AI can help us stop viruses like monkeypox crossing nature

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.

It was announced this weekend that Australia is no longer a spectator as Canada, the US, and European countries try to contain monkeypox, a less dangerous relative of the dreaded smallpox virus that we could eradicate at great cost.

While we push nature to the margins, we make the world unsafe for humans and animals.

That’s because environmental destruction forces animals that have viruses closer to us or us to them. And when a contagious disease like COVID strikes, it can easily pose a global health threat, given our highly interconnected world, the ease of travel, and dense and growing cities.

We can no longer ignore that man is part of the environment, not separated from it. Our health is inextricably linked to animal and environmental health. This will not be the last pandemic.

To be better prepared for the next spread of animal viruses, we must focus on human, environmental, and animal health links. This is known as the One Health approach, endorsed by the World Health Organization and many others.

AI can help us stop viruses like monkeypox crossing nature

We believe that artificial intelligence can help us better understand this web of connection and teach us how to keep life in balance.

We have pushed nature to the brink in many parts of the world. Photo: Shutterstock

How can AI help us fend off new pandemics?

More than 60 percent of all infectious diseases that affect humans are zoonoses, meaning they come from animals. That includes the deadly Ebola virus from primates, swine flu from pigs, and the novel coronavirus, most likely from bats.

It is also possible for humans to give animals our diseases, with recent research pointing to the transmission of COVID-19 from humans to cats and deer.

Early warning of new zoonoses is vital 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 monkeypox, the virus is already circulating in African countries but has now made the leap internationally.

What does this look like? For example, collecting and analyzing real-time data on infection rates. AI was even used to first flag the novel coronavirus as it became a pandemic, with work done by AI firm Bluedot and HealthMap at Boston Children’s Hospital.

How? By tracking massive streams of data in ways, humans just can’t. For example, HealthTap 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 mine social media data to understand where and when the next COVID peak will happen. Other researchers are using AI to examine the genomic sequences of viruses that infect animals to predict whether they could potentially jump from their animal hosts into humans.

As climate change changes the Earth’s systems, it also changes the way diseases spread and how they spread. Here too, AI can be used in new surveillance methods.

Climate change changes where diseases occur. Photo: Getty

Better preservation through AI

There are clear links between our environmental destruction and the emergence 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, Wildbook 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 monitors satellite imagery and Earth observation data for signs of unwanted change.

Citizen scientists can also get involved by helping train machine learning algorithms to get better at identifying endangered plants and animals on platforms like Zooniverse.

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 even worse results for domestic and wild species; for example, animal tracking data can be prone to errors if not double-checked by humans on the ground or even hacked by poachers.

AI is ethically blind. Unless we take steps to embed values ​​into this software, we could end up with a machine replicating existing biases. For example, inequalities in people’s access to water resources can easily be recreated in AI tools that perpetuate this unfairness. That’s why organizations like the AINowInstitute focus on bias and environmental justice in AI.

In 2019, the EU released ethical guidelines for trustworthy 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 need to broaden AI outwards, away from the human-centricity of most AI tools, toward embracing the fullness of our environment and sharing with other species.

We must do this while anchoring our AI tools in principles of transparency, fairness, and protection of rights for all.

Ann Borda, Associate Professor, Melbourne Medical School, University of Melbourne; Andreea Molnar, Associate Professor, Swinburne University of Technology; Cristina Neesham, Associate Professor of Business Ethics and Corporate Social Responsibility, Newcastle University, and Prof. Patty Kostkova, Professor of Digital Health, Director of UCL Center of Digital Public Health in Emergencies (dPHE), UCL

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