When a new coronavirus emerged from nature in 2019, it changed the world. But COVID-19 won’t be the last disease to leapfrog the shrinking wilderness. Only this weekend it was announced that Australiais no longer a spectator like Canada, USA and European countries clamber to contain monkeypox, a less dangerous relative of the dreaded smallpox virus that we were able to eradicate at great cost.
While we push nature to the margins, we make the world less safe for both humans and animals. That’s because environmental destruction forces animals that have viruses closer to us, or us to them. And when an infectious disease like COVID does skipcould easily pose a global threat to health, given our deeply interconnected world, the ease of travel and our dense and… growing cities†
We can no longer ignore the fact that man is part of the environment, not separated from it. Our health is inextricably linked to the health of animals and the environment† This will not be the last pandemic.
To be better prepared for the next spread of animal viruses, we need to focus on the links between human, environmental and animal health. This is known as the One health approachendorsed by the World Health Organization and many others.
We believe that artificial intelligence can: help us better understand this web of connection and teach us how to keep life in balance.
How can AI help us fend off new pandemics?
Fully 60% of everything infectious diseases in humans are zoonoses, meaning they come from animals. That includes the deadly Ebola virusthat came from primates, swine fluof pigs, and the new coronavirus, most likely of bats† It is also possible for humans to feed animals our diseases, with recent research pointing to transmission of COVID-19 from people to cats like deer†
Early warning of new zoonoses is vital if we are to tackle viral spillover before it becomes a pandemic. Pandemics such as swine flu (influenza H1N1) and COVID-19 have shown us the enormous potential of AI-based prediction and disease surveillance. In the case of monkey pox, the virus has: already circulating in African countries, but has now made the leap internationally.
What does this look like? Think about collecting and analyzing real-time data on infection rates. In fact, AI was used to first flag the new coronavirus as it became a pandemic, with work done by AI company bluedot and health card at Boston Children’s Hospital.
How? By tracking massive streams of data in ways humans just can’t. For example, Healthmap uses natural language processing and machine learning to analyze data from government reports, social media, news sites and other online sources to track the global spread of outbreaks.
We can also use AI to my social media data to understand where and when the next COVID peak will occur. Other researchers are using AI to research the genome sequences of viruses that infect animals to predict whether they could potentially jump from their animal hosts into humans.
Better preservation through AI
There are clear links between our destruction of the environment and the rise of new infectious diseases and zoonotic spillovers† This means that protecting and preserving nature is also good for our health. By keeping ecosystems healthy and intact, we can prevent future disease outbreaks.
AI can also help with nature conservation. For example, game book uses computer vision algorithms to detect individual animals in images and track them over time. This allows researchers to make better estimates of population sizes.
Polluting the environment through deforestation or illegal mining can also be spotted by AI, such as through the Trends.Earth project, which monitors satellite images and Earth observation data for signs of undesired change.
AI for both the natural world and humans
Researchers are starting to think about the ethics of AI research on animals† If AI is used carelessly, we could see worse results for domestic and wild animal species, for example, animal tracking data can prone to errors if not double checked by people on the ground, or even hacked by poachers†
AI is ethically blind† Unless we take steps to embed values in this software, we may end up with a machine that replicates existing biases. For example, if there are existing inequalities in people’s access to water resources, they can easily be recreated in AI tools that perpetuate this unfairness. That is why organizations like the AINow Institute focus on bias and environmental justice in AI.
In 2019, the EU released ethical guidelines for reliable AI. The goal was to ensure that AI tools are transparent and prioritize human power and environmental health.
AI tools have real potential to help us tackle the next pandemic by keeping an eye on viruses and helping us keep nature intact. But for this to happen, we will have to broaden AI outwards, away from the people orientation of most AI tools, to embrace the fullness of the environment we live in and share with other species.
We must do this while anchoring our AI tools in principles of transparency, fairness and protection of rights for all.
Ann BordaAssociate Professor, Melbourne Medical School, The University of Melbourne† Andrea MolnarColleague Professor, Swinburne University of Technology† Cristina Neeshamassociate professor of business ethics and corporate social responsibility, University of Newcastleand Prof Patty KostkovaProfessor in Digital Health, Director of UCL Center of Digital Public Health in Emergencies (dPHE), UCL