Alex Rahin, chief product and technology officer at Cervest, discusses how the response to the Covid-19 pandemic might help us deal with the climate crisis more effectively using AI.
Though it may not be apparent on the surface, the Covid-19 crisis bears many similarities with the climate crisis. Both situations represent international challenges that transcend borders and affect people indiscriminately.
Above all, they both require human action in order to reduce the threat they pose, whether that be through social distancing or forecasting climate risks both holistically or specifically for organisations.
The risks posed by Covid-19 and our volatile climate will only be curbed by organisations and governments embracing a sustained shift in priorities, as well as further implementing technology – such as artificial intelligence (AI) – to build future climate security.
So what lessons have we learnt from the Covid-19 pandemic so far, and how can we apply them to the climate crisis?
Widespread social disruption
The first lesson we have learned is just how quickly widespread social disruption can occur. While there are similarities, there are also critical differences between Covid-19 and climate volatility.
Covid-19 is a short-term challenge. The implications are severe but within 18 months we may develop a vaccine and social distancing measures are expected to limit the spread.
Yet, within this time, we have seen how drastically social norms have been disrupted. The very same is true of the extreme weather events caused by the climate crisis. For instance, just this year, Australia was affected by widespread fires that caused extreme damage to the ecosystem and economy.
The second lesson is just how quickly measures can be taken to protect the public.
Though there was a range of responses to the pandemic globally, they were largely rapid and reflected the urgency of the situation across the globe. In just a few months, society had been radically restructured in order to protect people from the threat of the virus.
Though climate volatility cannot be solved in such a short time span, this recent pandemic is evidence that rapid and widespread change is possible when the risks are well understood.
As we have seen with Covid-19, a unified response is needed across all social levels to address the climate crisis. Every organisation has a role to play – from farmers and producers to insurers and retailers. Every organisation has been, or will be, impacted by the changing climate.
So how can we take these learnings and arm them for the fight against climate volatility? What measures can we put in place to ensure the wider understanding of the potential implications of climate volatility?
Insights gained through AI
Through Covid-19, we have seen AI can be pivotal in improving our understanding of the virus.
These insights have helped inform the responses of governments and organisations. For instance, we have seen AI trained to help diagnose Covid-19 via chest CT scans, to help in drug development for treatments, and even in predicting the status of patients.
These are a handful of the uses we are seeing for AI during the pandemic. Like a novel virus, climatic events move in complex, interlocking structures that can be difficult to predict.
Only through understanding the immediate risks of a situation can we begin to address them and align responses between different people and groups. The same is true of the climate crisis.
There is a staggering amount of data held about the planet’s climate and due to the innumerable variables and potential outcomes, the risks posed by climate are near impossible to visualise without the aid of AI.
AI can make this data digestible and informative for non-governmental organisations. As climate security continues to impose itself on the agenda of both nations and businesses, it is imperative that stakeholders understand the risks that threaten their organisation and value chain. The Covid-19 pandemic has proven the need and possibility for rapid action to mitigate against issues with businesses’ value assets.
Understanding the issue
Whether it is a flood, drought or forest fire, extreme climatic and weather events are increasing in their severity and frequency globally. The damage they cause affects individuals and businesses, and forces families to leave their homes.
While this is a macro problem, it needs action – both macro and micro – to mitigate against potential repercussions.
Governments and businesses have established broad, long-term climate goals such as cutting emissions, which have little impact today. What is needed is a way of understanding the need for action in the short term and what can be done on an individual level. And this is where AI comes in.
Just as it has been used in the present Covid-19 pandemic, AI can help understand the effects of the climate crisis. How can supply routes be altered to account for increased hurricanes in Europe? What can be done about declining fish stocks as the Gulf Stream slows? What do locusts spreading across east Africa mean for food supplies?
These are the kinds of questions that organisations need to inform their actions but simply cannot be realised by human intelligence alone.
Mapping out the future
AI is able to analyse enormous international climate data pools. Through the latest developments in Earth science, data engineering and machine learning, AI is more empowered than ever to yield these insights.
Information can be collected from an array of global sources, scientists, satellites and sensors to be converted into personalised, accurate and dynamic maps that provide essential information to individual organisations.
Only through this careful dissemination of information can organisations develop plans of action that address their climate security.
It has been reassuring to see the capabilities of organisations in responding to Covid-19. In tracking, mapping and modelling the spread of the virus they have been able to take rapid action and limit the effects of a potentially devastating pandemic.
The view of climate change is equally necessary to ensure that similar, widespread measures can be implemented. Though the same results cannot be achieved in such a short time frame, now is a better time than any to begin moving in the right direction.
By Alex Rahin
Alex Rahin is the chief product and technology officer at predictive AI start-up Cervest.