When a new coronavirus emerged from nature in 2019, it changed the world. But COVID-19 won’t be the last disease to jump from the shrinking wild. This weekend, it was announced that Australia is no longer a spectator, as Canada, the US and European countries scramble to stop monkeypox, a less dangerous relative of smallpox that we were able to eradicate at great cost. .
As we push nature over the edge, we make the world less safe for both humans and animals. This is because environmental destruction forces the animals to carry the virus to us or us close to them. And when an infectious disease like COVID spreads, it can easily pose a threat to global health, given our deeply connected world, ease of travel, and our dense and growing cities.
We can no longer ignore the fact that man is 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 better prepare for the next spread of the virus from animals, we must pay attention to the relationship between humans, the environment, and animal health. This is known as the One Health approach supported by the World Health Organization and many others.
We believe that Artificial Intelligence can help us better understand this web of connections, and teach us how to keep life in balance.
How can AI help us overcome new epidemics?
About 60% of all infectious diseases affecting humans are zoonoses, which means they came from animals. This includes the deadly Ebola virus, which came from primates, swine flu, from pigs, and the novel coronavirus, most commonly from bats. It is also possible for humans to pass our diseases to animals, with recent research suggesting transmission of COVID-19 from humans to cats and deer.
Early warning of new zoonoses is important if we are able to tackle viral spillover before it becomes a pandemic. Pandemics like Swine Flu (Influenza H1N1) and COVID-19 have shown us immense potential for AI-enabled prediction and disease surveillance. In the case of monkeypox, the virus is already running in African countries but has now made the leap to the international level.
What does this look like? Think about collecting and analyzing real-time data on infection rates. In fact, AI was previously used to flag the novel coronavirus as becoming a pandemic, with work done by AI company BlueDot and HealthMap at Boston Children’s Hospital.
How? By tracking vast flows 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 outbreaks.
We can also use AI to mine social media data to understand where and when the next COVID surge will occur. Other researchers are using AI to examine the genomic sequences of viruses infecting animals to predict whether they could potentially jump from their animal hosts to humans.
As climate change changes Earth’s systems, it is also changing the ways diseases spread and their distribution. Here too, AI can be harnessed in new ways of surveillance.
AI. better protection through
There are clear links between our destruction of the environment and the emergence of new infectious diseases and zoonotic spillovers. That is, protecting and conserving nature also helps in our health. By keeping the ecosystem healthy and intact, we can prevent future outbreaks of diseases.
AI can also help in 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.
The destruction of the environment by deforestation or illegal mining can also be seen by AI, such as Trends. The Earth Project, which monitors satellite imagery and Earth observation data for signs of unwanted change.
Citizen scientists can also pitch in to help train machine learning algorithms to get better at identifying endangered plants and animals on platforms like Zooniverse.
AI for the natural world as well as for humans
Researchers are beginning to consider the ethics of AI research on animals. If AI is used recklessly, we could actually see worse outcomes for species of domestic and wild animals, for example, if not double-checked by humans on the ground, or even Animal tracking data can be prone to errors if it is not hacked by poachers.
AI is morally 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 human access to water resources, these can easily be recreated in AI tools that will perpetuate this unfairness. That’s why organizations like AINowInstitute are focusing on bias and environmental justice in AI.
In 2019, the EU issued ethical guidelines for trusted AI. The goal was to ensure that AI tools were transparent and prioritize human agency and environmental health.
AI tools have real potential to help us tackle the next pandemic by helping us keep track of viruses and keep nature afloat. But for that to happen, we need to broaden AI outward, away from the human-centricity of most AI tools, into the environment we live in and share with other species.
We must do so while embedding our AI tools with principles of transparency, equality and protection of the rights of all.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
National center to advance Australia’s AI goals