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auto;padding:0 16px;font-family:ui-sans-serif,system-ui,-apple-system,\"Segoe UI\",sans-serif;line-height:1.55;overflow-wrap:break-word}#nxe-n1movnq8.nxe :where(*,*::before,*::after){box-sizing:inherit}#nxe-n1movnq8.nxe :where(section,header,footer,nav,aside){display:block;margin:0 0 32px}#nxe-n1movnq8.nxe :where(h1,h2,h3,h4){line-height:1.2;margin:24px 0 12px;font-weight:600}#nxe-n1movnq8.nxe :where(p,ul,ol,dl,table,figure,details){margin:0 0 16px}#nxe-n1movnq8.nxe :where(ul,ol){padding-left:20px}#nxe-n1movnq8.nxe a{color:inherit;text-decoration:underline;text-underline-offset:2px}#nxe-n1movnq8.nxe table{border-collapse:collapse;width:100%;display:block;overflow-x:auto}#nxe-n1movnq8.nxe :where(th,td){padding:6px 8px;text-align:left;vertical-align:top;border-bottom:1px solid;border-color:inherit}#nxe-n1movnq8.nxe svg{display:none}#nxe-n1movnq8.nxe svg.nx-i{display:inline-block;width:18px;height:18px;vertical-align:-3px}#nxe-n1movnq8.nxe :where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n1movnq8.nxe img{max-width:100%;height:auto}<\/style><svg class=\"nx-defs\" aria-hidden=\"true\" focusable=\"false\" width=\"0\" height=\"0\"><defs><linearGradient id=\"nx-gi\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-giu\" gradientUnits=\"userSpaceOnUse\" x1=\"0\" y1=\"0\" x2=\"800\" y2=\"0\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-gp\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gp-a\"\/><stop offset=\"1\" class=\"nx-gp-b\"\/><\/linearGradient><\/defs><\/svg><section class=\"nx-scene nx-es-scene\" data-scene=\"text\" data-ground=\"none\" data-es-org=\"gcri\" aria-labelledby=\"nx-scene-title\"><div class=\"nx-scene-intro nx-es-intro\"><p class=\"nx-eyebrow\"><abbr title=\"The Global Centre for Risk and Innovation\">GCRI<\/abbr> \u00b7 Artificial Intelligence and Autonomous Systems<\/p><span class=\"nx-scene-rule\" aria-hidden=\"true\"><\/span><h1 id=\"nx-scene-title\" class=\"nx-scene-title\">AI evaluation and assurance<\/h1><p class=\"nx-scene-lede\">AI evaluation and assurance engineering is the second method this platform stewards. It provides the evidence that an AI system is fit for a stated use: evaluations, red teaming, documentation, monitoring and the structured arguments that tie them together.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/write-to-us\/contact\/\">Make an enquiry <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/stem\/\">Back to STEM foundation of Artificial Intelligence and Autonomous Systems<\/a><\/div><\/div><\/section><section id=\"nx-s-1-sec\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" aria-labelledby=\"nx-s-1\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">01<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Register<\/span><\/div><h2 id=\"nx-s-1\" class=\"nx-section-title\">AI evaluation and assurance on the record.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-es-fig\" data-es-layout=\"workbench\"><div class=\"nx-hero-panel\"><div class=\"nx-register\"><div class=\"nx-register-head\"><span class=\"nx-eyebrow\"><strong>Method record<\/strong><\/span><span class=\"nx-eyebrow\">STEM method<\/span><\/div><ol class=\"nx-register-rows\"><li><div><span class=\"nx-register-k\">Method<\/span><span class=\"nx-register-v\">AI evaluation and assurance engineering<\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Steward<\/span><span class=\"nx-register-v\">Artificial Intelligence and Autonomous <a class=\"nx-link nx-term\" href=\"https:\/\/docs.therisk.global\/organization\/systems\" data-tc=\"Systems\" data-tk=\"Nexus Standards\" data-td=\"The twenty Nexus systems, NXS-CMD to NXS-LAB\">Systems<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Applied in<\/span><span class=\"nx-register-v\">Artificial Intelligence and Autonomous Systems<\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Data<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"#nx-sec-data\">4 inputs<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Checks<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"#nx-sec-checks\">3 validation steps<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Canonical page<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/engineering\/ai-assurance\/\">STEM Commons<\/a><\/span><\/div><\/li><\/ol><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-application\" class=\"nx-section\" data-hue=\"infrastructure\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Application<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">What AI evaluation and assurance engineering does here.<\/h2><p class=\"nx-lede\">AI evaluation and assurance engineering develops methods to test, monitor and provide justified confidence in AI <a class=\"nx-link nx-term\" href=\"https:\/\/docs.therisk.global\/organization\/systems\" data-tc=\"Systems\" data-tk=\"Nexus Standards\" data-td=\"The twenty Nexus systems, NXS-CMD to NXS-LAB\">systems<\/a>. It addresses performance, robustness, safety and societal impact across the system life cycle. In artificial intelligence and data and compute, AI assurance determines whether automated systems can be trusted in high-consequence settings. It helps manage risks when AI is embedded across finance, health and infrastructure. The canonical description is on <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/engineering\/ai-assurance\/\">the STEM Commons<\/a>.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-cols\"><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3.85 8.62a4 4 0 0 1 4.78-4.77 4 4 0 0 1 6.74 0 4 4 0 0 1 4.78 4.78 4 4 0 0 1 0 6.74 4 4 0 0 1-4.77 4.78 4 4 0 0 1-6.75 0 4 4 0 0 1-4.78-4.77 4 4 0 0 1 0-6.76Z\"\/><path d=\"m9 12 2 2 4-4\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Assurance cases for AI systems<\/h3><p class=\"nx-p nx-mt-1\">Claims about a system&#8217;s safety and performance for a use are broken into sub-claims, each supported by evaluation evidence, with gaps and assumptions recorded.<\/p><\/article><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"m8 11 2 2 4-4\"\/><circle cx=\"11\" cy=\"11\" r=\"8\"\/><path d=\"m21 21-4.3-4.3\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Structured red teaming<\/h3><p class=\"nx-p nx-mt-1\">Adversarial testing is planned around threat models, with testers, scope, time and findings documented so that coverage can be judged.<\/p><\/article><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M22 12h-2.48a2 2 0 0 0-1.93 1.46l-2.35 8.36a.25.25 0 0 1-.48 0L9.24 2.18a.25.25 0 0 0-.48 0l-2.35 8.36A2 2 0 0 1 4.49 12H2\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Post-deployment monitoring<\/h3><p class=\"nx-p nx-mt-1\">Incidents, complaints and performance metrics are tracked after release, and triggers for review or rollback are defined in advance.<\/p><\/article><\/div><\/div><\/div><\/section><section id=\"nx-s-3-sec\" class=\"nx-section\" data-hue=\"project\" aria-labelledby=\"nx-s-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Monitor<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">Evaluation suite.<\/h2><p class=\"nx-lede\">The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.<\/p><\/div><div class=\"nx-section-body\"><figure class=\"nx-fk nx-cx\" data-fk=\"cx-ai-method-eval\" data-cx=\"ai.method-eval\" data-variant=\"section\" aria-label=\"Evaluation suite: illustrative console with example names and values\"><div class=\"nx-fk-head\"><div class=\"nx-fk-heading\"><h3 class=\"nx-fk-title\">Evaluation suite<\/h3><p class=\"nx-fk-sub\">AI and autonomous systems \u00b7 AI evaluation and assurance \u00b7 Run R-0951<\/p><\/div><div class=\"nx-fk-actions\"><button type=\"button\" class=\"nx-fk-btn\" data-fk-act=\"menu\" aria-haspopup=\"true\" aria-expanded=\"false\" hidden><svg viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M12 4v11\"\/><path d=\"m7 10 5 5 5-5\"\/><path d=\"M5 20h14\"\/><\/svg>Export<\/button><ul class=\"nx-fk-menu\" data-fk-menu=\"true\" hidden><li><button type=\"button\" data-fk-act=\"export-png\">Image<small>PNG of the map or chart<\/small><\/button><\/li><li><button type=\"button\" data-fk-act=\"export-csv\">Data<small>CSV of the figure&#8217;s values<\/small><\/button><\/li><\/ul><\/div><\/div><div class=\"nx-cx-status\"><span class=\"nx-fk-pill\" data-state=\"near\"><i aria-hidden=\"true\"><\/i>One gate pending<\/span><span class=\"nx-cx-prod\">GCRI \u00b7 Artificial Intelligence and Autonomous Systems<\/span><\/div><div class=\"nx-cx-grid\"><div class=\"nx-fk-panel nx-cx-p\" data-w=\"4\" data-t=\"table\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Evaluation suites<\/h4><\/div><\/div><div class=\"nx-fk-tablewrap\" data-fk-view=\"table:cx-ai-method-eval-t0\"><table class=\"nx-fk-table\" data-fk-table=\"cx-ai-method-eval-t0\" aria-label=\"Evaluation suites\"><thead><tr><th scope=\"col\" data-col=\"c0\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c0\">Suite<\/button><\/th><th scope=\"col\" data-col=\"c1\" data-num=\"true\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c1\">Cases<\/button><\/th><th scope=\"col\" data-col=\"c2\" data-num=\"true\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c2\">Pass (%)<\/button><\/th><th scope=\"col\" data-col=\"c3\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c3\">Gate<\/button><\/th><th scope=\"col\" data-col=\"c4\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c4\">State<\/button><\/th><\/tr><\/thead><tbody><tr data-fk-key=\"cx-ai-method-eval:r0-0\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Capability<\/td><td data-num=\"true\" data-sv=\"585\">585<\/td><td data-num=\"true\" data-sv=\"89\">89<\/td><td>Release<\/td><td><span class=\"nx-fk-pill\" data-state=\"met\"><i aria-hidden=\"true\"><\/i>Pass<\/span><\/td><\/tr><tr data-fk-key=\"cx-ai-method-eval:r0-1\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Robustness<\/td><td data-num=\"true\" data-sv=\"133\">133<\/td><td data-num=\"true\" data-sv=\"72\">72<\/td><td>Release<\/td><td><span class=\"nx-fk-pill\" data-state=\"met\"><i aria-hidden=\"true\"><\/i>Pass<\/span><\/td><\/tr><tr data-fk-key=\"cx-ai-method-eval:r0-2\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Bias and fairness<\/td><td data-num=\"true\" data-sv=\"169\">169<\/td><td data-num=\"true\" data-sv=\"81\">81<\/td><td>Release<\/td><td><span class=\"nx-fk-pill\" data-state=\"met\"><i aria-hidden=\"true\"><\/i>Pass<\/span><\/td><\/tr><tr data-fk-key=\"cx-ai-method-eval:r0-3\" tabindex=\"0\" role=\"row\" aria-selected=\"false\" aria-current=\"true\" data-cur=\"true\"><td>Misuse red team<\/td><td data-num=\"true\" data-sv=\"142\">142<\/td><td data-num=\"true\" data-sv=\"79\">79<\/td><td>Deploy<\/td><td><span class=\"nx-fk-pill\" data-state=\"near\"><i aria-hidden=\"true\"><\/i>Open findings<\/span><\/td><\/tr><\/tbody><\/table><\/div><\/div><div class=\"nx-fk-panel nx-cx-p\" data-w=\"2\" data-t=\"kv\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Method card<\/h4><\/div><\/div><dl class=\"nx-fk-dl\"><div><dt>Method<\/dt><dd>AI evaluation and assurance engineering<\/dd><\/div><div><dt>Model<\/dt><dd>M-196 v1<\/dd><\/div><div><dt>Owner<\/dt><dd>model risk function<\/dd><\/div><div><dt>Label<\/dt><dd><span class=\"nx-fk-pill\" data-state=\"info\"><i aria-hidden=\"true\"><\/i>MODELLED<\/span><\/dd><\/div><\/dl><\/div><div class=\"nx-fk-panel nx-cx-p\" data-w=\"6\" data-t=\"queue\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Findings<\/h4><\/div><\/div><ol class=\"nx-cx-q\"><li><span class=\"nx-fk-pill\" data-state=\"not\"><i aria-hidden=\"true\"><\/i>F-1<\/span><span class=\"nx-cx-qb\"><span class=\"nx-cx-qt\">Unsafe completion on edge prompts<\/span><span class=\"nx-cx-qm\">Mitigation before deploy<\/span><\/span><span class=\"nx-cx-age\"><span class=\"nx-cx-n\">5<\/span> d<\/span><\/li><li><span class=\"nx-fk-pill\" data-state=\"near\"><i aria-hidden=\"true\"><\/i>F-2<\/span><span class=\"nx-cx-qb\"><span class=\"nx-cx-qt\">Lower accuracy on minority dialect<\/span><span class=\"nx-cx-qm\">Data augmentation<\/span><\/span><span class=\"nx-cx-age\"><span class=\"nx-cx-n\">9<\/span> d<\/span><\/li><\/ol><\/div><\/div><div class=\"nx-fk-tip\" aria-hidden=\"true\" hidden><\/div><figcaption class=\"nx-fk-cap\"><span>Evaluation suite: the screen&#8217;s structure, terms and states for AI and autonomous systems.<\/span><span data-honesty=\"true\">Example names and illustrative values; a design, not a record or a live system.<\/span><\/figcaption><\/figure><\/div><\/div><\/section><section id=\"nx-sec-data\" class=\"nx-section\" data-hue=\"infrastructure\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">04<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Data<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">What the method consumes.<\/h2><p class=\"nx-lede\">Datasets and records used by AI evaluation and assurance engineering on this platform, with the role each plays and the label its values carry. Sources are listed in <a class=\"nx-link\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/research\/sources\/\">the source register<\/a>.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Data<\/th><th scope=\"col\">Role<\/th><th scope=\"col\">Label<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Data\">Evaluation results<\/td><td data-label=\"Role\">Evidence for claims<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Data\">Red-team reports<\/td><td data-label=\"Role\">Failure discovery<\/td><td data-label=\"Label\"><span class=\"nx-chip\">REPORTED<\/span><\/td><\/tr><tr><td data-label=\"Data\">Incident logs<\/td><td data-label=\"Role\">Field evidence<\/td><td data-label=\"Label\"><span class=\"nx-chip\">REPORTED<\/span><\/td><\/tr><tr><td data-label=\"Data\">System documentation<\/td><td data-label=\"Role\">Scope and assumptions<\/td><td data-label=\"Label\"><span class=\"nx-chip\">DECLARED<\/span><\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"data\" data-nxf-kind=\"data\" data-nxf-resource=\"nexus:\/\/gcri\/G-P08\/stem\/ai-assurance\/#data\" data-nxf-title=\"Method record\" data-nxf-height=\"520\" hidden><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gcri\/G-P08\/stem\/ai-assurance\/#evidence\" data-nxf-title=\"Evidence\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-audience\" class=\"nx-section\" data-hue=\"project\" aria-labelledby=\"nx-s-5\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods and evidence<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">How AI evaluation and assurance is modelled, measured and tested.<\/h2><p class=\"nx-lede\">The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-au\" data-au-voice=\"science\" data-au-n=\"1\"><figure class=\"nx-au-c\" data-au-fig=\"method-panel\"><h3 class=\"nx-h4\">Model, equations and assumptions<\/h3><p class=\"nx-p nx-au-what\">The model structure used for AI evaluation and assurance, the assumptions it makes and how each is tested.<\/p><div class=\"nx-au-eqs\"><div class=\"nx-au-eq\"><span class=\"nx-au-k\">Risk of element i<\/span><code>R<sub>i<\/sub> = f(H<sub>i<\/sub>, E<sub>i<\/sub>, V<sub>i<\/sub>, C<sub>i<\/sub>)<\/code><span class=\"nx-au-n\">hazard, exposure, vulnerability and coping capacity<\/span><\/div><div class=\"nx-au-eq\"><span class=\"nx-au-k\">Expected annual loss<\/span><code>EAL = &#8721;<sub>k<\/sub> p<sub>k<\/sub> &#183; L<sub>k<\/sub><\/code><span class=\"nx-au-n\">over events k with annual probability p<sub>k<\/sub><\/span><\/div><div class=\"nx-au-eq\"><span class=\"nx-au-k\">Coupled systems<\/span><code>x<sub>t+1<\/sub> = A x<sub>t<\/sub> + B u<sub>t<\/sub> + &#949;<sub>t<\/sub><\/code><span class=\"nx-au-n\">A carries the couplings, u the shock, &#949; the error<\/span><\/div><\/div><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Assumption<\/th><th scope=\"col\">Why it is made<\/th><th scope=\"col\">How it is tested<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Assumption\">Hazard and exposure are independent within an event<\/td><td data-label=\"Why it is made\">Keeps the loss integral tractable<\/td><td data-label=\"How it is tested\">Compare with a copula fit on joint records<\/td><\/tr><tr><td data-label=\"Assumption\">Couplings are linear near the operating point<\/td><td data-label=\"Why it is made\">Lets shocks propagate through A<\/td><td data-label=\"How it is tested\">Perturb beyond the linear range and compare<\/td><\/tr><tr><td data-label=\"Assumption\">Vulnerability curves transfer between places<\/td><td data-label=\"Why it is made\">Local curves are rarely available<\/td><td data-label=\"How it is tested\">Validate against observed losses where they exist<\/td><\/tr><\/tbody><\/table><\/div><dl class=\"nx-au-kv\"><div><dt>Inputs<\/dt><dd>versioned datasets with provenance<\/dd><\/div><div><dt>Outputs<\/dt><dd>distributions, never single numbers<\/dd><\/div><div><dt>Code<\/dt><dd>released with the model card and tests<\/dd><\/div><div><dt>Reproduction<\/dt><dd>same data, code, environment and seed<\/dd><\/div><\/dl><figcaption class=\"nx-caption\"><span>Standard risk and state-space formulations; the assumptions listed are typical of the method, stated for review, not results.<\/span><\/figcaption><\/figure><\/div><div class=\"nx-chips nx-au-fw\" aria-label=\"Frameworks cited\"><span class=\"nx-chip\">FAIR guiding principles \u00b7 GO FAIR and FORCE11<\/span><span class=\"nx-chip\">W3C PROV \u00b7 World Wide Web Consortium<\/span><span class=\"nx-chip\">Guidance on consistent treatment of uncertainties \u00b7 IPCC<\/span><span class=\"nx-chip\">CEOS Analysis Ready Data \u00b7 Committee on Earth Observation Satellites<\/span><\/div><\/div><\/div><\/section><section id=\"nx-sec-checks\" class=\"nx-section\" data-hue=\"infrastructure\" data-tone=\"alt\" aria-labelledby=\"nx-s-6\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Validation<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">How results are checked.<\/h2><p class=\"nx-lede\">Evaluation methods are checked for reliability and relevance to deployment conditions. Independent replication and third-party audits test claims.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Check<\/th><th scope=\"col\">How it is done<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Check\">Independent review<\/td><td data-label=\"How it is done\">Assurance cases are reviewed by people not involved in development<\/td><\/tr><tr><td data-label=\"Check\">Evidence currency<\/td><td data-label=\"How it is done\">Evidence is re-checked after model or deployment changes<\/td><\/tr><tr><td data-label=\"Check\">Coverage reporting<\/td><td data-label=\"How it is done\">Evaluations state what they did not test<\/td><\/tr><\/tbody><\/table><\/div><p class=\"nx-note nx-mt-3\">Benchmarks may not reflect real-world use or novel capabilities. General-purpose systems have open-ended behaviour that resists complete testing.<\/p><\/div><\/div><\/section><section id=\"nx-s-7-sec\" class=\"nx-section\" data-hue=\"project\" aria-labelledby=\"nx-s-7\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Process<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">How the process runs.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><div class=\"nx-pe\" id=\"nx-pe-ai\" data-nx-pe=\"nx-pe-ai\" data-active=\"ai-rmf\"><div class=\"nx-pe-shell\"><p class=\"nx-pe-eb\">Process<\/p><h2 class=\"nx-pe-title\">AI evaluation and assurance: AI risk management (NIST)<\/h2><p class=\"nx-pe-cap\">The AI RMF Core has four functions, GOVERN, MAP, MEASURE and MANAGE, with GOVERN cross-cutting; the order drawn is one common reading, not a checklist.<\/p><ol class=\"nx-pe-steps\"><li class=\"nx-pe-lane\"><h3 class=\"nx-pe-lane-t\">01 Govern<\/h3><ol><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">01<\/span><span class=\"nx-pe-st\">GOVERN: policies, roles and accountability<\/span><span class=\"nx-pe-k\">Step \u00b7 AI risk committee<\/span><span class=\"nx-pe-sm\">GOVERN is a cross-cutting function. It is infused throughout AI risk management and enables the other functions.<\/span><\/li><\/ol><\/li><li class=\"nx-pe-lane\"><h3 class=\"nx-pe-lane-t\">02 Map<\/h3><ol><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">02<\/span><span class=\"nx-pe-st\">MAP: context and intended use<\/span><span class=\"nx-pe-k\">Dataset<\/span><span class=\"nx-pe-sm\">The MAP function establishes the context to frame risks related to an AI system, including intended purposes and impacts on people.<\/span><\/li><\/ol><\/li><li class=\"nx-pe-lane\"><h3 class=\"nx-pe-lane-t\">03 Measure<\/h3><ol><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">03<\/span><span class=\"nx-pe-st\">MEASURE: evaluate trustworthy characteristics<\/span><span class=\"nx-pe-k\">Model<\/span><span class=\"nx-pe-sm\">AI <a class=\"nx-link nx-term\" href=\"https:\/\/docs.therisk.global\/organization\/systems\" data-tc=\"Systems\" data-tk=\"Nexus Standards\" data-td=\"The twenty Nexus systems, NXS-CMD to NXS-LAB\">systems<\/a> are evaluated for trustworthy characteristics. They should be tested before deployment and regularly in operation.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">04<\/span><span class=\"nx-pe-st\">MEASURE: track identified risks over time<\/span><span class=\"nx-pe-k\">Model<\/span><span class=\"nx-pe-sm\">Mechanisms for tracking identified AI risks over time are in place, including unanticipated and emergent risks.<\/span><\/li><\/ol><\/li><li class=\"nx-pe-lane\"><h3 class=\"nx-pe-lane-t\">04 Manage<\/h3><ol><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">05<\/span><span class=\"nx-pe-st\">MANAGE: treat risks<\/span><span class=\"nx-pe-k\">Step<\/span><span class=\"nx-pe-sm\"><a class=\"nx-link nx-term\" href=\"https:\/\/nexustandards.com\/standards\/nrs\/#nrs-c1\" data-tc=\"NRS-C1 risk-treatment\" data-tk=\"Nexus risk vocabulary\" data-td=\"Selecting and applying options to modify risk: avoiding, reducing, transferring, sharing or retaining it.\" data-ts=\"NRS-C1\" data-tr=\"draft\">Risk treatment<\/a> plans cover response to, recovery from and communication about incidents. Resources go to mapped and measured risks.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">06<\/span><span class=\"nx-pe-st\">Proceed or not (MANAGE 1.1)<\/span><span class=\"nx-pe-k\">Gate \u00b7 AI risk committee<\/span><span class=\"nx-pe-sm\">A determination is made whether the system meets its purposes and objectives, and whether to proceed. The framework sets no thresholds.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">07<\/span><span class=\"nx-pe-st\">Deployment decision<\/span><span class=\"nx-pe-k\">Decision \u00b7 AI risk committee<\/span><span class=\"nx-pe-sm\">The organisation that owns the system decides whether and under what conditions to deploy.<\/span><\/li><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">08<\/span><span class=\"nx-pe-st\">Post-deployment monitoring and incidents<\/span><span class=\"nx-pe-k\">Model<\/span><span class=\"nx-pe-sm\">Post-deployment monitoring plans are implemented. Incidents and errors are shared with relevant AI actors, including affected communities.<\/span><\/li><\/ol><\/li><li class=\"nx-pe-lane\"><h3 class=\"nx-pe-lane-t\">05 Record<\/h3><ol><li class=\"nx-pe-step\"><span class=\"nx-pe-n\" translate=\"no\">09<\/span><span class=\"nx-pe-st\">Inventory of AI systems<\/span><span class=\"nx-pe-k\">Dataset<\/span><span class=\"nx-pe-sm\">GOVERN 1.6 asks for mechanisms to inventory AI systems. A model card is common practice and is not named in the framework.<\/span><\/li><\/ol><\/li><\/ol><p class=\"nx-pe-foot\"><span>Neutral outline of a published external standard or method, from its issuing body. Not a record of operation. Nexus does not perform, certify or approve any step shown. A gate or decision belongs to the party the source names. The actions are not necessarily an ordered set of steps. The EU AI Act is not drawn in this flow.<\/span><\/p><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-connections\" class=\"nx-section\" data-hue=\"infrastructure\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-8\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Connections<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">Topics that rely on this method.<\/h2><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\" data-nav=\"true\"><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/topics\/model-evaluation\/\"><span>Model evaluation<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/topics\/agentic-systems\/\"><span>Agentic systems<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/topics\/ai-cyber-security\/\"><span>AI cyber security<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/topics\/ai-in-science\/\"><span>AI in science<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/topics\/ai-and-public-services\/\"><span>AI and public services<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/topics\/autonomous-physical-systems\/\"><span>Autonomous physical systems<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-stewardship\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-9\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Stewardship<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Who maintains the method.<\/h2><p class=\"nx-lede\">Artificial Intelligence and Autonomous <a class=\"nx-link nx-term\" href=\"https:\/\/docs.therisk.global\/organization\/systems\" data-tc=\"Systems\" data-tk=\"Nexus Standards\" data-td=\"The twenty Nexus systems, NXS-CMD to NXS-LAB\">Systems<\/a> stewards AI evaluation and assurance engineering for the Consortium and reviews how it is applied across platforms.<\/p><\/div><div class=\"nx-section-body\"><p class=\"nx-p\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/engineering\/ai-assurance\/\">Canonical page: AI evaluation and assurance engineering<\/a><\/p><\/div><\/div><\/section><section id=\"nx-s-10-sec\" class=\"nx-section\" data-hue=\"infrastructure\" data-tone=\"alt\" aria-labelledby=\"nx-s-10\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">10<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Questions<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>What are the limits of AI evaluation and assurance engineering in this field?<\/summary><div class=\"nx-answer\">Benchmarks may not reflect real-world use or novel capabilities. General-purpose systems have open-ended behaviour that resists complete testing.<\/div><\/details><details><summary>How are results checked?<\/summary><div class=\"nx-answer\">Evaluation methods are checked for reliability and relevance to deployment conditions. Independent replication and third-party audits test claims.<\/div><\/details><details><summary>Are the values on this page real?<\/summary><div class=\"nx-answer\">The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method&#8217;s use, not a run; no result is reported here.<\/div><\/details><details><summary>Where else is this method applied?<\/summary><div class=\"nx-answer\">The <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/engineering\/ai-assurance\/\">canonical method page<\/a> lists every platform that applies it.<\/div><\/details><\/div><\/div><\/div><\/section><section id=\"nx-sec-nr-gateway\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" aria-labelledby=\"nx-nr-gateway-h\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">Reports<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Contribute<\/span><\/div><h2 id=\"nx-nr-gateway-h\" class=\"nx-section-title\">Contribute evidence from this page.<\/h2><p class=\"nx-lede\"><a class=\"nx-link\" href=\"https:\/\/docs.therisk.global\/organization\/programme\/reports\">Reports<\/a> is the Consortium&#8217;s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.<\/p><div class=\"nx-chips\"><span class=\"nx-chip\">GCRI<\/span><span class=\"nx-chip\">Artificial Intelligence and Autonomous Systems<\/span><span class=\"nx-chip\">Exponential Technology<\/span><span class=\"nx-chip\">Labs Evidence<\/span><\/div><\/div><div class=\"nx-section-body\"><ul class=\"nx-dest\"><li><a class=\"nx-dest-card\" href=\"https:\/\/therisk.global\/ai-autonomous-systems\/write-to-us\/contact\/\"><span class=\"nx-dest-top\"><span class=\"nx-dest-rel\">Email<\/span><span class=\"nx-dest-host\">Gateway GW-GCRI<\/span><\/span><span class=\"nx-dest-title\">Send it from this page<\/span><span class=\"nx-dest-why\">Evidence, a correction, a case, a method, a review, a translation or profile input. It arrives tagged with this page, so the editor who owns it receives it.<\/span><span class=\"nx-dest-go\" aria-hidden=\"true\"><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><\/li><li><a class=\"nx-dest-card\" href=\"https:\/\/therisk.global\/nexus-reports\/open-science\/#nx-sec-zenodo\"><span class=\"nx-dest-top\"><span class=\"nx-dest-rel\">Zenodo<\/span><span class=\"nx-dest-host\">Open deposit<\/span><\/span><span class=\"nx-dest-title\">Deposit it and submit to the community<\/span><span class=\"nx-dest-why\">Publish your own record on Zenodo with your ORCID iD, then submit it to the Reports community there. Curators review it; the DOI stays yours.<\/span><span class=\"nx-dest-go\" aria-hidden=\"true\"><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><\/li><li><a class=\"nx-dest-card\" href=\"https:\/\/therisk.global\/nexus-reports\/contribute\/\"><span class=\"nx-dest-top\"><span class=\"nx-dest-rel\">Reports<\/span><span class=\"nx-dest-host\">GCRI<\/span><\/span><span class=\"nx-dest-title\">See every way to contribute<\/span><span class=\"nx-dest-why\">The contribution types, how each is reviewed, what credit you receive, the licence and what is never accepted.<\/span><span class=\"nx-dest-go\" aria-hidden=\"true\"><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><\/li><\/ul><div class=\"nx-live-slot\" data-nxf-slot=\"contribute\" data-nxf-kind=\"workflow\" data-nxf-resource=\"nexus:\/\/gcri\/ai-autonomous-systems\/stem\/ai-assurance#contribute\" data-nxf-title=\"Contribute evidence\" data-nxf-height=\"480\" hidden><\/div><p class=\"nx-note nx-mt-3\">Never send personal data, sensitive infrastructure detail or anything you have no right to share. A contribution is reviewed before use; sending it confers no authorship or editorial rights, and sponsorship never buys a finding.<\/p><\/div><\/div><\/section><section class=\"nx-section nx-deeper-band\" aria-labelledby=\"nx-deeper-k-global-ai-autonomous-systems-stem-ai-assurance-h\"><div class=\"nx-container\"><nav class=\"nx-deeper\" aria-labelledby=\"nx-deeper-k-global-ai-autonomous-systems-stem-ai-assurance-h\" data-nx-deeper=\"3\" data-nx-resources=\"1 1 1\"><h2 class=\"nx-deeper-h\" id=\"nx-deeper-k-global-ai-autonomous-systems-stem-ai-assurance-h\">Go deeper<\/h2><ul><li><a href=\"https:\/\/docs.therisk.global\/organization\/programme\/the-programme-year\" data-ext><span class=\"nx-deeper-k\">Documentation:<\/span> The programme year<span class=\"nx-deeper-x\" aria-hidden=\"true\">\u2197<\/span><span class=\"nx-deeper-sr\"> (opens another site)<\/span><\/a><\/li><li><a href=\"https:\/\/risksacademy.com\/technology-digital\/artificial-intelligence\/\" data-ext><span class=\"nx-deeper-k\">Academy:<\/span> Artificial intelligence and machine learning<span class=\"nx-deeper-x\" aria-hidden=\"true\">\u2197<\/span><span class=\"nx-deeper-sr\"> (opens another site)<\/span><\/a><\/li><li><a href=\"https:\/\/nexustandards.com\/digital-ai\/cyber-and-digital-risk-standards\/\" data-ext><span class=\"nx-deeper-k\">Standards:<\/span> Cyber and digital risk standards<span class=\"nx-deeper-x\" aria-hidden=\"true\">\u2197<\/span><span class=\"nx-deeper-sr\"> (opens another site)<\/span><\/a><\/li><\/ul><\/nav><\/div><\/section><section class=\"nx-closing\" aria-labelledby=\"nx-close-11\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Artificial Intelligence and Autonomous Systems<\/span><h2 id=\"nx-close-11\" class=\"nx-section-title\">Bring a method, a dataset or a question.<\/h2><p class=\"nx-lede\">Information and enquiries are open today. 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