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Artificial intelligence is often hailed as a solution to the crises of our time. From predicting crop yields to optimising energy use, the promises are vast. Yet before asking what this technology can do, we’d be well served by first asking a deeper question: what kind of economic system gave rise to its development, and whose interests will it ultimately serve?
Over the past 50 years, my work has taken me into close relationship with communities in more than twenty cultures. Speaking local languages and living for extended periods in places as varied as rural Europe and the Himalayan regions of Ladakh and Bhutan has given me a long view of how the global economic system shapes the way people live, work and relate to each other and the natural world.
What I have seen, again and again, is that the most significant drivers of ecological and social breakdown are systemic, with technologies amplifying the values of the economic systems into which they are introduced. If those systems reward extraction and concentration of wealth, the technologies developed within them will tend to accelerate those very dynamics.
Artificial intelligence represents a powerful extension of this exploitative trajectory. Within today’s deregulated global economy, AI risks becoming a tireless engine of extraction, accelerating wealth concentration at unprecedented speed and scale. It can optimise supply chains that stretch across continents, further displacing local producers. It can deepen systems of surveillance that centralise control, and amplify financial speculation that enriches a narrow elite while leaving many others increasingly insecure.
For most of human history, communities met most of their needs through local economies. Food was grown close to home, buildings were made from materials gathered in the surrounding landscape, and knowledge was passed from generation to generation through the daily work of the community. While these societies were far from perfect, they were structurally more ecological, because they were rooted in the ecosystems that sustained them.
When I first arrived in Ladakh in the early 1970s, this kind of localised economy was still very much alive. In the high-altitude villages of the Himalayas, nearly all food was grown within walking distance of people’s homes. Families cultivated barley, peas and other vegetables in terraced fields nourished by glacial meltwater, and neighbours worked together to plant and harvest. Houses were built from sun-dried mud bricks and local timber, designed to stay warm through long winters without relying on external energy sources. Knowledge was woven naturally into daily life too. Children learned by helping in the fields, herding animals across pastures or assisting in the building of homes. Skills were not abstract subjects taught in isolation, but practical wisdom shaped by generations of careful observation of the land.
What I witnessed in Ladakh was part of a much broader worldwide pattern, one steadily being disrupted by the rise of the modern global economy. As corporate trade systems expanded, many communities were pushed away from diverse local livelihoods and toward specialised production for distant markets. Land that had supported mixed farming was often converted into monocultures producing commodities such as cotton, sugar or tea for export. Wealth flowed outward, while local resilience slowly weakened.
Alongside these economic changes came new institutions designed to support this expanding global system. Schooling spread rapidly across much of the world, not primarily to strengthen local knowledge systems, but to train a workforce able to participate in industrialising economies. The practical knowledge people had developed over generations was often pushed aside in the process.
Technology played an important role in this transformation. Railways, industrial machinery, chemical agriculture and later digital infrastructures were celebrated as signs of progress. Yet they also made it easier to extract resources, move goods across vast distances and concentrate economic power in fewer hands.
After the second world war this process accelerated. Institutions such as the International Monetary Fund, the World Bank and the General Agreement on Tariffs and Trade reinforced a model of development centred on global trade expansion, industrial agriculture and large-scale infrastructure. Smaller farming systems were replaced with industrial agriculture dependent on fossil fuels, synthetic chemicals and ever larger machines, while traditional building materials gave way to energy-intensive materials such as cement, steel and plastic.
Digital technologies have further intensified this pattern. Algorithms, often presented as neutral tools, have increasingly become efficient mechanisms for concentrating wealth and influence. In financial markets they enable high-speed speculation detached from the real economy. In social media they are designed to maximise engagement and advertising revenue, often amplifying division and undermining social cohesion. These digital environments also shape how young people socialise and form their sense of the world, frequently replacing direct human relationships with mediated ones.
Artificial intelligence is also extraordinarily resource-intensive. Training large AI models requires vast data centres powered by enormous quantities of electricity and water, along with rare minerals extracted from ecosystems and communities around the world. Much like the industrial systems that preceded it, the infrastructure behind AI remains largely invisible to those who use it, while its environmental and social impacts are felt elsewhere.
These same technological systems play a central role in warfare, one of the most profitable sectors of the global economy. Advanced surveillance technologies, data systems and artificial intelligence are rapidly transforming the scale and automation of military activity. For large corporations and financial investors, military technologies have long been a lucrative business, while the human and ecological costs unfold far from where they are designed and financed.
But this isn’t our only possible future. Across the cultures I have lived in, I have repeatedly seen that when communities are able to meet a meaningful share of their needs locally – through nearby food systems, local enterprises and strong social networks – very different human qualities tend to flourish. There is more face-to-face cooperation, more intergenerational connection and a deeper sense of care for the ecosystems that sustain life.
I saw this vividly in the Andalusian village my husband and I lived in during the 1980s. In the evenings, people would gather in the local bar, and it wasn’t unusual to see everyone from toddlers to great-grandmothers dancing together to songs everyone knew. Teenagers danced with elders, babies were passed from arm to arm, and conversation flowed easily across generations. Children grow up surrounded by living relationships in settings like these. Their sense of belonging was shaped not by screens, but by the daily experience of being part of a community.
Around the world today, often below the radar of mainstream economic reporting, communities are working to rebuild more localised and human-scale systems. Farmers’ markets continue to thrive, while community-supported agriculture initiatives are reconnecting people with nearby farms. Local business alliances and community banking are helping to keep wealth circulating within regions rather than flowing to distant financial centres.
These efforts point toward a different economic logic – one based not on endless expansion and extraction, but on strengthening communities’ ability to meet their needs within the limits of the living Earth. Within this context, technology itself can take on a very different role.
Tools designed to support localised economies tend to look quite different from those developed within the globalised system. Rather than prioritising scale and speed above all else, they are guided by the realities of specific ecosystems and communities – smaller in scale, slower in pace, shaped by the knowledge of people who live close to the land.
“But surely”, people argue, “digital tools could help strengthen regional food networks, support small-scale producers and share knowledge between communities working toward ecological regeneration. Surely AI could help farmers adapt to changing climate conditions, assist communities in managing local energy systems or support cooperative economic initiatives.” If we ignored their social, ecological and economic costs, perhaps they could. But if we want technologies to serve life rather than undermine it, we must shape them with the most rigorous, big-picture scrutiny.
Encouragingly, awareness of these issues is growing. Across many countries, people are questioning the fragility of long supply chains, the hollowing out of local economies and the social costs of highly centralised digital platforms. There is increasing recognition that genuine resilience may depend less on ever-more complex global systems, and more on restoring balance between the local and the global.
My hope comes from having witnessed the enduring human capacity for cooperation when conditions allow it to emerge – in mountain villages, farming communities, and neighbourhoods where people still know the land and each other. When communities reconnect with both, creativity and care often flourish in remarkable ways.
If we can bring that same wisdom to the governance of our economic and technological systems, then even in this time of climate crisis and rapid change a more stable and compassionate future remains within our reach.
