The HumanAI and OrgAI Framework Calculator, version 1.2.0

Version 1.2.0 of the Human^AI and Org^AI Framework Calculator is publicly available at no cost. It is a single HTML file that runs entirely in the browser: no installation, no account, and no network request of any kind. It opens unchanged on a machine with no internet connection.

The instrument accompanies the whitepaper “Human^AI and Org^AI: A Relational Framework for AI-Mediated Human and Organizational Capacity”, and turns the relationships defined there into an assessment record you complete for a concrete situation: one process, one team, one observation period.

The problem it addresses

Every organisation that has introduced AI into a process eventually faces the same question: does it work?

The usual answer rests on two observations: people are visibly faster, and nobody has complained. Both may be true. Neither answers the question.

The difficulty is that “does it work” conflates things that must be measured separately: what the system can produce, what the accountable person can validate, who is authorised to decide, and what happens to a wrong conclusion once it enters the workflow. The framework separates them. The calculator makes them computable.

The central distinction is epistemic decoupling: the gap between the range of answers AI makes accessible and the demonstrated capacity of the accountable actor to validate them. When access grows faster than validation, an organisation produces claims it cannot support, and then reuses them.

What it looks like

Eight modules and a diagnostic panel. The modules are a sequence rather than a menu: module 02 consumes the result of 01, module 06 depends on 03, and the classification worksheet can stop everything else if the situation does not belong to the construct.

Module	What it establishes
00. Classification	Whether the situation is a HumanAI case, through a ten-question membership test
01. Epistemic decoupling	The gap between access and validation, with a confidence interval
02. Propagation exposure	How an unvalidated error is amplified by reuse, now and after declared controls
03. OrgAI threshold	Whether the six constitutive conditions are demonstrated or merely declared
04. Contribution profile	On which dimensions AI changes the outcome, in which direction, and what is lost
05. Synergy test	Whether the result exceeds the relevant comparators with declared risk thresholds satisfied
06. Maturity	The M0 to M5 level for each bounded domain separately
07. OrgAI profile	What the organisational architecture actually produces, not merely that it exists

What changed since version 1.0.0

This release began from an uncomfortable finding: in four places, the calculator contradicted its own whitepaper.

• Material contribution was evaluated on a single dimension chosen from a dropdown, although the whitepaper defines a seven-dimension profile and explicitly forbids compressing it into a score.
• The exported record carried none of the seven fields of the minimum reporting convention, and so was not citable under the framework’s own rule.
• Access and validation were entered as slider values, although they are proportions over a declared task set, which manufactured an apparent precision with nothing behind it.
• Validated organisational learning appeared disconnected from the architecture it belongs to.

All four are fixed. No formula defined in the whitepaper was altered, and the six assertions of the original test suite pass unchanged.

On top of the repairs, the missing constructs were added: the classification worksheet, an evidence reference for every organisational condition, exposure compared before and after controls, the nine-dimension organisational profile, maturity assessed per domain, the anti-pattern detector, and a JSON schema that can be re-imported.

Three things worth seeing

A profile, not a score

In the example above, AI made security alert triage significantly faster and moderately better. At the same time, confidence calibration, analyst autonomy and risk exposure all worsened, each beyond the declared threshold.

A composite score would have summed the five values and reported a gain. The result would have been technically correct and entirely misleading: part of the speed came from reduced validation. The instrument refuses to produce that number, not because of a technical constraint, but because the whitepaper forbids compressing the profile, and a single score hides exactly the trade-off that matters.

A number without a volume says nothing

Access and validation are entered as counts, how many tasks out of how many, not as estimated percentages. The counts produce a confidence interval, and when that interval includes zero the instrument says “not demonstrated at this task volume”, not “no gap”.

A larger gap, poorly measured, supports less than a smaller one measured well. The instrument does not hide that difference behind the same two-decimal number.

A claim is not evidence

Each of the six organisational conditions requires an evidence reference and its type, not a checkbox. A condition marked “demonstrated” without a reference appears as declared, undocumented, and does not count towards the threshold. The counter becomes a pair, declared and documented, and the difference between the two numbers shows the distance between what an organisation believes about itself and what it can show.

Across all modules runs a detector that reads the configuration as a whole and looks for contradictions between what was declared in one place and what was measured in another. It is the only component that tells the assessor something they did not know on the way in.

Properties

Property	State
Installation	None. One HTML file opened in any modern browser
Network requests	None. Fonts are embedded; it works on an isolated network
Browser persistence	None. No localStorage, no cookies
Account, database, analytics	None exist
Security policy	Restrictive CSP in the self-hosted variant, with connect-src “none”
Verification	29 automated tests that extract the logic from the delivered file

The last line deserves an explanation. The tests do not hold a copy of the formulas: they extract them from the shipped file, between two markers in the code. A passing run is a statement about the file in your hand, not about a laboratory version.

Where to get it

The instrument is deposited on Zenodo with a citable DOI: 10.5281/zenodo.22884721, version 1.2.0. The record contains the source archive and the ready-to-use index.html. No unpacking is needed: the file opens directly in the browser.

The canonical whitepaper: 10.5281/zenodo.22295278.

The code is licensed under MIT, © 2026 S.C. PRODEFENCE S.R.L. The conceptual framework, the definitions and the interpretive text remain under CC BY-ND 4.0, as published in the whitepaper. In practice: the code may be reused freely, but the definitions and thresholds may not be republished in modified form under the names Human^AI or Org^AI. When you rely on the definitions or on the interpretation of the framework, cite both.

Limits

• Results are interpretive. They do not constitute empirical validation, certification, legal advice or a compliance determination.
• The instrument verifies nothing: every value remains a claim by the assessor until it is tied to the evidence it points to.
• The propagation indicator is conceptual; without local calibration it does not estimate real probabilities.
• Thresholds are declared by the user, according to domain and risk.
• The instrument cannot be the sole basis of a consequential decision.

The last two remain permanently visible in the interface, not only in the documentation.

Further reading

The framework behind the instrument, with its definitions, the constitutive threshold and the threat model, is explained in the article “Human^AI and Org^AI: what capacity has the organisation built”, which we publish on 25 September. A screen-by-screen walk through the modules follows in the guided tour of the calculator, published on 27 September.

Frequently asked questions

The framework, the definitions, the variables, the formulas and the interpretive model were developed by Alexandru Angheluș, an independent and self-funded author. Artificial intelligence and automation tools were used selectively for software development, structural organisation, drafting and verification activities. Responsibility for the conceptual model and for the software remains entirely with the author.