What If Our Cities Were Designed for Both People and Nature?

Aug 20, 2026

Aerial shot of Fortaleza’s urban landscape blending with sprawling forested areas. by Nino Souza via Pexels

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What if our cities were designed for wildlife as well as people?

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By Saman Sobhani, Aberystwyth University

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Common swift flying at sunset — shutterstock.
Paul Sawer/Shutterstock

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On a warm evening in May, swifts scream over rooftops, chasing insects above the traffic. A fox slips along a garden wall while gulls squabble on a supermarket roof. We tend to treat these animals as visitors. But they’re residents too, living alongside us in places designed for people.

My recent research argues this needs to change. Instead of asking how nature can make cities better for humans, urban planners should consider what cities owe the many species that already live in them.

More than half the world’s population now lives in urban areas, while cities continue to expand into wildlife habitats.

In the UK, swifts provide a distinct example. They nest in gaps under eaves and roof tiles, which can disappear when older buildings are demolished, re-roofed or insulated. UK swift numbers have fallen by around 60% since 1995. In 2021, the species was added to a list of birds at greatest risk of extinction.

The issue isn’t simply how we can make cities greener. It’s who we think cities are for.

For my new study, I compared approaches to incorporating nature into urban planning, including environmental offsetting, sustainable development and nature-based solutions such as green roofs, street trees and wetlands. I also examined cases where governments and courts have given species and ecosystems a different status in decision-making.

The pattern I found was striking. These approaches have become increasingly good at showing how nature benefits people, but much less willing to ask whether other species have interests of their own.

Trees are planted because they cool streets. Wetlands are protected because they can hold floodwater. Parks are funded because they improve our health.

All of those benefits are important. But they can also leave nature looking like a service provider for people. If a tree no longer provides enough shade, or a wetland becomes more valuable as development land, what happens to the argument for protecting it?

This is where the idea of “multispecies justice” comes in. It starts from a different premise, where animals, plants and ecosystems are not simply amenities that provide benefits to people. They are co-inhabitants of places we share.

That changes the question urban planning asks. Instead of only considering what nature can do for us, it asks what responsibilities we have towards the species with which we live.

What would change?

This doesn’t mean turning cities into wildlife reserves. It can involve small changes to decisions that shape urban life.

For example, before restoring a river, planners could consider whether the proposed changes are likely to create conditions in which fish and frogs can thrive. They could then assess the project not only on its effects on flooding or visitor numbers.

A development could be designed around established wildlife routes rather than treating them as obstacles to mitigate later. Environmental assessments could consider what a new road does to the routes used by badgers, bats or other animals, alongside its effects on drainage and emissions. Some places might be left undisturbed during breeding seasons.

There are already examples of governments experimenting with this type of approach. In New Zealand, the Whanganui River was recognised as a legal person in 2017, with guardians appointed to represent its interests. Colombia’s Atrato River was recognised as a subject of rights in 2016, with a similar system of guardianship.

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A view of the Whanganui River looking lush and green. — The Whanganui River in New Zealand.
Robert Harding Video/Shutterstock

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These cases aren’t straightforward solutions. The rights granted to rivers still have to operate within existing political and legal systems. Research suggests implementation in Colombia has been uneven.

But they illustrate a different way of thinking. Nature doesn’t have to justify its existence solely through the benefits it provides to people.

The idea is also beginning to appear in more conventional urban planning. Barcelona has built green corridors linking parks to the hills beyond the city so that wildlife can move through it.

In the UK, Scotland has become the first nation by law to require swift bricks in new buildings. These hollow bricks contain a nesting cavity and cost roughly £30 each. But its significance is larger than the brick itself. It treats the presence of another species as something that should be considered when we design buildings, rather than as an unexpected problem to deal with afterwards.

In England, efforts to require swift bricks by law were rejected by the House of Lords. The UK government has instead pursued their inclusion through planning policy and development requirements.

A different way of designing cities

None of this makes urban planning simple. Species can have competing needs, and protecting wildlife can sometimes conflict with other environmental or social goals.

A protected predator might threaten a vulnerable population. Preserving a habitat might complicate a development intended to reduce overheating. There won’t always be a simple answer.

But those conflicts already exist. The difference is that they’re often resolved using systems that give human interests the greatest weight. Multi-species justice asks us to make those choices more explicit.

Cities are already shared habitats. The birds nesting in our roofs, the insects in our gardens, the bats above our streets and the organisms in our soils are not simply passing through. They are part of urban life.

The challenge for planners is to decide whether they’ll continue to design cities primarily around human needs, adding nature where it provides a benefit, or begin to treat the flourishing of other species as a legitimate consideration in its own right.

Saman Sobhani, PhD Candidate in Environmental Economics, Aberystwyth University

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This article is republished from The Conversation under a Creative Commons license. Read the original article.

Bedouin Craft in Contemporary Infrastructure Influence

Aug 19, 2026

Across the Gulf, Bedouin heritage often enters architecture first as an image. Airport terminals recall tent silhouettes, visitor centres incorporate woven screens, and pavilions reinterpret traditional textiles as decorative façades. These references have become a familiar visual language for expressing regional identity. They also risk reducing one of the world’s most sophisticated vernacular building traditions to an architectural motif. Long before the Bedouin tent became a cultural symbol, it was an environmental technology: a lightweight, adaptable structure capable of creating comfort in one of the planet’s most demanding climates. What contemporary infrastructure may inherit is not the tent’s silhouette, but the construction intelligence woven into it.

The Bedouin black tent, traditionally woven from goat hair by women practising Al Sadu weaving, demonstrates a remarkably precise understanding of climate and material. The material works with desert conditions instead of resisting them. Goat-hair fibres swell when exposed to moisture, tightening the weave to resist rain, and loosen as they dry, allowing air to circulate during intense heat. Individual textile strips are woven separately before being stitched into larger membranes, enabling damaged sections to be repaired or replaced without dismantling the entire structure.

Supported by poles and tensioned ropes instead of rigid walls, the tent remains lightweight, portable, and adaptable to changing patterns of movement. Filtered shade, moving air, and permeability create comfort without complete enclosure. Recognised by UNESCO as an important element of intangible cultural heritage, Al Sadu represents far more than a craft tradition; it contains a sophisticated understanding of environmental performance achieved through material knowledge rather than mechanical technology.

For decades, these ideas were discussed mainly as vernacular architecture. The Hajj Terminal changed that. Completed in 1981, the Hajj Terminal at King Abdulaziz International Airport in Jeddah transformed the environmental logic of the Bedouin tent into one of the twentieth century’s most ambitious pieces of transport infrastructure. Beyond borrowing the tent merely as a cultural image, architects at SOM explicitly described the project as a reinterpretation of the Bedouin tent, translating its lightweight construction into a vast cable-supported tensile membrane system. The result was not simply a dramatic roof, but an entirely different approach to accommodating people in an extreme climate.

The terminal’s celebrated PTFE-coated fabric canopy stretches across hundreds of modular roof bays, creating expansive shaded spaces that remain naturally ventilated while accommodating the extraordinary seasonal demands of the annual Hajj pilgrimage. Unlike conventional airport terminals designed around permanently enclosed, mechanically conditioned halls, the Hajj Terminal accepts that comfort in the desert can emerge through shade, airflow, and openness. Millions of pilgrims occupy these spaces during peak periods before the infrastructure returns to a quieter operational rhythm for the rest of the year. In many ways, its spatial intelligence mirrors that of the Bedouin encampment itself: modular rather than monolithic, flexible rather than fixed, and organised around temporary but highly efficient occupation. The project proved that environmental knowledge developed at the scale of a family dwelling could also organise national infrastructure.

Subsequent generations of Gulf infrastructure reveal an interesting shift. Explicit references to Bedouin architecture have become less common. The environmental strategies, however, continue to reappear. Foster + Partners’ Red Sea International Airport, for example, draws inspiration primarily from the surrounding desert landscape rather than Bedouin settlements. Its modular terminal clusters, lightweight roof structures, and carefully shaded circulation spaces are presented as responses to climate, energy efficiency, and future expansion rather than cultural symbolism. The result is unexpectedly familiar: lightweight structures, generous shade, modular growth and buildings that remain adaptable over time. The resemblance is less about influence than about arriving at similar solutions under similar climatic pressures. Faced with the same desert climate, architects repeatedly arrive at principles already embedded within Bedouin construction.

A comparable evolution can be observed in projects beyond transport infrastructure. Grimshaw’s Terra Sustainability Pavilion at Expo 2020 Dubai demonstrates how large roof canopies can function as environmental infrastructure rather than purely formal expression. The pavilion’s expansive shading system filters intense solar radiation while creating usable public space beneath it, reducing dependence on enclosed conditioned environments. Likewise, visitor facilities across AlUla and landscape projects such as the Wadi Hanifah Visitor Centre increasingly prioritise passive cooling, landscape integration, and filtered environmental conditions over iconic architectural form. These projects rarely resemble tents. What they borrow is the way tents work.

This distinction may appear subtle, but it fundamentally changes how architectural heritage is understood. Too often, discussions of regional identity focus on preserving appearances while overlooking the knowledge systems that generated them. Bedouin construction was never remarkable because tents looked distinctive. They were remarkable because they solved complex environmental problems using locally available materials, reversible construction, and extraordinary material efficiency. The lesson lies in understanding why weaving produced comfort, flexibility, and repair rather than copying its patterns.

As architecture confronts increasingly extreme climates, growing resource constraints, and more dynamic patterns of occupation, these lessons become newly relevant. Airports designed for fluctuating passenger volumes, temporary cultural events, disaster relief infrastructure, and rapidly expanding desert settlements all require buildings capable of adapting without excessive material consumption or mechanical dependence. Its principles of lightweight assembly, modular repair, passive environmental control, and climatic responsiveness align closely with many of the ambitions now driving sustainable architecture worldwide.

The Hajj Terminal continues to resonate more than four decades after its completion, for its enduring significance lies in demonstrating that indigenous knowledge can operate confidently within contemporary engineering. It showed that tradition need not survive only through preservation; it can evolve through translation. Desert infrastructure will not become more regionally grounded by repeating the image of the Bedouin tent. It will do so by understanding the environmental intelligence woven into its construction.

This article is part of the ArchDaily Topic: The Architecture of Craft: Handmade Stories in a Digital Age.

How to Assess and Address System-Level Physical Risks Wisely

Aug 18, 2026

By MARSH 08/18/2026

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Excavator working on land clearing near forest edge

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Climate risk does not stop at the boundary of a building or facility. An organization’s resilience is inseparable from the health of the surrounding communities, ecosystems, infrastructure, and supply chains. Yet for many businesses, climate-related risks are still assessed too narrowly, often only at the level of individual assets. A more connected approach enables clients to better identify, assess, manage, and transfer system-level physical risks. The steps below can help clients begin to take that broader view.

What are system-level risks?

System-level risks are threats to the suppliers, customers, infrastructure, resources, ecosystem services, governments, regulators, capital providers, and communities that organizations depend on but do not fully control (see Figure 1).

Whereas asset-level risk is predominantly related to potential property damage and business interruption, systems-level risk is driven primarily by the threat of business interruption, with property damage as a secondary concern.

For example, a company may harden an asset against flooding or heat. However, if during an extreme weather event, transport links fail, the power supply is disrupted, workers cannot reach the site, or critical suppliers are impacted, the business is still exposed.

System-level risks are particularly important to consider in the built environment, where organizations depend on complex networks of infrastructure, labor, energy, water, logistics, public services, and local communities. In towns and cities, a heatwave, flood, or wildfire rarely remains purely a local physical hazard.

However, until now, these risks have often been underestimated. Traditional risk assessments tend to focus on physical assets because they are easier to model and more familiar to business leaders. By contrast, system-level dependencies are more diffuse. They cut across functions and stakeholders rather than sitting within a single team or budget. That makes them harder to own, harder to quantify, and easier to overlook.

01 | The Marsh Risk Climate Adaptation Framework: organizations should consider both asset- and system-level considerations

Practical steps to address system-level risk

Addressing these risks requires a broad approach. To build true resilience, organizations need to look beyond their own boundaries and actively engage with regulators, suppliers, peer organizations, and critical infrastructure providers.

As put forward in Marsh’s report, Addressing the system-level resilience gap, organizations can achieve this by taking a four-step approach: identify system dependencies, assess materiality, manage risk more effectively, and transfer residual risk where possible. This is an iterative process that should be embedded into location strategy, procurement, capital allocation, and enterprise risk management to support more resilient decision-making across the business.

Marsh has also developed practical checklists, available in the report appendix, aligned to each system-level climate risk that organizations operating in urban and industrial areas can use. Designed to be actionable, they provide a useful tool for risk managers and other risk owners across the organization.

Additionally, tools such as Marsh’s Insurance Enabler Framework can be used to identify where resilience measures can improve risk outcomes and where pricing pressure may point to deeper vulnerabilities.

Helping clients turn complex climate risk into informed action

In our work, we regularly encounter barriers such as climate risk being communicated in technical or scientific language that does not always resonate with senior decision-makers.

Another challenge is organizational fragmentation. In many businesses, climate resilience sits in silos — perhaps within sustainability, operations, risk, or business continuity — rather than being embedded across governance, capital allocation, procurement, and strategy. As a result, organizations may understand that system-level climate risks present a threat, but they do not always have a consistent way to translate that awareness into coordinated action.

At the same time, the benefits of resilience are often long term, indirect, or difficult to express in financial terms, while the costs are immediate and visible. As a result, system-level risk can appear less urgent than it truly is. Marsh’s framework and checklists provide clients with a practical way to turn this challenge into an effective response.

Is universities’ AI embrace compromising climate targets?

Aug 17, 2026

Low-angle view of a green plant-covered building in Warsaw, Poland. by Vladislav Murashko via Pexels

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Is universities’ AI embrace undermining their net-zero targets?

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Amid all the debates about student employability and academic integrity, the question of how AI mandates square with universities’ commitments to addressing climate change has been largely neglected. Juliette Rowsell reports

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Published on Times Higher Education – August 17, 2026

By Juliette Rowsell

A woman touching a giant robot hand that looks like it is coming from the centre of a storm. To illustrate whether universities embracing AI is undermining their net-zero targets.

Source: Getty Images montage

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For at least a decade, universities around the world have been declaring their determination to get to net-zero emissions. Then, in 2019, a slew of universities around the world went a stage further, declaring climate “emergencies” that often came with accelerated targets to eliminate net institutional carbon emissions.

Announcing Cardiff University’s climate emergency in 2019, for instance, its then vice-chancellor Colin Riordan said the university had already fully divested from fossil fuels and must “lead by example and accelerate our plans to reduce our carbon emissions, energy and water use and overhaul our operational activities”.

And in 2021, Universities UK’s Confronting the climate emergency report committed all UK universities to setting targets for reducing the carbon footprint of sources they control directly (known as source 1 emissions) and of the energy they use (known as source 2). It also promised that institutions would “set a target” for reducing scope 3 emissions, caused by the production of products and services they use – or, failing that, “commit to a programme of work to set targets as soon as possible”. They would publish these targets on their websites and “set out how progress against these targets will be reported in a transparent, consistent, and understandable way”.

But then, late the following year, ChatGPT was unleashed, and institutional attention turned towards the adoption of AI. There were concerns about it, of course, but they were centred around its corrosive effect on academic integrity. And notwithstanding those concerns, many universities have committed to making AI tools available to all staff and students and embedding technology into the curriculum – on the grounds that the technology is here to stay and students need to be fluent in its use.

In 2025, for instance, California State University rolled out ChatGPT Edu – OpenAI’s customised education version of its large language model tailored to higher education institutions – to more than 460,000 students and more than 63,000 staff, making it the biggest educational roll-out of ChatGPT in the world. And later that year, the University of Oxford became the first UK institution to roll out ChatGPT Edu to students, while earlier this year the University of Manchester announced a “world-first” partnership with Microsoft to provide access to its AI tool, 365 Copilot, for all staff and students.

A student climate protester overlaid on to the interior of a data centre. To illustrate a conflict of mass AI roll-outs with net-zero targets.

Source: Getty Images montage

Yet amid all the debates about employability, pedagogy and the integrity of student assessment, the potential conflict of mass AI roll-outs with net-zero targets has been rather overlooked.

A June report by UK IT body Jisc and the Environmental Association for Universities and Colleges (EAUC) warned that pressure for universities to adopt AI has “outpaced clarity about what responsible action looks like in practice”.

The report cites statistics from the International Energy Agency, which show that global data centres’ energy consumption could more than double by 2030 – or even, according to Greenpeace Germany, increase elevenfold. And data centres already account for 6 per cent of all electricity consumption in the US and the UK, according to an industry body – and a much higher proportion in some other countries.

“As institutions with public commitments to net zero, tackling climate change, and broader environmental sustainability goals…it is imperative that we recognise how the adoption of these technologies is contributing to both our individual and collective environmental footprint across multiple dimensions,” the Jisc/EAUC report read.

Water consumption is also a major concern, as large amounts of water are needed to cool data centres. Research published in the journal NPG Clean Water in 2021 found that even a relatively small 1 MW data centre can consume about 25 million litres of water per year, while the UK water company Affinity Water told UK MPs in May that one recent proposal for a data centre had estimated that its daily water need would be equivalent to that of 147,000 people.

And Jonatan Pinkse, research director at the Centre for Sustainable Business at King’s College London, noted that Google’s recently released sustainability report revealed an 18 per cent year-on-year increase in carbon emissions as it expands its AI operations, and an 81 per cent increase in emissions from 2019, despite having a 2030 net-zero target.

“The negative [of AI use] has become so clear so fast that there’s no going around it any more,” he said.

Michael Draper, professor in legal education at the University of Swansea and director of the university’s academic regulations and student cases board, said: “If you actually design your assessment so that AI [must be] used by the student, and some students are saying, ‘Well, we shouldn’t be doing this because of the impact on the environment, and some of the ethical concerns’, there are real concerns around that, and that conversation isn’t really had…It’s all around academic integrity. The point I raise…is that institutions often have a commitment to UN sustainability goals. Well, where does that commitment fit with the widescale adoption of artificial intelligence when it’s using all this energy and water?”

Students on laptops overlaid on an image of a forest fire. To illustrate that people use AI without realising that there’s an environmental footprint associated with it.

One reason that such conversations rarely occur is that the environmental impact of AI is not universally known. Cal Innes, a digital sustainability specialist at Jisc and co-author of the Jisc/EAUC report, told Times Higher Education that “a lot of people are going into [AI usage] as they do with a lot of aspects of digital behaviours: not realising that there’s an environmental footprint associated with it”.

But even university managers who are aware of the problem and determined to address it face an uphill struggle since AI companies rarely disclose information regarding individual institutions’ AI use, the Jisc/EAUC report says, making it almost impossible for universities to produce reliable estimates of the environmental cost of their AI use.

THE asked several universities that have announced major AI roll-outs about how they are tracking their emissions data in relation to AI use. However, out of California State, Oxford, Manchester, Arizona State, the Massachusetts Institute of Technology and the universities of Cambridge and Surrey, only Surrey, Manchester and MIT provided responses.

A spokesperson for Surrey, which recently announced that AI is being incorporated into curricula for all subjects, explained that it had “robust monitoring processes” in place as part of its sustainability agenda, and added it is “applying those same standards to how we procure AI tools for our framework”. It estimates its indirect emissions and reports them in both its annual sustainability report and its institutional annual report.

“Scope 3 emissions are harder to pin down than direct emissions, as they depend on suppliers reporting their own carbon data back to us,” the spokesperson conceded. However, “we’ve recently updated our procurement policy to require this, and we’re now starting to collect that data, including from external AI vendors”.

A spokesperson for Manchester, meanwhile, argued that it is important that staff and students have “equitable” access to AI tools, and for them to be equipped with “necessary skills for the workplace”, including learning to use AI “responsibly”. The university is working “closely” with Microsoft to ensure transparency around AI’s environmental impacts, the spokesperson said, adding it has initiated “groundbreaking research in partnership with Microsoft to model the impacts of our Copilot usage and to inform the actions the university will take to manage and minimise these impacts. We are exploring how best to understand and monitor these impacts as the university-wide roll-out progresses.”

Alex de Vries-Gao, founder of Digiconomist, which examines the impact of technology trends on the environment, is concerned by AI’s typical absence from universities’ sustainability statements: he would expect organisations to reference it even if merely to acknowledge “how difficult it may be to obtain the right information”.

“If you’re not capable of getting the numbers, at least talk about it and show that you’re thinking about this because if you’re not discussing it, you’re probably not thinking about it,” he said.

A spokesperson from OpenAI said the company gives considerable thought to the best use of its computing power and said it supports its partners to meet their sustainability and water-consumption goals. And they pointed out that the Jisc/EAUC report did not take into account modern closed-loop water cooling systems, which are more efficient than traditional cooling towers that allow water to evaporate away, adding that it is currently developing data centres in Norway that run entirely on renewable energy.

OpenAI believes AI will be instrumental in tackling climate change by optimising energy systems and accelerating research, the spokesperson added, noting that the company is partnering with leading universities to accelerate these efforts, such as Oxford and the US National Laboratories.

Microsoft declined to comment but its 2026 Environmental Sustainability Report said that in the 2025 financial year it had “replenished more water than we withdrew” and “achieved our milestone to match 100% of our annual electricity consumption with renewable energy”. It added that the company is “scaling clean, reliable energy to meet growing demand from cloud and AI, exploring sources from nuclear to fusion, and investing in the grid infrastructure and technologies needed to get there”.

The construction of a 374-acre data centre in rural Virginia, with people planting trees overlaid. To illustrate that AI companies are making efforts to be sustainable and minimising water consumption.

Source: Getty Images montage

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Universities are also exploring how AI can help them reduce their own scope 1 emissions. While MIT was unable to provide details on its generative AI (GenAI) use and how it is tracking such data, it outlined that it is currently expanding a pilot launched in 2023 that uses machine learning to optimise its energy systems and increase efficiency in heating and cooling its buildings. It said the programme had reduced the pilot building’s energy use by up to 40 per cent annually and was now being expanded to additional buildings and updated so MIT systems can automatically respond to live data.

But Charlotte Bonner, chief executive of EAUC and co-author of the report with Jisc, noted that traditional machine learning is distinct from GenAI tools. And De Vries-Gao, who is also completing a PhD at the Vrije Universiteit Amsterdam Institute for Environmental Studies, said machine learning tools do not have as significant an impact as GenAI and are more likely to have been developed in-house, which provides institutions with greater transparency over their energy use.

That lack of transparency about AI’s environmental cost is the “ultimate problem”, he said, adding that institutions are also “not capable of really dissecting what is the benefit of each individual application [of AI] either. So you’re missing both sides of the equation.”

Examples of such applications are also few and far between. Bonner and Innes had wanted to include more positive examples of universities using AI to address the environmental impact, but “once we really started to look into the research available, we found that where claims were being made about how AI use was helping drive positive environmental change, it was nearly always as a result of traditional machine learning rather than GenAI,” Bonner said. “We can’t really find at this moment in time any substantiated evidence that generative AI is helping drive positive environmental change.”

And even though universities’ AI use may lead to research breakthroughs that ameliorate climate change, King’s’ Pinkse said this is far from guaranteed.

“We hope that it will of course lead to fantastic breakthroughs,” he said. “But you can never really promise it because…the whole point of research and development [is] that we don’t always know what the outcome is going to be.”

Student on a smartphone in class, with parched earth overlaid. To illustrate that people use AI without realising that there’s an environmental footprint associated with it.

Source: Getty Images montage

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So what are universities to do? None of the experts that THE spoke to said that abandoning AI was the way forward. Pinkse’s view is that universities are in an “almost impossible” dilemma given the ubiquity of AI.

“If a university were to say, ‘We’re becoming a non-AI university’, students would start saying, ‘We’re not too sure about this one’,” Pinkse said. “That puts them in a very vulnerable position because they are competing with other universities and other organisations. There are [also] demands that we deliver students who are AI literate and so forth. So I don’t think it’s that easy to say, ‘We should not be doing this’…It’s unfair as a demand on universities.”

Meelis Kitsing, rector of the Estonia Business School, thinks he has found the right balance by seeking to produce graduates who are not only AI-literate but also able to engage with wider ethical debates regarding technology. To that end, the school has embedded questions on AI throughout its curriculum and strategy, embracing the tech while also remaining critical of it.

The institution is also hosting its seventh “digitalisation and sustainability” summer course bringing together students, academics and policymakers to examine how AI is reshaping business models while simultaneously intensifying energy demands.

“We need to encourage people to be critical thinkers, rather than ideologues who believe that AI will solve all problems – or the opposite: that AI will only create problems for sustainability,” Kitsing said. “I think that truth is more likely to be characterised by different shades of grey, rather than be black and white.”

Ultimately, the “guilt” for AI use’s environmental impact should not fall on academics and students, Innes believes. He referred to a concept known as “greenshifting”, whereby the responsibility for environmental harm is projected by companies on to consumers, which he said “diverts away from institutional responsibility, where we have the greatest leverage”.

But do universities really have any meaningful leverage over BigTech firms?

Bonner suspects that they have more power than they think to demand greater transparency on AI’s water consumption and energy use, provided they act collectively – and, ideally, with other sectors, such as health systems. And she can “foresee a future” in which universities develop shared “sector-specific large language models” and data centres – in a similar way that numerous institutions have access to Isambard-AI, the University of Bristol-based supercomputer purpose-built for AI research.

That, as she and others pointed out, would allow them to better track the technology’s usage and energy consumption. “But I don’t think that we’ll ever get to a situation where we don’t use some of [the AI developed by] the household names,” she conceded.

Universities could also restrict academics and students to “acceptable” uses of AI, Innes suggested, noting that creating just eight seconds of video with AI can produce up to 2,000 times more carbon than a single text prompt. But he was wary of singling out AI firms when other forms of digital technology also have significant environmental impacts. While it is important to hold them to account, “we’re not routinely questioning the footprint of watching YouTube videos, doomscrolling social media, or leaving webcams on in online conferences”, he noted.

It is abundantly clear that AI is only going to become ever more closely integrated into university teaching, research and administration. Jisc itself, for instance, is currently running a trial of AI marking tools. But in the midst of another unprecedently hot summer across Europe and North America, the phrase “climate emergency” has never seemed more apt – and it would seem odd for institutions pledged to combating it to simply dismiss AI’s huge carbon footprint as a problem too difficult and poorly documented for them to engage with.

For her part, Bonner conceded that institutions can often feel “overwhelmed” when it comes to tackling the sustainability consequences of AI. But she urged them not to wait until they have “perfect data” on it before acting.

“We don’t want there to be a paralysis of action because the data quality isn’t there,” she said. Because if universities take that approach, “we’re never going to do anything”.

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Technological Sovereignty and Digital Justice in 2026

Aug 16, 2026

Futuristic robotic hand touching a digital network on a blue background. by Tara Winstead via pexels

An 18th SDG? Technological sovereignty and digital justice

Fulufhelo Nemavhola – University World News 13 August 2026

Professor Fulufhelo Nemavhola, Image: Durban University of Technology

When the Sustainable Development Goals (SDGs) were adopted in 2015, they gave the world one of the most ambitious frameworks for shared development in modern history. The 17 goals created a common language for poverty, hunger, health, education, gender equality, water, energy, work, infrastructure, inequality, climate action, peace and partnerships.

But the world of 2026 is not the world of 2015.

Artificial intelligence now shapes education, research, public administration, labour markets, health systems and democratic debate. Cloud infrastructure has become as strategically important as physical infrastructure. Data has become a source of economic power. Digital platforms increasingly mediate how societies learn, trade, communicate, govern and form political opinion. Cybersecurity is now a daily concern for universities, hospitals, municipalities and states.

The SDGs remain important. But as the world begins to think beyond 2030, it must confront a difficult question: can any country achieve sustainable development if it lacks the capacity to understand, govern, produce, and benefit from the technologies that increasingly determine its future?

This is why the world needs a serious conversation about the 18th SDG: technological sovereignty and digital justice – in particular in Africa and the Global South.

Technology is a field of power

This is not a call to multiply global slogans. It is a call to recognise that technology has become the operating system of development itself. Education, health, agriculture, energy, climate adaptation, industrialisation, public finance and governance are now mediated by digital systems, artificial intelligence, data infrastructure and advanced technologies. A development framework that treats technology only as an enabler, rather than as a field of power, dependency and justice, is incomplete.

Several proposals for an 18th SDG have already emerged. Some have argued for universal communication. Others have proposed responsible and inclusive artificial intelligence, digital technology, animal welfare, space sustainability, or ethnic-racial equality as possible missing goals.

These proposals are important because they reveal a wider truth: the 2015 SDG framework is now under pressure from realities that have intensified since its adoption. My argument is that the most comprehensive missing goal is technological sovereignty and digital justice, particularly for the Global South.

Technology in the list of 17

Technology is not absent from the existing SDGs. SDG 9 already speaks to industry, innovation and infrastructure. Other goals also refer to science, innovation, data, energy systems, education technologies and partnerships. But technological sovereignty, artificial intelligence governance, data justice, cybersecurity resilience and domestic innovation capability are not treated as development goals in their own right. That is the gap.

For Africa and the Global South, this issue is urgent. Many universities teach through foreign platforms, store research data in external cloud systems, rely on imported laboratory equipment, use artificial intelligence tools designed elsewhere, and depend on digital architectures over which they have limited control.

Many governments procure digital systems without building domestic capability. Many countries generate vast quantities of data without having sufficient sovereign infrastructure, technical expertise or regulatory capacity to govern that data in the long-term public interest.

This creates a new development divide. It is no longer only a divide between those with and without access to technology. It is a divide between those who design technology and those who merely consume it; between those who own data infrastructure and those who supply data; between those who govern artificial intelligence and those who are governed by it.

An 18th SDG should, therefore, be framed as follows: ensure equitable technological sovereignty, responsible artificial intelligence, data justice and inclusive innovation capacity for all nations.

Technological sovereignty

Such a goal would not promote technological isolation. Sovereignty does not mean autarky or withdrawal from global cooperation. It means the ability to participate in global systems with dignity, capability and bargaining power. It means that developing countries should not be permanent consumers of technologies designed elsewhere, but co-creators of the technological future.

Higher education must be central to this agenda. Universities cannot remain observers of technological dependence. They must become engines of technological capability. This means producing, not only graduates and publications, but also prototypes, patents, start-ups, open technologies, local platforms, community innovations, industrial partnerships and public-interest research.

Universities of technology play a particularly important role. Their mandate is applied knowledge, problem-solving, industry engagement and social innovation. They are well placed to translate technological sovereignty into practical development outcomes, including medical devices, clean energy systems, water technologies, agricultural tools, digital public infrastructure, cybersecurity capacity, smart manufacturing, and inclusive entrepreneurship.

But this requires a shift in how governments, funding agencies and universities define impact. Research systems often reward publications more easily than prototypes. They measure journal outputs more consistently than technology transfer.

They celebrate international collaboration but do not always ask whether it builds local capability. They encourage innovation rhetoric but underfund the laboratories, workshops, testing platforms, and commercialisation pathways required to move ideas into products.

An 18th SDG would help correct this imbalance. It would give countries, universities and development agencies a language for measuring technological capability as a development outcome. It would ask whether a country can build, maintain, adapt and govern the technologies on which its development depends.

The proposed SDG 18 should include measurable targets: affordable and secure digital infrastructure; responsible AI governance; national data protection and data sovereignty frameworks; cybersecurity readiness; local language inclusion in digital systems; investment in research and development; technology transfer; local manufacturing of critical technologies; support for university-based innovation; and fair participation of developing countries in global technology governance.

The United Nations has already recognised the importance of digital cooperation through the Global Digital Compact. That is a positive step. But a compact is not the same as a goal. A compact can guide cooperation; a goal shapes measurement, accountability, funding, institutional behaviour and political priority.

Existing goals depend on technology

The SDGs matter because they tell the world what to count. If technological sovereignty is not counted, it will remain peripheral. If digital justice is not measured, it will remain rhetorical. If innovation capacity in the Global South is not treated as a development priority, the world will continue to reproduce dependency while speaking the language of partnership.

The world does not need an 18th SDG as if the existing 17 were already irrelevant. It needs one because the existing goals are increasingly dependent on technology.

Health systems depend on diagnostics, data and medical technologies. Education depends on connectivity and learning platforms. Agriculture depends on sensors, climate intelligence and logistics systems. Climate adaptation depends on modelling, satellites and early-warning tools. Governance depends on secure information systems. Work depends on digital skills and readiness for automation.

Technological sovereignty is, therefore, not a separate development concern. It is becoming the foundation for many existing goals.

The SDGs promised that no one should be left behind. In the 21st century, those most likely to be left behind are countries, communities and institutions that are locked out of the technologies that define the future.

The world needs an 18th SDG. It should be technological sovereignty and digital justice.

Professor Fulufhelo Nemavhola is the deputy vice-chancellor for research, innovation, and engagement at the Durban University of Technology (DUT) in South Africa.

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