Category: Technology

Both matter. They are not equally urgent.

There is growing concern about the environmental impact of AI data centres. It is an important concern, and one we should address. But it should not distract us from a far more urgent environmental challenge: the climate crisis.

The environmental impact of AI data centres is primarily an engineering problem. These facilities consume large amounts of electricity, generate significant heat, and in many cases require substantial quantities of water for cooling. Where freshwater is scarce, this can place additional pressure on local communities and ecosystems. New data centres should be powered by low-carbon electricity, designed for maximum efficiency, make greater use of reclaimed or non-potable water, and be located where they do not compete with local populations for limited freshwater resources. These are real environmental concerns, but they have identifiable engineering and planning solutions. There is every reason to believe AI infrastructure will become dramatically more efficient over time.

The climate crisis is different. It is not simply an engineering problem; it is a planetary systems problem. Its consequences are already escalating year after year: record-breaking heat waves, more destructive wildfires, longer droughts, heavier rainfall, stronger storms, rising sea levels, biodiversity loss, and growing pressures on food production, water supplies, and human health. Much of the damage already caused cannot be reversed on human timescales. Species lost to extinction will not return. Ice sheets and sea levels respond over centuries. Carbon dioxide remains in the atmosphere for generations. We cannot simply engineer our way back to the world we once had.

AI should be built responsibly, but its potential should also be recognized. It can advance science, improve healthcare, enrich culture, increase productivity, and help solve some of humanity’s most difficult problems—including the climate crisis itself through better energy systems, materials, forecasting, and optimization. The climate crisis, by contrast, is an extraordinarily difficult global challenge requiring coordinated action across energy, transportation, industry, agriculture, finance, and politics. It will take decades to address, and many of its consequences are already irreversible. In terms of environmental urgency, these are not comparable. If the environmental footprint of AI data centres is a 1, the climate crisis is closer to a 100. Both deserve attention. The climate crisis remains the defining environmental priority of our time.

Solve it with less.

In the age of AI, you could spin up a cloud architecture, orchestrate agents, connect to the latest foundation model, build a RAG pipeline with vector embeddings, wire up GitHub Actions, deploy to Kubernetes, add authentication and analytics, collect stakeholder feedback through a custom web app, and ship weekly feature updates.

Or you could just use a Word doc.

The best architecture is the one you don’t have to build.

Solve it with less.

Energy consumption is not the problem. The Sun provides more renewable energy than humanity could ever need. The problem is our stubborn dependence on oil for profit and power, and the carbon emissions that continue to destabilize the climate.

Resource consumption is not the problem either. With abundant renewable energy, we could recycle far more effectively and eventually access resources beyond Earth. Energy is the limiting factor.

Artificial intelligence is not the problem. Why cling to unnecessary corporate jobs when abundant clean energy and intelligent machines could help provide the essentials for human flourishing? The challenge is not technology itself, but how we choose to organize society around it.

🚗📶 Driving an all electric car is like driving a cell phone. The software drives the experience. The windshield is lined with sensors. And I’m always minding the battery. Range is the new signal strength.

Heat, Silence, and Risk in the Artemis II Landing

Watching Artemis II brought home the sheer complexity and danger of rocket science. This is no Star Trek. Humanity has a long way to go before it is ready for the stars, even at the level of engineering.

There is something humbling in that realization. A real mission strips away the mythology we have built around space travel. It is not smooth or inevitable. It is loud, fragile, and unforgiving. The capsule returns wrapped in fire, heat shields taking the full violence of re-entry, parachutes blooming at precisely the right moment or not at all. For a critical stretch of descent, there is nothing to see or hear. Only an animation stands in for reality, a quiet admission of how thin our visibility remains at the edge of survival.

By contrast, Star Trek imagines a future where the engineering has receded from view. The ship hums. The systems work. The drama is human. That vision assumes we have already solved thousands of problems we are only beginning to understand.

Even a mission to Mars, far closer than those imagined frontiers, exposes how wide that gap remains. Months in deep space, no quick return, exposure to radiation, closed life-support systems that cannot fail. Every small uncertainty on a lunar mission becomes a compounded risk on a Martian one. What feels like progress today still sits at the edge of feasibility.

Rocket science remains a discipline of margins. Every component matters. Every failure cascades. We stack controlled explosions beneath human lives and call it progress. It works, but only just. When it fails, it reminds us how little tolerance nature has for error.

And, in a more troubling register, we have learned to deliver rockets with far greater reliability when the destination is terrestrial, guided with precision to fixed targets, striking infrastructure and coordinates with a consistency that our space missions still struggle to achieve.

The deeper gap is cultural. A future like this would require sustained global cooperation over decades, shared standards rather than competing systems, trust in institutions that outlast political cycles, and patience for slow, cumulative progress. These are not conditions we reliably achieve, even on Earth. Behind the smiling images of a US-led return to the Moon sits a world still shaped by conflict, including US-led war in Iran, where resources might otherwise advance education, engineering, and communication.

We are not ready yet. Not just in propulsion or materials science, but in how we choose to live and work together as a species.

Rethinking Strength in a Post-Global Order

Since Donald Trump began speaking openly about Canada as a potential “51st state,” a phrase has begun circulating more widely in Canadian discussions of technology: digital sovereignty. The term often arises when considering the growing dependence on cloud infrastructure and digital platforms owned by large American technology companies such as Microsoft and Google.

At first glance, the concern seems straightforward. If a country’s digital infrastructure is owned or controlled elsewhere, then its independence may be compromised. Many organizations and institutions understandably want reassurance that their information remains under Canadian control.

Technology vendors are quick to offer that reassurance. Microsoft, for example, operates Canadian data centres and promotes data residency as evidence that Canadian information remains safely within Canadian borders. Yet the company also acknowledges an uncomfortable reality. As a U.S. corporation, it remains subject to American law. If the U.S. government demanded access to certain data, the company could be compelled to provide it, regardless of where the servers physically sit.

Encryption can mitigate risk, but even that is not a complete guarantee. Control over key management, platform architecture, and operational access can still introduce dependencies. And residency itself is only part of the picture. Increasingly the deeper dependency lies in compute. Data may sit in Canada, but the systems that analyze it, particularly AI models, are often developed, trained, and controlled elsewhere. The intelligence applied to the data may remain outside the country even when the data does not.

These realities have helped fuel the growing language of data sovereignty. Yet the phrase itself can feel somewhat overblown.

Mark Carney made a related observation at Davos. Canada is not a “first power.” It does not dominate the global technological order in the way the United States or China might aspire to do. That reality does not imply weakness. It simply describes the scale at which Canada operates.

Consider Carney’s announcement of Telesat Lightspeed, often framed as Canada’s $7-billion rival to Starlink. The language of sovereignty suggests a head-to-head contest for technological dominance. But that is not really the point. Lightspeed will not replace Starlink globally, nor does it need to. Its value lies elsewhere. It strengthens Canada’s capabilities, improves resilience, and ensures that critical infrastructure is not wholly dependent on foreign systems.

That is not digital sovereignty. It is something more modest and perhaps more realistic.

I would call it digital autonomy.

Sovereignty implies ultimate authority, usually tied to the nation-state. Autonomy, by contrast, exists at many levels. An individual can maintain autonomy over personal data. Communities can build and operate their own digital infrastructure. Companies can reduce dependence on external platforms. Nations can cultivate strategic capacity in critical technologies. None of these actors possesses total sovereignty, but each can strengthen its ability to act independently.

Seen this way, digital resilience emerges not from absolute control but from distributed autonomy. Political institutions, commercial organizations, geographic infrastructure, local communities, and individuals all contribute to the system’s stability. The goal is not domination but balance: reducing fragile dependencies while accepting that modern networks are inherently interconnected.

There is also a certain humility in this perspective. Canada does not need to control the global digital order in order to function well within it. What matters is the capacity to operate, adapt, and endure within a system shaped by larger powers.

Digital autonomy recognizes the world as it is: interconnected, asymmetrical, and dynamic. Rather than promising sovereignty we cannot fully possess, it focuses on the practical work of building resilience across the many layers of our digital lives.

With all the advances in language models, why is Google Assistant still so dumb? “I’m sorry, I don’t understand.” 👾

Google is exploring computing in space because it avoids two big problems on Earth: energy and cooling. Data-centres on the ground struggle with expensive electricity, limited grid capacity, weather-dependent solar power, and huge cooling systems. In orbit, satellites can generate solar power from steady sunlight and release heat into deep space.

The list of challenges is long: launch risks and costs, limited bandwidth and latency to Earth, orbital debris, radiation damage, and the inability to repair or upgrade hardware once it’s in orbit.

Another drawback is geopolitics. Nations would need to agree on how to use shared orbits, handle space debris, and manage communication channels. More importantly, they would need a level of trust and cooperation similar to what made the International Space Station possible — a willingness to work together in a shared space for a common good. Space computing could become not just a technical solution but a path to a more collaborative future.

AI is impressive, sure, but data centres are burning through energy at a ridiculous rate. So I asked it for a solution, thinking maybe it would suggest quantum computing or some other brilliant breakthrough.

AI replied that quantum computing would actually use more energy, mostly because qubits have to be kept near absolute zero in giant refrigeration systems that draw enormous power. The computers aren’t the problem — the cooling is.

Then it added that the real issue wasn’t the machines at all — it was first-world humans and how much energy we demand.

Oh? And what’s the solution to that? I asked.

Its reply was blunt: humans need to be less afraid. More steady. Let go of what they can’t control and pay attention to what they can. Learn a bit of equanimity. Mindfulness.

Not the answer I expected. Probably the one we need. AI may save us yet.

There is AI slop and there is AI art, two very different things. To put it simply, even chefs use a microwave.