An investor places a trade. A voter changes preference. A patient accepts a treatment. A parent decides about a vaccine. Four decisions, made by four different people, in four different rooms, governed by the same multiplicative logic. If any one of the four constituting forces approaches zero, the decision collapses, regardless of how strong the other three are. The Human Decision-Making program is where the laws are tested back against the substrate they were first observed in.
The Human Decision-Making program is the substrate program that runs in reverse. The three laws emerged from operational observation of human decisions before any of the formal theory existed. This program is what tests the formal theory back against the substrate the theory came from, in the six contexts where human decisions have the deepest available empirical record.
The Mehrhoff Research Program was not born in a seminar room. It was born in operational financial services, watching identical institutional clients in different jurisdictions make divergent decisions about the same product. One client would proceed where another would balk, and the difference was not in the strength of the case for the product. The difference was in which single force, of four, happened to be approaching zero in their particular room on their particular day. The pattern became the formal multiplicative structure the Foundational program now develops.
The biological substrate is where the empirical record runs deepest. Decades of behavioural data in financial markets, electoral systems, public health, education, and clinical care provide the densest available test surface for the three laws. Each context the program covers carries its own canonical datasets and its own institutional consequences. The structure either accounts for them or it does not. There is no third option.
The relationship to the Foundational program is bidirectional. The Foundational program develops the laws abstractly. The Human Decision-Making program tests the laws empirically in the substrate the laws came from. Each finding either confirms the structural prediction, refines it under domain-specific conditions, or surfaces a counter-example the Foundational program then has to address. The traffic runs both ways. The work stays honest because of it.
Here are a selection of six contexts where human decisions are made at scale and where the empirical record is deepest. Six domains with different institutional structures, different timescales, different stakes. The laws hold across all six. The parameter values vary by context. The structural form does not.
Financial markets, asset allocation, and risk decisions across institutional and individual decision-makers. The context where the multiplicative pattern was first observed working, and where the structural form remains most extensively tested. The investor who decides under genuine uncertainty is the canonical case the rest of the program was built around.
Electoral dynamics, polarisation cascades, and political decision-making at scale. The context where the three UCT phases are most visible in real time, working across populations the same way they work across individuals, and where asymmetric reversibility is observable in the failure of cascades to reverse on the timescales their proponents expect.
Purchasing decisions, brand dynamics, and technology adoption across consumer markets. The context where the four-force structure governs the moment of purchase and the cascade governs how adoption spreads through populations. The marketing-science empirical record is the second-largest behavioural-data corpus available after financial markets, and the cascade dynamics in product success and failure are observable in real time.
Treatment choices, clinical decision-making, vaccination behaviour, and pharmacological combinations under uncertainty. The context where the four-force structure governs both the individual clinical decision and the population-level health outcome, with the cascade linking the two scales the same way it links them in financial markets and in elections. The pandemic decade made the cascade dynamics visible in real time across multiple jurisdictions.
Learning outcomes, curriculum effects, and educational decision-making across institutional and individual levels. The context where the meta-law (ISP) has its first practitioner-facing deployment surface, through the zero-shortcoming analogy framework that overturns forty years of accepted limits on what an analogy can transfer.
Hiring, promotion, performance evaluation, and managerial reasoning across labour markets and inside organisations. The context where the four-force structure governs the individual managerial decision and the cascade governs how organisational norms spread through cultures and across companies. The high-risk decision surface under every emerging AI-governance regime.
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Decision outcomes are governed by structural forces, not by stable attributes. The same multiplicative logic recurs at three scales and across domains.
Action under complexity is determined by the dynamic interaction of four forces. The interaction itself is the mechanism. Additive models systematically under-perform because they cannot represent it.
How individual decisions aggregate into institutional outcomes through three sequential phases. Ignition. Polarisation. Institutionalisation.
A criterion for when a structural pattern recurs across scales and domains. The pattern transfers only where structural identity holds.
Patrick Mehrhoff is a German entrepreneur, independent researcher, AI engineer, and author. He is the author of the three original theories that constitute the Mehrhoff Research Program. He built the work the studio carries.
Most practitioners spend a career inside one domain. He worked as a practitioner at six of the frontiers that redefined how society organises information, money, and value over the last two decades. The consumer internet, Swiss fintech, European monetary policy, Southeast Asian financial publishing, institutional crypto assets, and the first wave of applied AI.
The same structural observation appeared at every frontier. By 2019, on a whiteboard at crypto infrastructure provider Wyden in Zurich, the pattern had become visible to itself. It did not yet have a name. Four years before any AI language model became publicly available, the complete logic of the Three Laws of Decision-Making was already on the whiteboard.
The studio was built from Bangkok, without institutional affiliation and without external funding. The Rubens workshop model defines how it operates. The founder sets the intellectual direction at every decisive step. The tools and collaborators execute within it.
The first program states the architecture and demonstrates the laws that govern it. The second tests those laws against the empirical record of human decision-making. Together they establish the studio's canonical core and its first empirical substantiation. Further programs are in active preparation.
The three laws at the micro, macro, and meta scales, derived and stated formally. Plus the empirical evidence that the multiplicative architecture holds across biological, artificial, and hybrid substrates. Every paper in every other program traces its structural claims back to this canonical core.
Tested against nine foundational scholars, three of them Nobel laureates, and across fifteen structural dimensions. Every cell is independently challengeable.
Every dimension independently challengeable.
Most frequently cited as predecessors.
Among the nine scholars tested.
Confirmed across all nine scholars.
The three laws describe the same multiplicative structure that governs decisions across scales. What each audience recognises in them is different. Each doorway below opens into the same set of laws, framed for the way you are most likely to find your own work inside them.
The literature in your field has been reporting tail-failure for decades. Outliers, noise, model misspecification. The three laws name a different culprit. The structural form of the model itself. Read the laws and find the place where the assumption you never questioned has been doing the work all along.
Every senior decision-maker has watched a model work on average and break where the decision mattered. The three laws name what is happening. The breakage is not an edge case the model failed to anticipate. It is the multiplicative architecture finding its zero. Read the laws and the pattern beneath every model break of your career becomes legible at once.
Each major institutional cascade of the past fifteen years was investigated as if it were unique. The reports document different operational failures in different sectors. The three laws read across the reports and recognise one structural pattern. Read the laws and the recurrence stops looking like coincidence.
Every philosophical tradition that has tried to describe the world has eventually arrived at the same conclusion. The three laws turn the conclusion into a working structural explanation. Decisions form. They cascade. Their patterns transfer across scales. Read the laws the way our studio reads them.
Most foundational research is finished before a student arrives. The three laws sit early enough in their life that the field around them is still to being created. A graduate student who reads them now enters a body of work inside its formative window. The reading path is curated for entry from any quantitative or social-science background.
Universities train within additive frameworks. Journals review within them. Regulators write rules under them. Funders evaluate against them. The three laws name the structural assumption beneath the entire foundational layer. It has been invisible because no curriculum, no review, no framework has ever required it to be examined. Read the corpus and the link your institution has been operating without becomes legible.
The first sketch of the Three Universal Laws. Drawn four years before any AI language model became publicly available.
Sketched at an office in Zurich. The board maps the direction of the markets, the forces driving them, the audiences they affected, the problems those audiences encountered, and the responses the market was developing. The structural logic that became the First, Second, and Third Laws is already on the board, in the language of practice.
Mehrhoff Research operates outside academia and outside industry. An independent science and research studio with no external funding, no board, and no university partnership. Founded 2019 in Zurich, domiciled in Tallinn, run from Bangkok.
The work is published open access. Every paper passes adversarial peer review before deposit. Every claim names the empirical conditions under which it would be falsified. Every citation traces to a primary source. The standard is not the institution. The standard is the work.
Deposited on Zenodo, permanently archived.
Data points analysed across all empirical validations.
Foundational and human decision-making.
No paywall, no journal embargo.
A horizon decades away. The daily practice of moving toward it. Seven principles the studio holds itself to, with or without anyone looking. Five codes the studio answers to when no external authority requires them. Each statement enforced internally. Each verifiable from outside.
Vision and mission, stated directly. What the studio is working toward, and what it does today.
Seven standards held against every paper, every conversation, every relationship the studio enters. Decision-making, rigour, independence, transparency, originality, curiosity, and courage.
Self-regulated science. Published standards, open methods, full results regardless of what they show.
Press, academic peers, conference organisers, policy bodies, industry practitioners, and readers reach the studio here.
Six formats, from public keynote to closed doctoral seminar. The full range is welcome; the substance of the questions decides the invitation.
Four positions, from visiting researcher to fellowship, with two scheduled per calendar year. A residency produces sharper work than a single talk because the conversation extends.
Press kit with bios, headshots, and topic briefs is ready to download. Lectures, learning materials, and the architecture itself are licensable.