Artificial intelligence transforms cognition into a strategic resource, reshaping science, cybersecurity, and national sovereignty. This editorial examines the challenges of cognitive inflation, surveillance capitalism, and underdeveloped information theory, urging Canada to leverage its energy and cryptographic strengths to safeguard intellectual integrity and maintain a competitive edge.

The Surplus of Thought

The rise of large language models (LLMs) marks a turning point in history. This phenomenon—electric thinking—turns parts of research into a computational service powered by energy and data rather than time and lived experience.

Abundant, low-cost cognition might seem to promise a golden age of knowledge and creativity. Yet economics warns that when something becomes plentiful, its marginal value declines. We are entering an era of cognitive inflation, where the sheer volume of generated content threatens to dilute meaning.

Fields of Resilience

Some disciplines remain resistant to these inflationary pressures. Pure and applied mathematics, as well as foundational science, advance through concepts built for the human mind. These fields are defined by depth—structures and insights that cannot be mechanically recombined or statistically approximated. They demand intuition, rigor, aesthetic judgment, and philosophical orientation.

Few researchers believe machines will soon solve the hardest open problems—such as the Millennium Prize Problems or controlled nuclear fusion. Could AI have discovered quantum mechanics? Paradigm shifts of that magnitude demand more than inference. As historian Paul Forman argued in the 1970s, breakthroughs arise from the Zeitgeist—the cultural and intellectual currents shaping scientists’ minds.

The humanities are likewise resilient. Even in fiction, where AI can imitate style, it is more likely to produce endless remakes than to give us a new Faulkner, Highsmith, Bergman, or Kieślowski. Style can be mimicked; vision cannot.

Triage for Electric Thought

This flood of ideas forces us to rethink how we assess quality. Traditional metrics—publication counts or short-term citations—are inadequate. Journal referees and grant reviewers face unsustainable workloads, leading to evaluations that are often uneven and uninsightful. Machines will need to assume part of this triage, though not without raising questions of judgment and accountability.

Not all research aims for immediate results. Some work creates long-term conceptual shifts, whose significance emerges only decades later. We must distinguish between near-term applicability and deep, deferred insight.

A telling example is LLM AI itself. Its “sudden” success rests on over 40 years of foundational work in neural networks and computational theory—much of it once considered speculative.

For near-term research, filters might include:
• Actionability – Can the idea be implemented under current conditions?
• Economic Viability – Is it sustainable and worthwhile?
• Human or Social Benefit – Does it improve lives and uphold dignity?

Long-horizon research requires another lens: transformative potential, the capacity to reshape how we think, work, or live.

Energy, Strategy, and the Battle for Thought

Electric cognition will reshape not only research but also strategy, diplomacy, and warfare. As thought becomes externalized, server farms and energy grids become strategic assets—no less vital than oil fields once were.

Disabling an adversary’s cognitive infrastructure could become a first-strike option, crippling the ability to plan or simulate. Betrayal now takes the form of poisoned inputs and misaligned inference systems.

Surveillance Capitalism and Privacy

Surveillance capitalism is a powerful force steering technology, thriving on the extraction and monetization of personal data. Machines track habits, movements, and preferences in real time, creating vulnerabilities where key military or infrastructure personnel can be profiled or targeted.

A pushback against domestic commercial surveillance is now a matter of national security. Yet absolute secrecy also fosters criminal activity. We need balanced oversight, where trusted government bodies protect citizens without abusing power, aided by tiered cryptographic models that allow lawful access under strict conditions.

This tension—between privacy, security, and trust—will define the age of electric thinking. It demands technical, legal, and ethical frameworks that adapt to an AI-enabled surveillance economy.

Beyond Shannon: Rethinking Information

The Shannon framework, built for an earlier era, defines information through entropy alone. Yet a high-entropy encrypted image and its original contain equal “information,” despite stark differences in meaning and utility. The key that facilitates access to encrypted information is nothing but a string of random bits—highlighting the conceptual gap in how information is currently understood. Quantum information theory, while powerful, does not address this issue.

What is needed is a post-Shannon theory of information—one that integrates semantics, structure, and adversarial awareness, uniting classical, quantum, and AI perspectives. To move forward, we must draw on insights from the mind sciences: brain science, psychology, philosophy, and more. Genuine progress will depend on conversations that bring together researchers from multiple domains. This kind of deep synthesis is more likely to emerge from a Bletchley Park–style model of urgent, cross-disciplinary collaboration than from the conventional rhythms of academic discourse. One of the first tasks is to design ledgers that preserve and reference meaningful, original thought.

A Canadian Perspective: Safeguarding Sovereignty

Canada enters this era with unique advantages: abundant renewable and nuclear energy, political stability, and vast space for secure infrastructure. Yet energy alone is not enough—cryptography must form the nervous system of cognitive sovereignty.

1. Cryptography as Strategic Infrastructure
Encryption is now foundational, protecting not just data but reasoning pipelines. Future conflicts will target the integrity of thought itself via data poisoning or adversarial manipulation. Canada must invest in quantum-resistant, lightweight cryptographic protocols designed for AI-native environments.

2. Energy and Cognitive Infrastructure
Our hydroelectric and nuclear resources allow Canada to host AI systems independently of foreign control. Cold-region data sanctuaries in the Arctic could combine thermal efficiency with geopolitical security. Yet without cryptographic fortification, such infrastructure is vulnerable.

3. Research and Governance
Canada must lead in:
• Cognitive Infrastructure Engineering – Secure, distributed computation and decision-making with built-in cryptographic verification.
• Epistemic Governance – Maintaining ledgers that track provenance and compress intellectual content, sifting durable ideas from over-verbose output—an antidote to epistemic inflation.
• Human-AI Oversight – Ensuring human contributions remain traceable and meaningful.

The Vision: Canada can lead not by scale, but by strategic depth and foresight. As central banks once safeguarded currency, we must now build institutions that preserve the authenticity and value of cognition itself.

Acknowledgment

This editorial was developed with the assistance of ChatGPT (OpenAI), used as an interactive drafting partner. While the ideas, structure, and final editorial judgment are our own, ChatGPT contributed to shaping phrasing, condensing sections, and improving clarity.