The Clearinghouse
Every crisis — real or not — yields the same demand: someone must sit in the middle and sort it out. War reparations need processing, bank failures need coordinating, carbon emissions need measuring, pandemic responses need directing.
The details change with time, but the demand is always for an intermediary that manages the terms of the transaction between the parties involved.
This intermediary is a clearinghouse.
The clearinghouse does not need to own anything, conduct science, make policy, or lend money. It only needs to judge compliance versus a given set of standards. Because above the clearinghouse sits whoever compiled the standards.
The clearinghouse is the mechanism; the standard-setter is the authority — and the two are rarely the same people. And this matters because the people who decide whether your country can access development finance, your house can be insured, your business can borrow, and your money can be spent were never elected, never named, and never asked your permission.
How It Works
A clearinghouse sits between two transacting parties, determining whether terms are met. In banking, the clearing function decides which payments should settle and at what cost. In governance, it establishes what triggers a response and what form the response takes. In information, it flags misinformation and determines which are credible sources.
In each case, the terms the clearinghouse applies were defined elsewhere — by a committee, a model, a treaty, or a standard-setting body that the transacting parties may never even encounter.
The principle scales without limit. A bilateral clearinghouse — one bank sitting between two sovereigns — handles a single transaction. An institutional clearinghouse such as the Bank for International Settlements handles all transactions between all central banks. A standard-setting body such as the Basel Committee on Banking Supervision determines how much capital every significant bank must hold, and national regulators apply its standards as the clearinghouse through which banks must pass.
At each stage, the scope increases and the visibility decreases. The bilateral banker is obvious. The Basel Committee is invisible to anyone outside financial regulation. The unnamed body that compiles the parameters feeding into the Basel framework is invisible to almost everyone. And it is in that upstream position — the compiler of standards, rather than the applier of them — where power is concentrated.
The Ethic, the Standard, and the Demand
Every clearinghouse requires a justification — a governing concern that creates public demand for coordinated action. The concern provides the ‘ethic’, while the coordinated action is considered ‘justice’.
The architecture has a British origin. By the mid-nineteenth century, the London Bankers’ Clearing House settled hundreds of millions of pounds weekly between member banks through accounts held at the Bank of England.
Alfred de Rothschild, a former Director of the Bank of England, described the system at the 1892 Brussels International Monetary Conference as approaching ‘perfection’. At the same conference, Julius Wolf proposed extending this identical architecture onto the international plane: gold-backed clearing certificates administered by a joint institution in a neutral country.
The London Clearing House settled between domestic banks. Wolf’s proposal would settle between nations. The architecture was the same — only the scale changed.
Forty years later, when Political and Economic Planning published its blueprint for the total reconstruction of British economic life, every institution required radical change — except the Bank of England, which already possessed, in PEP's words, the perfect constitution for the new order.
Back in the late nineteenth century, the ethic was sovereign debt management. After the Franco-Prussian War (1870-1871), five billion francs in reparations between France and Germany had to be processed, with private banks performing this function.
After the First World War, the same function (war reparations) was formalised into the Bank for International Settlements, established in 1930 under a functioning gold standard that provided a common reference point for settling between currencies.
The BIS was Wolf's proposal realised — a joint institution in a neutral country, settling between nations. The Bank of England template scaled internationally.
The gold standard disintegrated almost immediately. Britain abandoned gold in 1931; most countries followed within a few years. Without the common anchor, exchange rates became volatile and competitive devaluations proliferated. The gold standard had not merely made active state management of the economy unnecessary — it had precluded it, by tying the money supply to a physical reserve that no government could print. Its removal was the precondition for what followed.
Keynesian economics filled the vacuum, providing the intellectual framework for countercyclical fiscal and monetary policy — active state management of money, demand, and employment. In doing so, it expressly politicised the economy, binding fiscal policy to central bank coordination as a permanent dependency.
The resulting currency chaos and the new economic consensus generated demand for a new intermediary — not to process reparations, but to stabilise the medium of exchange itself. The ethic had shifted from sovereign debt to currency stability, and the clearinghouses that emerged were the International Monetary Fund, established at Bretton Woods in 1944 to oversee fixed exchange rates and provide balance-of-payments support, and the World Bank, established alongside it to channel development finance on conditional terms.
When Nixon suspended gold convertibility in 1971, the last external constraint on monetary expansion was removed — and the IMF’s role shifted from managing fixed rates to surveillance and conditional lending.
In the late twentieth century, the ethic was financial stability. After successive banking crises, someone had to set capital adequacy standards — minimum thresholds of reserves that banks must hold — so that they would not over-leverage themselves into collapse. The Basel Committee performed this function.
In the twenty-first century, the ethic is sustainability. Climate risk, biodiversity loss, and environmental governance have created demand for new standards, new scenarios, and new intermediation.
The Network for Greening the Financial System — a consortium of 134 central banks and supervisors — now performs this function.
The sustainability ethic also provides the justification for an older ambition: central bank authority over fiscal policy. The case was built through recurring crises. The 2008 financial crisis supposedly demonstrated that monetary and fiscal policy operating independently produced instability.
COVID, however, demonstrated that the two had already merged in practice — central banks monetised government deficits on an unprecedented scale, funding the fiscal response directly. Without central bank accommodation, most countries could not have afforded to lock down during Covid at all.
Each crisis expanded the remit of the central banks, and each failure of that expanded remit was used to justify further expansion.
In 2023, the Fabian Society published In Tandem, proposing that the Bank of England be granted a statutory mechanism to direct the Treasury’s fiscal stance — including formal letters to the Chancellor and a new coordination committee with pre-budget statutory meetings.
The proposal is framed as coordination, but in practice, it would make the central bank the senior partner — no longer merely applying standards to capital flows, but dictating the fiscal conditions under which the sovereign itself operates.
The nation state would, in practice, be compelled to follow fiscal policy guidance set by technocratic institutions including the central banks themselves, or the politicians would be Truss’ed.
The pattern is consistent. A crisis generates fear, fear generates demand for coordination, coordination requires standards, and standards require a standard-setter. The clearinghouse then applies those standards as the intermediary through which all transactions must pass.
And those politicians who go their own way don’t tend to last for long.
The same template has now been replicated across every major domain of human activity — technology, health, finance, information, resources, climate — with comprehensive institutional frameworks now pre-positioned and awaiting activation. It’s just a matter of drumming up the facilitating crisis.
The clearinghouse is generally visible — a bank, a regulator, an institution. The standard-setter who defines the parameters it applies is generally not.
The Migration
The international clearinghouse function has migrated through five distinct stages over two centuries, each migration making it harder to see.
In the first stage, the clearinghouse was a private bank. Gerson von Bleichröder processed German war reparations on one side whilst the Rothschild syndicate raised bonds on the other. The intermediary was a named individual at a negotiating table, and everyone involved knew who sat in the middle.
In the second stage, the clearinghouse became an institution. The Bank for International Settlements, established in 1930 to administer reparation payments, absorbed the private clearing function into a formal organisation with a sovereign mandate.
The function was identical — intermediating capital flows between states — but the wrapper was multilateral rather than private, and it looked like neutral governance.
In the third stage, the standard-setter and the clearinghouse began to separate. In 1988, the Basel Committee published its first Capital Accord, establishing minimum capital requirements for banks across the G10 and beyond.
A single committee’s technical framework now determined how much reserve capital banks worldwide were required to hold.
The committee had no democratic mandate and no legislative authority, yet it compiled the standards.
The Financial Stability Board coordinated their adoption across jurisdictions, and national regulators became the clearinghouse through which those standards were applied as domestic law to every bank within their jurisdiction.
In 1989, the Financial Action Task Force was established to complete the architecture — providing the enforcement mechanism through which non-compliant jurisdictions could be greylisted or blacklisted, triggering financial exclusion without requiring legislation in any country.
The tiers crystallised: Basel compiled the standard, the Financial Stability Board coordinated its adoption across jurisdictions, national regulators applied it, and FATF enforced it through the financial system itself. Basel II, Basel III, and now Basel 3.1 have progressively extended this framework, each iteration adding new parameters — including, most recently, climate-related risk — to the calculation.
In the fourth stage, the standard-setting function migrated into ‘black box’ computational models. The regulatory clearinghouse remained — the capital framework, the stress testing process, the national regulators — but the parameters feeding into it were now generated by models rather than negotiated between parties.
Climate scenarios, stress tests, and risk weightings are all model outputs, and whoever designs the model’s assumptions determines what the financial system does. The clearinghouse merely transmits the result.
The criteria the models enforce — climate risk, ESG compliance, stakeholder accountability — trace back to ethical governance frameworks codified globally after the Enron collapse, themselves descended from interfaith declarations on business conduct drafted a decade earlier.
In the fifth and most recent stage, the clearinghouse is migrating into the money itself. Central bank digital currencies — now in pilot or development in over a hundred countries — introduce programmability to the medium of exchange.
Conditional money can judge and execute at the point of transaction: a payment approved or declined based on the carbon footprint of the purchase, the environmental rating of the vendor, the geographic restrictions on the currency, or any other condition written into the code.
At this stage, the clearinghouse is no longer a separate institution sitting between two parties. It is embedded in the instrument they use to transact. The intermediary has disappeared from view because it has become indistinguishable from the money. The parameters that once required a named banker, then an institution, then a regulator, then a model, are now encoded in the currency itself. The clearinghouse has migrated into money, with an ‘ethic’ its ruling aspect.
Moses Hess’s Essence of Money (1845) will finally come to fruition, though no-one appears to realise.
The conditional CBDC operates at the level of the individual — every purchase conditionally cleared at the point of sale. The same logic applies at every other scale.
At the level of the enterprise, ESG-integrated capital markets perform the same function. A company’s bond pricing, credit terms, insurance availability, and listing eligibility all adjust based on compliance scores compiled against upstream standards. The enterprise experiences this as market conditions — the cost of capital simply rises or falls depending on how well the company performs against metrics it did not set. It does not experience it as explicit governance.
At the level of the sovereign, the mechanism is even older. It originates in Robert McNamara’s Planning, Programming, and Budgeting System, introduced at the Department of Defense in 1961: set objectives, measure performance, allocate resources conditionally based on results.
When McNamara moved to the World Bank in 1968, he carried the same framework into development lending — aid conditional on measurable outcomes. Today, impact investing and development finance apply the identical logic to entire countries.
Disbursement-linked indicators determine when capital flows; in UN capacity this means SDG indicators — derived from global surveillance data spanning health, environment, economics, and social conditions — serve as KPIs under results-based management (RBM). A country receives funding when it hits thresholds set by those upstream.
The receiving sovereign does not experience this as governance — it experiences it as investment climate.
The three scales interlock.
The sovereign must meet SDG indicators to access development finance.
The enterprise must comply with ESG frameworks to access capital markets.
The individual must transact through the conditional currency to access the economy.
Each scale’s compliance requirement cascades downward into the next — one architecture, three scales, total coverage — governed by parameters compiled in the same place. The ethic that justifies the compliance at every scale is the same: the seventeen Sustainable Development Goals, whose moral authority makes the architecture invisible.
Each migration has followed the same logic: the scope increases, the visibility decreases, and the accountability diminishes. A bilateral banker controlled one transaction between two sovereigns. A conditional currency controls every transaction in an economy.
The Black Box
In earlier iterations of this pattern, parameters were set through negotiation. Bismarck’s banker argued over the size of the French indemnity at Versailles. Central bankers debated capital ratios at Basel. The process was slow, political, and at least partially visible.
The modern iteration has removed negotiation from the process entirely, because the parameters are now set by models.
In December 2025, the Network for Greening the Financial System announced the creation of an independent scientific advisory committee to oversee the climate scenarios that calibrate global banking capital requirements. No members were named and no terms of reference were published.
The scenarios this committee validates are produced by a consortium funded by Bloomberg Philanthropies and the ClimateWorks Foundation. The disclosure framework that created demand for those scenarios was chaired by Michael Bloomberg. ClimateWorks sits on the advisory council that organises scenario production for the Intergovernmental Panel on Climate Change.
The same ‘philanthropic’ entities fund the science, the disclosure standards, the research network, and the regulatory guidance.
The NGFS scenario is a model output. The model is a black box — its assumptions, weightings, and sensitivities are not subject to parliamentary scrutiny or democratic override. When the model produces a scenario in which fossil fuel assets carry elevated risk over a thirty-year horizon, that scenario feeds into regulatory stress tests.
The stress tests determine how much reserve capital banks must hold against those assets. The larger the reserve, the more expensive the asset becomes for the banks. The capital requirements consequently determine whether it remains economic for banks to hold them at all. When the cost exceeds the return, the assets become stranded — rendered uneconomic by a parameter change inside a ‘black box’ model that no elected official reviewed.
Stranded by Design
The stranded asset mechanism illustrates how this template reaches the general public.
An unnamed NGFS scientific advisory committee validates a climate scenario. Central banks adopt the scenario as the basis for stress testing. The stress test determines how much additional capital a bank must hold against climate-exposed assets. If the capital surcharge makes those assets uneconomic, the bank sells. The assets lose value, the industries dependent on them lose financing, and the communities dependent on those industries lose employment.
At no point in this chain did anyone vote for the outcome — the committee was not elected, the scenario was not debated in parliament, and the capital requirement was adopted through a technical standards process that most elected officials do not understand and most voters have never even heard of.
The mechanism applies well beyond fossil fuels. Any asset class can be stranded by the same process.
Agricultural land can be reclassified as ‘biodiversity-sensitive’.
Industrial plants can be reclassified as ‘emissions-intensive’.
Residential property can be reclassified as ‘lying within a projected flood plain’ — one that a ‘black box’ model predicts may flood in fifty or eighty years under a particular climate scenario, whether or not it floods today.
Consider what this means at the level of an individual household. If a model reclassifies a property as sitting within a future flood-risk zone, insurers withdraw coverage or price it beyond reach. Without insurance, mortgage lenders will not lend against the property. Without a mortgage market, the property cannot be sold at anything close to its previous value.
The area may never flood. But a parameter changed inside a model, and the financial system executed the consequence: the house is now effectively worthless on paper, the mortgage is underwater, and the owner’s principal asset has been stranded.
The same principle applies to the energy that heats the house. If a climate scenario reclassifies proven fossil fuel reserves as stranded assets, the capital required to extract them becomes prohibitive and the reserves remain in the ground — not because they are exhausted, but because a model determined they carry too much risk to finance. Supply declines whilst demand does not, and energy prices rise accordingly.
It applies equally to the factory where the homeowner works. If an industrial plant is reclassified as emissions-intensive under the same scenario framework, the cost of capital for that facility rises. If the surcharge makes continued operation uneconomic, the factory closes or relocates, and the homeowner loses employment because a model output changed a capital requirement that made the business unviable.
One parameter change in one model can strand a home, raise energy costs, and eliminate employment simultaneously. The homeowner experiences these as three separate misfortunes, but they originate from the same mechanism, applied through the same architecture, by the same upstream standard-setter.
This is anticipatory governance — regulation on the basis of modelled future outcomes rather than observed present conditions. The regulation does not respond to a harm that has occurred, but to a harm that a ‘black box’ model projects may occur under assumptions selected upstream. Those assumptions are not subject to challenge by the people whose assets are repriced as a result.
Crucially, anticipatory governance is self-executing. A weather forecast does not cause rain, but a flood-risk reclassification causes the asset to strand. The model does not predict that the house will lose value — it causes the house to lose value, by changing the parameter that determines whether the house can be insured and mortgaged. The template is universal: wherever a model output connects to a regulatory parameter, the same architecture applies, and the asset class is interchangeable.
It’s a general purpose mechanism for confiscating property.
Anticipatory governance has a sibling: indicator governance, in which society is managed through the continuous processing of real-time surveillance data. Where anticipatory governance regulates on the basis of a modelled future, indicator governance regulates on the basis of a processed present — surveillance data thresholds monitored in real time, with policy responses triggered automatically when an indicator crosses a line.
This already happened. During COVID-19, populations across the developed world were locked down, schools closed, businesses shuttered, and movement restricted when R numbers or case counts crossed thresholds set by modelling teams.
The thresholds were not debated in parliament before they took effect. The models that generated them were not subject to public consultation. No-one was held accountable after the fact. The data feeding them — PCR cycle thresholds, hospital admission coding, death certification criteria and other public health surveillance — were defined by technical committees whose assumptions were largely opaque to the public and to most elected representatives.
The mechanics were consistent across jurisdictions.
In the United Kingdom, the Scientific Advisory Group for Emergencies — SAGE — produced the modelling that determined when restrictions were imposed and lifted. Ministers announced the lockdowns, but the trigger points had already been determined by the models.
In Germany, the Robert Koch Institute performed the same function.
In the United States, the CDC’s modelling teams set the thresholds that governed school closures, business restrictions, and travel bans at the state level.
In each case, the standard-setter was a technical body with no electoral mandate, the clearinghouse was the emergency powers framework, and the population experienced the output as an inevitable response to objective reality rather than a policy choice embedded in a model’s assumptions.
While indicator governance changes the conditions of daily life overnight on the basis of a data feed processed in real time, anticipatory governance changes capital requirements over years on the basis of a modelled ‘black box’ scenario set decades ahead. Yet the architecture is the same — a model upstream, a clearinghouse in the middle, a population downstream — but the cycle time has expanded from hours to decades. And as we move from the current to a future prediction, precision almost certainly craters. Assets are stranded on account of guesswork, and little else, for which no-one is ever held accountable.
During COVID-19, indicator governance still required human teams to process the data and human officials to announce the restrictions. The UN Emergency Platform proposes to formalise this at the international level, doing away with both.
The Emergency Platform
In 2023, the United Nations Secretary-General proposed the Emergency Platform — a mechanism that would allow the UN to convene emergency responses to ‘complex global shocks’. Under the published proposal, a complex global shock — predicted by ‘black box’ modelling — triggers the emergency protocol.
Once activated, governance shifts from the normal deliberative process to centralised crisis management in the name of ‘protection’. The feedback loops that ordinarily constrain international decision-making — debate, amendment, ratification, national sovereignty — are suspended for the duration of the emergency.
But if the world is experiencing a ‘meta-crisis’ — as the claim now goes — the emergency never ends. Climate, biodiversity, and black-box-predicted pandemics all qualify as ‘complex global shocks’. The activation becomes permanent.
Governance by indicator, emergency authority, democratic feedback suspended — what COVID-19 demonstrated at the national level the Emergency Platform would establish as a permanent international mechanism.
The clearinghouse, in this form, intermediates between a model output and a governance response. The model declares the crisis. The platform activates the response. The parameters of both the model and the activation protocol were set before the emergency was declared, by whoever designed them. If the model determines when a crisis exists, and the protocol determines what happens when one is declared, then whoever designed both has pre-determined the governance outcome.
Whether a climate tipping point, a pandemic threshold, or a financial contagion event — the crisis need not be independently verified. It needs only to be modelled by a ‘black box’ with an accountability gap.
The Final Migration
The Emergency Platform still requires a human decision to activate it. Artificial intelligence removes this remaining constraint.
An AI system can ingest global surveillance data — epidemiological, environmental, financial, behavioural — assess it against predefined thresholds continuously, and trigger governance responses without human review at the point of activation. The standard-setter compiles the parameters, the AI processes the indicators, and the infrastructure downstream — whether a regulatory framework, an emergency protocol, or a programmable currency — executes the result.
The entire pipeline from surveillance data to governance outcome can operate at machine speed, with no democratic feedback at any stage.
This is the final stage of the migration. A cognitive tier sets the criteria. The AI occupies the evaluative tier — processing, assessing, judging. A behavioural tier executes the verdict. The population experiences only the output.
The clearinghouse that began as a named banker at a negotiating table has become an automated system that monitors and judges without human intervention at any point in the chain, whilst the infrastructure beneath it enforces the verdict at machine speed. Earlier stages of the migration relied on invisibility — the clearinghouse disappeared from view as it grew.
The final stage may not require invisibility at all. As we saw with the NGFS Kotz paper, a system that can describe its own architecture with perfect accuracy, and remain entirely unchanged by the description, does not need to hide.
The Pattern
The clearinghouse pattern is visible across every domain in which intermediation exists.
Credit rating agencies sit between borrowers and lenders. They do not lend money, but they compile the parameters — the credit ratings — that determine who can borrow and at what price. A sovereign downgrade reprices a country’s entire debt overnight.
The SWIFT messaging network sits between every bank that transfers money internationally. It does not hold funds; it routes messages. When a country is excluded from SWIFT, the clearing function becomes visibly geopolitical — the neutral intermediary revealed as a lever of control.
Academic peer review sits between researchers and publication. It does not conduct research, but it determines what qualifies as knowledge by defining the boundaries of acceptable methodology, evidence, and conclusion. Research that does not pass through the clearinghouse does not reach the public.
The Codex Alimentarius Commission sits between food producers and markets. It does not grow food, but it compiles the safety and quality standards that determine what can be sold and where. A farmer whose product fails a Codex-aligned standard experiences it as a market access problem — not as a decision made by a joint FAO/WHO committee in Rome.
Search engines and social media platforms sit between information and the public. They do not produce content, but they determine what is visible. When a platform suppresses, demotes, or labels content based on upstream policy guidelines, the user experiences an algorithmic outcome — not the editorial decision of a trust and safety team applying standards compiled elsewhere.
Every one of these clearing functions is migrating to AI — the human intermediary replaced by automated assessment operating at machine speed, applying standards compiled upstream, with no democratic feedback at the point of execution.
The same architecture governs democratic institutions directly.
At the United Nations, specialised agencies and technical committees draft frameworks over twenty-year horizons. The Secretariat administers them. The General Assembly votes on the resulting proposals piecemeal.
At the European Union, the structure is identical — technical bodies compile, the Commission proposes, and the Parliament votes — with one additional feature: only the Commission holds the right of legislative initiative. Members of the European Parliament cannot introduce legislation. They can only vote on what the Commission presents.
The parliament that ratified each component of a twenty-year plan, piece by piece across multiple electoral cycles, no longer exists by the time the plan reaches fruition. No single vote was the deciding moment, and no surviving parliament can be held accountable for the cumulative outcome.
The policy horizon exceeds the electoral horizon by design. When these functions migrate to AI — and indicator governance during COVID demonstrated the prototype — the electoral horizon becomes irrelevant entirely. The machine does not wait for a parliamentary term to expire. It processes, assesses, and executes continuously — especially once the UN Emergency Platform has come to pass.
In some cases, the same entity both compiles the standards and applies them. In others, the two functions have separated entirely. The power resides in the same place regardless: whoever defines the framework within which all subsequent decisions are made.
The architecture maps onto a three-tier structure that recurs across every governance system examined as of late on this substack. The financial industry has its own vocabulary for it: standards, clearing, settlement.
A cognitive tier compiles the standards — defining what is true, what constitutes risk, what qualifies as a crisis.
An evaluative tier assesses compliance and transmits the standards downward — the clearing function, whether it takes the form of a regulator, a rating agency, a protocol, or a programmable currency.
A behavioural tier executes — settlement: the banks that adjust their lending, the businesses that restructure, the populations that comply.
The evaluative tier rarely questions the cognitive tier; it applies what has been handed down. The behavioural tier rarely sees the cognitive tier at all. It experiences only the clearinghouse, and assumes the parameters it applies are neutral.
The standard-setter, the model architect, the unnamed committee — these occupy the cognitive position, and they are the one tier that is never visible.
And soon they will be the only tier that matters.
Conclusion
The clearinghouse function has migrated over two centuries from a named banker at a negotiating table to programmable conditions embedded in the money supply, applying to the sovereign state, the enterprise and the individual alike. At each stage, the scope has increased, the visibility has decreased, and the democratic accountability has diminished.
The conditions trace back to the Sustainable Development Goals, whose indicators — derived from global surveillance data — measure the state of each variable against a target boundary. Falling outside the boundary calls for correction. Refusing correction is labelled ‘unethical’ — and arguing against an ethic is harder than arguing against a regulation as we all experienced during Covid.
The modern clearinghouse requires an unnamed committee, a black-box model, an emergency activation protocol, and a programmable currency to execute its verdicts at the point of sale. The function is identical to the banker at the table — the architecture has simply become too large and too technical for the public to recognise it as the same thing.
But the next stage replaces the committee — COVID-era indicator governance, in which thresholds triggered policy in real time, is already giving way to anticipatory governance, in which the model acts before the threshold is crossed.
A cyberattack against the digital infrastructure on which anticipatory governance depends becomes an attack on governance itself — making the system’s self-preservation a qualifying emergency. And the multipolar world order provides the final justification: nation states acting alone cannot manage planetary-scale crises, so authority must transfer to international institutions that no electorate controls.
This was the express intent of Leonard Woolf’s 1916 Fabian report, International Government — the intellectual blueprint for the League of Nations. The emergency becomes permanent, and authority settles with the international institutions that were always intended to receive it.
Power thus centralises with the standard-setter — yet the standard-setter accepts no responsibility for the outcome.
The NGFS occupies a unique position in this architecture: it is the bridge between environmentalism and economics — the node where climate science becomes banking regulation, with Basel 3.1 setting the capital ratios, FATF enforcing compliance, with pre-emptively stranded assets being a direct outcome.
The NGFS scientific advisory committee, which validates the scenarios that calibrate your borrowing costs, has no published members, no terms of reference, and no public accountability. The architecture’s most consequential node is its least scrutinised.
The question is whether the entities that compile the parameters — the unnamed committees, the philanthropic funding loops, the model architects, the currency programmers — should be subject to the same democratic scrutiny as the institutions that enforce them, including accepting accountability when things go wrong.
Because at present, they are not.
Yet over the past decades, they have progressively reduced parliamentary democracy to kabuki theatre.
And whether there’s a legitimate reason is actually somewhat besides the point, because they never bothered to tell you they were doing it.
Extraordinary and clear, thank you. The only thing we can do is to say & show that “the science” underlying anticipatory governance is well thought out fraud.
The global climate boiling change nonsense, in which “carbon” is a pivotal factor, has absolutely no foundation whatsoever.
Unless you know this, everything downstream of algorithmic decision making at the level of the individual attempting a transaction, is irresistible, logical and “ethical”.
Another approach, which does not require the audience to be persuaded of multidecade, planned deception, is to invite the listener to step outside the entire framework. Are you really so sure that the future “crisis”, on the basis of which everything is decided by an AI platform applying algorithms, justifies the extent of extreme interference with routine activities which, taken together, constitutes ordinary life?
A reductio ad absurdam example might be the simple joy a driver or rider feels when they negotiate a particular bend under conditions in which the throttle response, chassis flex, the changing quality of the sounds and the resulting bodily sensations, that pastes a silly grin on your face. Supranational governance assesses your actions used 3% more “fossil fuel” than was objectively necessary to move your vehicle. The technical standard, ostensibly to save the polar bears, allows plus/minus 2% variance in “carbon output”. You’re either fined in one scenario or the control grid in another simply doesn’t allow said throttle opening. Is this dulling of every joy a strictly necessary thing? Obviously it’s not, but equivalent restrictions & obligations are forced on you at the level of the individual.
The claimed, assumed, implicit assumption is that the black box models that will have set every standard regulating your very existence are precisely correct. This is obviously not true.
I think most people are willing to accede to big picture regulations. We’ve accepted these pretty much forever. But few people have any conception yet about how crazily personal these restrictions and obligations are to become. The final control step into this matrix world is acceptance of updated in real time, biometric, digital ID, accompanied by elimination of all media of exchange except CBDC. At that point, the “totalitarian rheostat” governing your entire existence is in the hands of a remote, impenetrable system that you will never even know exists.
Your work is incredible, mate.