AI could help us stop viruses like monkeypox from 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 rip through shrinking nature.

Just this weekend it was announced that Australia is no longer a spectator, as Canada, the United States and European countries struggle to contain monkeypox, a less dangerous relative of the dreaded smallpox virus that we were able to eradicate at great expense.

By pushing nature to the periphery, we make the world less safe for humans and animals.

This is because environmental destruction brings virus-carrying animals closer to us, or closer to them. And when an infectious disease like COVID does jump throughit can easily pose a threat to global health given our deeply interconnected world, ease of travel, and our density and growing cities.

We can no longer ignore that humans are part of the environment, not separate 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-derived 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 network of connection and teach us to maintain the balance of life.

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

How can AI help us ward off new pandemics?

Fully 60 percent of all infectious diseases affecting humans are zoonoses, that is, they originate in animals. This includes death Ebola virusfrom primates, swine flupigs, and the new coronavirus, most likely bats.

It is also possible that humans transmit our diseases to animals, with recent research suggesting the transmission of COVID-19 from humans to cats as good as stag.

Early warning of new zoonoses is essential if we are to be able to control viral spread before it becomes a pandemic.

Pandemics such as the swine flu (H1N1 flu) and COVID-19 have shown us the huge potential of AI-based disease prediction and monitoring. In the case of monkeypox, the virus has has already circulated in African countries, but has now made the leap internationally.

What does it look like? Remember to collect and analyze real time data on infection rates. In fact, AI has been used to first flag the new coronavirus as it became a pandemic, with the work carried out by the AI ​​company blue dot and HealthMap at Boston Children’s Hospital.

How? By tracking vast streams of data in ways that humans simply cannot. Healthmap, for example, 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 epidemics.

We can also use AI to harness social media data to understand where and when the next COVID surge will occur. Other researchers use AI examine the genomic sequences of viruses infecting animals in order to predict whether they could potentially jump from their animal hosts to humans.

As climate change alters Earth systems, it is also change the ways spread of diseases and their distributions. Here too, AI can be used in new monitoring methods.

hand biting a mosquito
Climate change changes where diseases occur. Photo: Getty

Better conservation thanks to AI

There are clear links between our destruction of the environment and the emergence of new infectious diseases and zoonotic fallout.

This means that protecting and conserving nature also contributes to our health. By keeping ecosystems healthy and intact, we can prevent future epidemics.

In conservation too, AI can help. For instance, wild book uses computer vision algorithms to detect individual animals in images and track them over time. This allows researchers to produce better estimates of population sizes.

Environmental destruction through deforestation or illegal mining can also be spotted by AI, for example through the Trends.Earth project, which monitors satellite images and Earth observation data for signs of unwanted change.

Citizen Scientists can also step in by helping train machine learning algorithms to better identify endangered plants and animals on platforms such as zoouniverse.

AI for the natural world and for humans

Researchers are starting to think about the ethics of AI animal research.

If AI is used carelessly, we might actually see worse results for domestic and wild animal species, for example, animal tracking data can be error prone if it is not double-checked by humans in the field, or even hacked by poachers.

AI is ethically blind. Unless we take steps to integrate values in this software, we could end up with a machine that reproduces the existing biases. For example, if there are inequalities in human access to water resources, these could easily be recreated in AI tools that maintain this injustice. This is why organizations like the AINow Institute focus on bias and environmental justice in AI.

In 2019, the EU published ethical guidelines for trustworthy AI. The goal was to ensure that AI tools are transparent and prioritize human action and environmental health.

AI tools have real potential to help us face the next pandemic by keeping an eye out for viruses and helping us keep nature intact.

But for that to happen, we’ll have to expand AI outward, away from the human centered of most AI tools, to embrace the fullness of the environment we live in and share with other species.

We must do this while embedding our AI tools with the principles of transparency, fairness and protecting rights for all.The conversation

Anne BordaAssociate Professor, Melbourne Medical School, The University of Melbourne; Andreea MolnarAssociate Professor, Swinburne University of Technology; Cristina NeshamAssociate Professor of Business Ethics and Corporate Social Responsibility, Newcastle Universityand Prof. Patty KostkovaProfessor of Digital Health, Director of the UCL Center for Digital Public Health in Emergencies (dPHE), UCL

This article is republished from The conversation under Creative Commons license. Read it original article.


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