pollution still exist in many places, with for instance London repeatedly reaching elevated levels over the past few weeks. This is all the more concerning as there are plausible suggestions that this can raise the risk of mortality from Covid-19.
In the longer term, a crucial question is whether we can shape a national and global recovery from the coronavirus pandemic in a way that supports the response to climate change and other environmental threats. Can we embed some of the positive aspects of the behavioural changes that we have been forced to adopt, such as greater use of virtual communication platforms? Can we re-boot the global economy by stimulating the growth in clean technologies? Can we use this opportunity to rethink our relationship to the natural world? As ever, good can be extracted from even the darkest hour, but it requires clear thinking, imagination and leadership.
How can the data science and AI community best contribute to tackling climate change?
First and foremost, you can only manage what you can measure. This means that data and the information it provides is absolutely central to tackling climate change.
That includes data on how the climate itself is changing from global temperature increases to sea level rise and changes to extreme weather around the world and on the wide-ranging impacts of climate change on people and nature. Today we have an unprecedented quantity of data regarding every aspect of our environment from satellites and vast networks of sensors on the ground. Data science and AI can help integrate these different data sources to better characterise the threat of climate change and enable informed decision-making.
"First and foremost, you can only manage what you can measure."
It also includes data on emissions of greenhouse gases from human activities (be that the burning of fossil fuels, carbon-intensive industrial processes or agricultural practices), or at an individual level the energy consumption in our homes or the carbon-footprint of the food we eat. In this case AI can also provide opportunities for developing climate-friendly practices from more efficient use of energy in buildings to smarter farming methods.
What advancements in data science and AI have had major impacts on the field of environmental science? What advancements do you see coming to fruition (e.g. in the next five years) and what will these enable us to do?
In many ways data science and modelling informed by data has always been a key part of environmental science. Over the past few years, however, there has started to be an explosion in the use of AI, and in particular machine learning methods, applied to environmental problems. These methods have been used to help monitor the environment, for example by extracting information on plant and animal species from satellite data to help with conservation efforts, and used to help predict environmental change by introducing data-driven algorithms to computer simulations, augmenting or replacing traditional approaches.
Environmental datasets, from both observations and computer simulations, are becoming increasingly complex as a result of technological and scientific advances. At the same time there is a growing demand from policymakers and others for trustworthy and accessible environmental information. Application of AI to environmental datasets offers enormous opportunities for economic and societal benefit on a global scale, from informing strategies to build resilience to climate change to mitigating the impact of natural disasters on our ability to feed, house and support ourselves. A new generation of researchers trained to apply and develop AI to tackle the challenges of environmental risks is now emerging and there is great potential for their work to be transformational.
Cover photo credit: Pete Bucktrout, British Antarctic Survey