'Knowledge Was Power' — The Depreciation of Knowledge

The air in the executive conference room was charged with a peculiar excitement.

Across the table, the CEO in his fifties was swiping through his tablet, letting out gasps of admiration. On screen was a risk analysis report for entering the Vietnamese market — one he'd personally generated the night before by feeding prompts into a generative AI. In the past, three junior analysts from the strategic planning division would have pulled all-nighters for two weeks straight just to produce a rough first draft of comparable depth. The report even had perfectly cross-referenced local regulatory nuances. The CEO smiled with satisfaction and said: "We can cut the research team in half now. No need to pay a premium for bright young things anymore."

My gaze drifted past the conference room glass to the twenty-somethings beyond the partitions, staring holes through their monitors. They had sacrificed over a decade to earn a seat at that table. Elite university credentials, hundreds of memorized textbooks, advanced foreign language skills carved into their brains. The asset called "knowledge" that they'd built by grinding away their youth was being rendered powerless in exactly 3 seconds by a $20-a-month subscription service. The entrenched seniors cheer at the ledger-line benefit of labor cost reduction, but for those at the bottom of the system who were just beginning to climb the ladder of knowledge, this reality is catastrophic.

Damn. This is a horrifically unfair game.

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The raw sense of dispossession soon transforms into a cold, logical question. Has the absolute proposition that was never once doubted in human history — Francis Bacon's declaration "Knowledge is power" (Scientia potentia est) — now been decommissioned? If knowledge can no longer guarantee power, where exactly are capital and authority converging in this era? We must answer this enormous question.

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The Death of Explicit Knowledge: Dissecting Knowledge Through Polanyi's Framework

To dissect this brutal phenomenon, we must borrow the epistemological framework of Michael Polanyi, the Hungarian-born philosopher and scientist. Polanyi decomposed human knowledge into two fundamental dimensions: "Explicit Knowledge," which can be clearly expressed through language and symbols, and "Tacit Knowledge," entangled with bodily experience and intuition, impossible to fully articulate in words.

Past education systems and knowledge labor markets placed a thorough premium on "the accumulation of sophisticated explicit knowledge." An accountant who memorized complex tax codes, a lawyer who commanded case precedents, an analyst who carried vast market data in their head — each was a walking database. Their explicit knowledge was expensive because it was scarce.

But the massive machinery called artificial intelligence has completely devoured Polanyi's realm of explicit knowledge. All forms of knowledge that can be digitized — text, numbers, code, blueprints — are no longer uniquely human assets. We must now redefine knowledge into three new matrices.

First, "Computational Knowledge." The ability to collect, classify data, and derive correct answers. Its value has already converged to zero.

Second, "Contextual Knowledge." The ability to connect information across different domains and produce situation-appropriate interpretations. Even this territory is being rapidly eroded by algorithmic advancement.

Third, "Embodied Knowledge." The intuition acquired by overcoming resistance in the physical world beyond the screen — the scars of failure, the ability to navigate complex interpersonal dynamics.

The axis of power is shifting from explicit knowledge in our heads to "embodied tacit knowledge" and "the ability to ask questions" — territories machines cannot reach. Those who know answers become tools; only those who design structures remain masters.

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Historical Patterns: From Gutenberg to Uber

This dismantling of knowledge-power and shifting of value axes is not the first time in human history. Structural contradictions always leave patterns. Every time a new tool emerged, specific classes lost their monopolies, and market rules were cruelly rewritten.

The first example is Johannes Gutenberg's movable type printing press in the 15th century. Before the press, the storage and reproduction of knowledge was the exclusive domain of Catholic clergy who monopolized manuscripts. They controlled scripture in Latin, wielding "information brokerage power" between God and humanity. But the printing press caused the marginal cost of knowledge reproduction to plummet vertically. Once anyone could read scripture in their native language, "possessing knowledge" itself was no longer power. The axis of value shifted from knowledge storage to "interpretation and application." The Reformation was not merely a theological debate — it was a transfer of power following a revolution in knowledge distribution infrastructure.

The second is a far more modern — and more blatant — case. Look at London's Black Cab drivers. To pass what's called "The Knowledge," the world's most notoriously difficult exam, they imprinted 25,000 streets and tens of thousands of landmarks onto their brains. This spatial cognition was their formidable barrier to entry and their guarantee of high income. But GPS systems and Uber's algorithms instantly rendered the spatial knowledge stored in their hippocampi worthless. Knowledge was absorbed into the platform's cloud, and drivers were reduced to terminal nodes performing only the physical labor of "holding a steering wheel."

If past technology smashed the rice bowls of specific classes, today's technology is taking dead aim at the entire foundation of white-collar knowledge workers.

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This Time Is Different: Why It's More Destructive

So how does the current phenomenon differ from the printing press shock or GPS shock of the past? Why does this collapse feel far more destructive and brutal? The essential difference lies in "the quality of knowledge being replaced" and "the speed of destruction." Past technology outsourced localized human functions like "memory" and "simple calculation," but today's AI is transferring "logical reasoning" and "pattern recognition" — capabilities believed to be the sanctum of human intellect — to external machinery.

The terrifying characteristics produced by this paradigm shift can be summarized as follows.

1. Irreversible Zeroing of Marginal Cost

Producing advanced knowledge as a human requires at minimum 20 years of education costs, enormous time, and daily caloric intake. Meanwhile, the marginal cost for AI to generate elite-level synthetic knowledge is a few cents in electricity. Human cognitive labor must now compete with the efficiency of power grids. A capital-input model with biological limits can never beat an electrical zero-marginal-cost model.

2. Collapse of Knowledge's Shelf Life

In the past, knowledge learned once could fund a lifetime pension. The validity of an elite university diploma lasted until retirement. But now, technology and industrial cycles outpace human learning cycles. A specific programming language or marketing technique studied for years can be decommissioned in mere months. Knowledge no longer accumulates — it evaporates.

3. Complete Extinction of the Middle Layer

There's no longer room for those who "sort of know." In the past, even those who couldn't be first could survive as second or third-tier knowledge workers, functioning as cogs within organizations. Now the market polarizes completely. Only a tiny minority of "Orchestrators" who oversee entire systems and control AI, and "Physical Nodes" who physically execute AI's conclusions, will remain. Middle managers and average knowledge workers will evaporate without a trace.

The boundary between what gets replaced and what survives has become clear. Everything that can be manualized will erode. What remains is only the metacognition to decide "what to ask" and the wild instinct to bear responsibility amid uncertainty.

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The Financial Statements of Knowledge: Is Your Brain a Non-Performing Loan?

At this juncture, to elevate the discussion, we must translate concepts we've taken for granted into the language of an entirely different domain. Let us reinterpret the reality of knowledge labor through the lens of corporate accounting and financial structure.

For the past several decades, we treated the knowledge inside human heads as "Permanent Assets" — like land or buildings. Attending a good university and earning difficult certifications was like erecting a building in prime Gangnam real estate. Once built, it guaranteed steady rental income (salary and status) for life without additional investment. This was a grand idol built on the illusion that knowledge never loses value.

But let's face reality. Knowledge is by no means a permanent asset. It is a machine that deteriorates rapidly over time — a tangible asset subject to Depreciation.

Suppose you recorded the advanced data analysis techniques or industry-specific regulatory knowledge you acquired five years ago at "acquisition cost" on your ledger. This asset's value is declining every single day, right now. As AI and automation tools advance, the "depreciation expense" on your knowledge grows exponentially. The gap between book value and actual market value widens.

What's even more terrifying is that when the market paradigm shifts completely, your knowledge doesn't merely depreciate — it gets written down to zero as an "Impairment Loss." Just as accounting writes down an asset's book value to zero when it's no longer expected to generate future economic benefits, your expertise can be expelled from the market overnight.

From this financial frame, seniors clinging to past knowledge and juniors following old credential formulas are essentially holding "Non-Performing Loans (NPLs)" that don't even generate interest. Just as corporations employ sophisticated tax strategies to offload NPLs at fire-sale prices to asset securitization vehicles, individuals too must make the brutal decision to write off and cut losses on their obsolete knowledge.

Knowledge bound to past success formulas is no longer a revenue-generating asset but merely a sunk cost eating away at maintenance expenses. True capital lies not in hardened expertise but in "Cognitive Liquidity" itself — the ability to wipe the ledger clean and rapidly absorb new rules in any changing environment. Only those who accept that the knowledge in their heads could become a non-performing loan tomorrow will survive the next turn of the market.

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We must not expect grandiose system redesigns or the kind of shallow, sentimental solutions that call for restoring human dignity. The combination of capitalism and technology never shows mercy.

In this era where the depreciation speed of knowledge astronomically outpaces the biological adaptation speed of humans, we must pose a weighty question to ourselves. In a world where explicit knowledge is replicated for free and our cognitive labor is reduced to a non-performing loan on an accounting ledger, where exactly does the intrinsic commercial value of "the human individual" reside? When the value of "knowing things" — the pursuit to which we devoted our lives — converges to zero, with what do we prove our existence to the market?

There is no answer. Structural contradictions only accelerate at speeds beyond our control.

The conference room air remains buoyant, and the juniors outside are still wrestling with Excel data that may soon become meaningless. I pull my gaze from the window and pick up the thick quarterly industry trend report sitting on my desk. Fragments of knowledge that might be replaced by an algorithm's summary as soon as tomorrow.

But to defend my position today, I need to at least grease this aging machinery.

I'm going to go fire up my depreciating brain and read these tedious texts now. Damn.

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