{ "schema": "org-writing@v1", "slug": "wise-workflows", "kg": { "id": "org:writing:wise-workflows", "type": "brick", "graph": "/kg.json" }, "title": "Wise workflows", "subtitle": "Design the workflow to be wise and no single part of it has to be", "abstract": "Why the buildable version of practical wisdom is a placement problem rather than a modeling problem, and the two questions that locate where a person belongs. The canonical treatment of wise workflows.", "kind": "brick", "topics": [ "Discernment", "Tacit knowledge" ], "courseMemberships": [ { "course": "org:courses:discernment", "topic": "Discernment", "wall": "org:walls:ethics", "position": 5, "total": 5 }, { "course": "org:courses:tacit", "topic": "Tacit knowledge", "wall": "org:walls:practice", "position": 6, "total": 6 } ], "publishedAt": "2026-08-03T00:00:00.000Z", "version": 2, "guidelinesVersion": 15, "brief": { "problem": { "text": "The stated goal is a wise agent, and the research money follows it, while the systems shipping today get placed at exactly the points where the missing capacity is the entire job.", "claims": [ "Artificial phronesis is a functionalist programme" ] }, "mechanism": { "text": "Wisdom is a property a workflow can hold without any single component holding it, so putting human judgment at the phases where the outcome turns on which rule applies buys the behavior the wise agent was supposed to supply.", "claims": [ "Simon divides decision-making into intelligence gathering, design, and choice" ] }, "move": { "text": "Walk the workflow, mark every point where the outcome turns on which rule applies rather than on what the rules are, and put a person there who carries the consequence.", "claims": [] } }, "sources": [ { "repo": "mnstry-strategy", "path": "docs/20-business/40-content/cathedral-of-the-mind/08-taxonomy-of-knowing.md" }, { "repo": "mnstry-strategy", "path": "docs/20-business/40-content/cathedral-of-the-mind/09-discernment-core-intelligence.md" } ], "canonicalPath": "/writing/wise-workflows/", "body": "There is a serious research programme aimed at building the wise machine outright. Artificial *phronesis*, associated most closely with the philosopher John Sullins, asks for systems whose outcomes a wise person would recognize as wise, and it is deliberately functionalist, requiring the outputs rather than an inner life behind them. It is honest work. It is also not what a team ships this quarter, and while it proceeds, systems with no capacity for the thing keep getting installed at the precise moments where the thing was the job.\n\nThe alternative is to move the wisdom up a level. Wisdom is a property a workflow can hold without any single component holding it, so putting human judgment at the phases where the outcome turns on which rule applies buys the behavior the wise agent was supposed to supply. Nothing in the workflow has to be wise, which is fortunate, because nothing in it is.\n\nHerbert Simon gave us the tool for finding those phases, and it has aged better than most things from the 1950s. He split decision-making into three. Gathering, scanning the environment for the conditions that call for a decision at all. Design, generating the possible courses of action. Choice, collapsing all that possibility into one committed act. Machine systems are extraordinary at the first two, which is exactly why they feel like they are doing the whole job, and the third phase is where discernment lives. The cognitive scientist John Vervaeke supplies the reason the third phase resists automation. Relevance is grounded in agency; an organism finds things relevant because it has something to lose, and a system with nothing to lose has no basis on which anything could matter to it, so it reproduces the relevance patterns in its training data rather than realizing relevance for itself.\n\nWell-placed, the arrangement produces results that are not modest. In the Swedish MASAI trial, reported in 2023, mammography screening supported by a detection model was compared against standard double reading by radiologists across a population screening programme. The machine sorted the reading queue. Radiologists kept the reading and kept the decision. Screen-reading workload fell by forty-four percent with cancer detection holding steady, which is what correct placement looks like when somebody measures it.\n\nThe older proof needs no machine at all. In 2009 a team led by Atul Gawande published the results of introducing a nineteen-item surgical safety checklist across eight hospitals in eight cities, from Seattle to Ifakara to Manila. Deaths fell from 1.5 percent to 0.8 percent and complications from 11 percent to 7 percent. A checklist has no wisdom in it whatsoever. It is a piece of laminated card. What it did was restructure the moments at which the surgical team's own judgment was forced to engage, and the workflow got wiser while every component stayed exactly as smart as it had been the week before.\n\nSo the discipline is placement, and it is decidable in an afternoon with two questions. Where in this workflow does the outcome turn on which rule applies, rather than on what the rules are? And at that point, who carries the consequence of being wrong? Wherever those two answers name different parties, the workflow has a hole in it, and no improvement in the model fills the hole. Note what does not count as placement. A person rubber-stamping a recommendation downstream is not at the choice point; they are a signature on somebody else's choice, which is the arrangement that produces alerts on eighteen percent of admitted patients and clinicians who learn to click through them.\n\nThis is not a hedge against capability improving, and it holds better as the models get better. Every improvement in gathering and design raises the stakes riding on the choice, so a system that improves at everything except judgment concentrates the judgment rather than dissolving it. Build for that concentration and you get the thing everyone actually wanted from the wise machine, arriving early, out of parts that were never wise, wherever somebody bothered to put a person where the weight falls.", "apparatus": { "note": "The human-facing essay is deliberately practical; this apparatus carries the full references, evidence-graded claims, article-local concepts, and research context behind it. Canonical concept definitions come from the concept registry.", "references": [ { "id": "org:references:wise-workflows:r01", "author": "John P. Sullins", "work": "Artificial Phronesis: What It Is and What It Is Not (in Science, Technology, and Virtues)", "relevance": "The programme the brick declines to build against and credits rather than dismisses. Sullins's definition is explicitly functionalist, asking for outcomes a wise agent would produce without requiring the machine to be wise." }, { "id": "org:references:wise-workflows:r02", "author": "Herbert A. Simon", "work": "Administrative Behavior and the bounded-rationality programme (intelligence, design, and choice as the phases of decision)", "relevance": "The placement tool. The three-phase split is what turns 'put the human where discernment is the work' from a slogan into a procedure you can walk a workflow with." }, { "id": "org:references:wise-workflows:r03", "author": "John Vervaeke", "work": "Relevance realization and the frame problem in 4E cognitive science", "relevance": "The reason the choice phase resists automation. Relevance is grounded in agency, so a system with nothing to lose reproduces relevance patterns rather than realizing relevance for itself." }, { "id": "org:references:wise-workflows:r04", "author": "Kristina Lång and colleagues", "work": "Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI), clinical safety analysis, The Lancet Oncology", "year": 2023, "relevance": "The modern case of correct placement. The model sorted the reading queue and radiologists retained the reading and the decision; the workload gain came without a detection loss." }, { "id": "org:references:wise-workflows:r05", "author": "Alex B. Haynes, Atul A. Gawande and colleagues", "work": "A Surgical Safety Checklist to Reduce Morbidity and Mortality in a Global Population (New England Journal of Medicine); the WHO Safe Surgery Saves Lives programme", "year": 2009, "relevance": "The proof that the mechanism predates machine intelligence entirely. A laminated card with no intelligence in it restructured the moments at which human judgment engaged, and the outcomes moved." } ], "claims": [ { "id": "org:claims:wise-workflows:c01", "claim": "Artificial phronesis is a functionalist programme, asking for outcomes that would be recognized as wise without requiring the machine to possess wisdom.", "basis": "Sullins's own definition of the field.", "confidence": "verified", "sources": [] }, { "id": "org:claims:wise-workflows:c02", "claim": "Simon divides decision-making into intelligence gathering, design, and choice, and current systems are strongest in the first two phases.", "basis": "Simon's published account of the decision phases; the capability characterization is the corpus's reading of current systems rather than a benchmark result.", "confidence": "verified", "sources": [] }, { "id": "org:claims:wise-workflows:c03", "claim": "In the MASAI trial's 2023 safety analysis, model-supported screen reading reduced radiologist screen-reading workload by 44 percent without a loss in cancer detection compared with standard double reading.", "basis": "Lång et al., The Lancet Oncology 2023, clinical safety analysis of a randomised, controlled, non-inferiority trial within the Swedish national screening programme. The larger detection-increase figures that circulate alongside this trial come from separate analyses and are deliberately not used here.", "confidence": "verified", "sources": [] }, { "id": "org:claims:wise-workflows:c04", "claim": "Introducing a nineteen-item surgical safety checklist across eight hospitals in eight cities was followed by a fall in death rate from 1.5 percent to 0.8 percent and in complications from 11 percent to 7 percent.", "basis": "Haynes et al., NEJM 2009; 3,733 patients before and 3,955 after introduction. A prospective before-and-after comparison rather than a randomised trial, which is the study's own stated design.", "confidence": "verified", "sources": [] }, { "id": "org:claims:wise-workflows:c05", "claim": "Relevance is grounded in agency, so a system with nothing at stake mimics relevance patterns from its training data rather than realizing relevance for itself.", "basis": "Vervaeke's relevance-realization argument. A theoretical position in cognitive science with substantial support and live opposition, not a measured finding.", "confidence": "directional", "sources": [] } ], "concepts": [ { "id": "org:concepts:phronesis", "name": "Phronesis", "definition": "Practical wisdom. The capacity to deliberate well about what is good in a particular situation and to act on the deliberation, distinguished in Aristotle's taxonomy from technical skill and from theoretical knowledge. It works through the minor premise, the perception that this situation falls under that rule, and it is inseparable from character, which is why it cannot be supplied by constraint from outside.", "provenance": "canonical" }, { "id": "org:concepts:the-stake-condition", "name": "The stake condition", "definition": "Judgment requires something at risk in the outcome. A system that cannot be harmed by being wrong, cannot be shamed by it, and does not persist through the consequence has no ground on which to weigh what is good. The condition is what the top of the data-to-wisdom hierarchy is actually made of, and it is not reachable by accumulating more of the level below it.", "provenance": "canonical" }, { "id": "org:concepts:wise-workflows", "name": "Wise workflows", "definition": "Designing the workflow rather than the agent to be wise, so that no single component has to hold a capacity none of them has. Human judgment is placed at the phases where the outcome turns on which rule applies rather than on what the rules are, and at those points the person placed there carries the consequence of being wrong. A signature downstream of a recommendation is not placement.", "provenance": "canonical" }, { "name": "The placement questions", "definition": "Where does the outcome turn on which rule applies rather than on what the rules are, and who carries the consequence of being wrong there? Where the two answers name different parties, the workflow has a hole.", "provenance": "local" } ], "researchContext": "Extracted from \"Discernment\" (essay parent), which closes on the placement\nargument in a paragraph. The brick is its canonical home and supplies what the\nessay had no room for: the two cases, the two placement questions stated as a\nprocedure, and the explicit disqualification of downstream rubber-stamping as\nplacement.\n\nThe Sullins programme is credited and not disparaged. The corpus does not build\nagainst it, and the brick says why in the text rather than implying a verdict\non whether it can succeed.\n\nTwo evidence notes. The MASAI figures are taken only from the 2023 clinical\nsafety analysis in The Lancet Oncology; larger cancer-detection percentages\nattached to this trial in press coverage come from separate analyses with\ndifferent endpoints, and mixing them would inflate the case. The surgical\nchecklist study is a prospective before-and-after comparison across eight sites\nrather than a randomised trial, and the apparatus records that limitation\nbecause the brick leans on the result.\n\nBoundary with \"Structural, not behavioral\" and with the threshold bricks: those\nargue where a system belongs relative to the agency line. This one argues where\na person belongs relative to the decision, which is a different placement\nquestion, and the two are compatible by construction." }, "contract": "https://mnstry.org/contracts/org/org-writing.v1.schema.json", "releaseHash": "f1209dc261b77ec280864b5db4d135e43d46b18662f6ea295750a8fd1988a0f5", "versions": [ { "version": 2, "cutAt": "2026-08-11", "note": "Tacit remainder demotion release: Tacit Knowledge course projection updated.", "visibility": "published", "path": "/writing/wise-workflows/", "contentHash": "sha256:dc4e86c1ab29141b", "releaseHash": "f1209dc261b77ec280864b5db4d135e43d46b18662f6ea295750a8fd1988a0f5" }, { "version": 1, "cutAt": "2026-08-03", "note": "Initial publication, discernment wave", "visibility": "published", "path": "/writing/wise-workflows/v/1/", "contentHash": "sha256:dc4e86c1ab29141b" } ] }