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Beyond Calculation: AI and Sustainability

Soils are the most complex microbial ecosystem we know. A single teaspoon of healthy soil may contain thousands of species, a billion individuals, and one hundred metres of fungal networks. The soils in forest ecosystems, especially, are a foundational part of the global carbon cycle. But to most of us in the modern urban world, they’ve been invisible and uncared for.

Julian Liber studies the rhizosphere – the soil around the root of plant where microbial activity is especially high. Helped by AI, he tracks fungal hyphae – their rate of growth, how often they branch, and other metrics.

The number and vitality of worms is another good indicator of soil health. Thanks to machine learning, observations from diverse sources can now be used to make diagnostic maps.

Fish farming is investing heavily in sensors and AI tools. Some of these systems can even even monitor what they eat.

Another agricultural process, composting, transforms organic waste to nutrient-rich manure. But composting infrastructures tend to be installed away from residential areas. This makes tending to the compost heap a tedious task.

Thanks to compost monitors, Internet of Things, and AI, composting has now become a more viable as an urban activity.

The scale and scope of biodiversity sampling is being expanded dramatically by small, low-power computing devices, advances in wireless communications, and data-recognition algorithms in the field of machine learning. AudioMoth, for example, is being used to understand the world of bats in real time.

These efforts are vital in efforts to prevent another Covid. Researchers at the Chinese Academy of Sciences are using AI-supported bioacoustics to plot the distribution of bat species.Their aim is anticipate any danger of ‘spillover’ – from wild into urban – as a result of habitat disturbance by human activity.

But let me return to the core issue of PURPOSE of AI and the new development paradigm mentioned earlier.

The restoration of ecosystems damaged by decades of extraction is surely central to that over-arching purpose. AI, here, can play a important role in identifying restoration options that diversify the local economy, and create jobs. For example, the use of fiber crops to remediate degraded land and provide future livelihoods.

In Australia, where numerous mine sites are being rehabilitated back to their native ecosystems, eDNA metabarcoding helps ecologists determine what insects, pollinators, and bacteria used to live there, and so what should be planted there, next.

Add all these experiments together, and the tools and connectivity are within our grasp, today, to monitor every patch the vital signs of of the planet in real time.

We could repurpose the giant screen used by Alibaba to monitor sales during Black Friday. We could feed in data – from satellites in space, to microbial communities surveyed by eDNA.

We’d get a wondrous insight into the health of planet – place by place, patch by patch.

But there’s a dilemma here. A new dashboard is not the same as a new system.

On the contrary. For most if the world’s economic and political actors – the ones that will spend $100 trillion of climate finance announced by Mark Carney – the climate crisis is not a system failure – it’s a problem of management, efficiency, and control.

All those promises to plant billions of trees? A Yale study found that 45% of these trees, planted “efficiently”, will be monocultural plantations – managed as cash crops and devoid of biodiversity.

That’s the problem with the dashboard idea. It frames the living world as some kind of machine to process “natural resources” and “ecosystem services”.

Returning to Mark Carney again: that tsunami of climate finance could actually increase ecological destruction.

Demand for carbon offsets, net-zero, and nature positive credits, is escalating. And in order to meet this demand on a large scale, investors demand standardised metrics in order to simplify and speed up verification.

But biodiversity is the literal opposite of standardised.

The best indicator of biodiversity health is diversity, continuous adaptation, and change. The health of an ecosystem lies in the vitality of interactions between its component species.

The study of living systems tells a consistent story. Whether it’s sub-microscopic viruses, mosses, and mycorrhizae – or trees, rivers and climate systems – science has confirmed an ancient wisdom: All natural phenomena are not only connected. Their very essence is to be in relationship with other things -including us.

The health of the soil, microbes, soil, plants – and the health of people – are a single story. Diversity and adaptation are the best indicators of vitality.

No matter how massive the datasets and simulations created by AI, computational models cannot comprehend the complexity and interdependence of ecosystems. They will remain just that: models of reality.

The bank Credit Suisse, with remarkable candour, has put it best: ”biodiversity is the anti-commodity”.

This is bad news for an industrial economy that that treats raw materials as commodities.

In an industrial system, efficiency and control are success factors. The system demands uniformity and standardisation. Diversity, of the kind found in healthy nature, makes the game impossible.

And this is why climate finance could make things worse.

Every social and ecological context is unique – but finance needs the living world to behave like a machine – like the tree plantations I mentioned earlier.

The inherent complexity of nature is confirmed by real-world restoration projects – especially in the world’s critical zones. To monitor their vitality, scientists have established critical zones observatories throughout the world including this one in China.

Yes, they use sensors and highly technical instruments to collect data in these outdoor laboratories. But making sense of this complex data involves multiple skills.

AI can help with interpretation, but the story on the ground remains complex.

As well as the diverse scientific disciplines, ecological restoration can often involve dozens of organisations. This social and organisational dimension further intensifies the complexity.

And as my colleague Professor Lou Yongqi has explained, social systems are just one among four that we have to contend with: Nature, Human, Artificial, and Cyber.

As well as involving multiple systems, real-world ecological restoration also involves multiple timescales.The timescales of restoring land, measured in decades, are way beyond the ultra-fast tempo of financial markets that can be measured in milliseconds.

If finance needs nature to be machine-like – but nature is not a machine – how best are we to respond?

I believe designers are well-placed to help us cope with this tangled dilemma .

Learning from the last 50 years, it’s surely clear that we don’t need more messages, concepts, instructions. What we need, and what we yearn for, is connection – connection with each other; connection with place; and above all, connection with the living.

Designers can use their creative skills to represent social and natural systems immersively. In so-called ‘system in the room’ intallations, we humans can experience being part of nature, not outside.

The word, experience, I believe, is key. AI, as I’ve shown, can provide extraordinary data and insights – but something more is needed to awaken the experience of interconnectedness.

Design-plus-AI can be a medium of attention – such as with ecosystems we have neglected; a medium of connection – so we don’t just look; a medium of relationship with the living world that can persist through time

Beyond Calculation

The destruction will stop when we stop thinking of the oceans, fields and forests as ‘resources’ or ‘solutions’ – and start thinking (and acting) in them as lifeworlds.

Making that shift is the basis of a new way to measure and create value, and therefore purpose. That’s why we need to experience the health of a place, and of the persons who inhabit it, as a single story.

Such a change of course requires ecological literacy, and a whole-systems understanding of the world. AI, art, design, I believe, can help us acquire these skills and understanding.


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