GCRI · زیرەکی دەستکرد و سیستەمە خۆسەرەکان
Methods and uncertainty
The methods Artificial Intelligence and Autonomous سیستەم relies on: their equations and assumptions, the data they need, how they are validated and the limits of what they can show.
ئەو ڕیزبەندییەی شتەکان تێیدا ڕوودەدەن.
- 01پێشنووسsources cited, labels attached
- 02Evidence checkevery value traced
- 03Independent reviewconflicts declared
- 04وەشانpublished with its limits
- 05ڕاستکردنەوەa new version, never a silent edit
The methods in use.
- 01زیرەکی دەستکرد و فێربوونی ماشێنDistribution shift analysis · Fine-tuning for a specific use · Interpretability methodsApplied here
- 02ئەندازیاری هەڵسەنگاندن و دڵنیایی لە زیرەکی دەستکردAssurance cases for AI systems · Structured red teaming · Post-deployment monitoringApplied here
- 03کۆمپیوتەری کارایی بەرز، هەور و لێوارCompute access for public research · Energy measurement of workloadsApplied here
- 04ئەگەر و ئامارUncertainty on benchmark scores · Calibration assessment · Audit samplingApplied here
- 05ئاسایشی سایبەری و کریپتۆگرافیThreat modelling AI applications · Model supply chain integrity · Injection defence testingApplied here
- 06زانستی کۆمەڵایەتی و ڕەفتاریHuman oversight studies · Affected community research · Workplace adoption studiesApplied here
- 07ڕۆبۆتیک و ئۆتۆماسیۆنScenario-based testing · Collaborative robot safety · Operating domain monitoringApplied here
Each method, its role in this field and how it is checked.
- Ai MLRole hereArtificial intelligence and machine learning is the technology this platform stewards for the network.Checks appliedHeld-out evaluation; Dataset documentation; Drift monitoring
- Ai assuranceRole hereAI evaluation and assurance engineering is the second method this platform stewards.Checks appliedIndependent review; Evidence currency; Coverage reporting
- ComputingRole hereHigh-performance and cloud computing supply the capacity AI needs.Checks appliedMeasurement boundaries; Reproducible configuration; Provider data verification
- Probability statisticsRole hereProbability and statistics make AI evaluation trustworthy: confidence intervals on scores, significance of differences between models, calibration of predicted probabilities and sampling designs for audits.Checks appliedInterval reporting; Multiple comparisons; Sample size planning
- ئاسایشی سایبەریRole hereCybersecurity and cryptography protect AI systems and the data they use.Checks appliedThreat model review; Provenance verification; Regression testing
- زانستی کۆمەڵایەتیRole hereSocial and behavioural science studies how people use, trust and are affected by AI.Checks appliedEthics review; Pre-registration; Representative sampling
- ڕۆبۆتیکسRole hereRobotics and automation bring AI into physical systems.Checks appliedScenario coverage; Simulation validity; Standards conformity
چۆن پرۆسەکە کار دەکات.
Process explorer · Process
Methods and uncertainty: PRISMA 2020 review reporting
10 steps·4 قۆناغ
پرۆسە
Methods and uncertainty: PRISMA 2020 review reporting
PRISMA 2020 is a reporting guideline for systematic reviews; the steps follow its checklist, not a mandated sequence, and no Nexus document adopts it.
01 Plan
- 01Registration and protocolRecord · The review teamThe guideline asks for registration details, access to the protocol and any amendments.
- 02Eligibility criteriaRecord · The review teamThe guideline asks for the inclusion and exclusion criteria and how studies were grouped.
02 Find and select
- 03Search: sources and strategiesStep · The review teamThe guideline asks for the information sources and the full search strategies. It does not fix which sources are used.
- 04Selection of studiesStep · The review teamThe guideline asks how studies were judged eligible, including how many reviewers screened. It does not fix the number of reviewers.
- 05Flow diagramتۆمارThe flow diagram shows the number of records found, the number of studies included and the reasons for exclusion.
03 Analyse
- 06Data collectionStep · The review teamThe guideline asks how data were collected from reports and which data items were sought.
- 07Risk of biasStep · The review teamThe guideline asks for the methods and tools used to assess risk of bias.
- 08SynthesisModel · The review teamThe guideline asks for the effect measures and the synthesis methods. It does not prescribe meta-analysis.
- 09Certainty of evidenceStep · The review teamThe guideline asks for the methods used to assess certainty, and reports the result per outcome. It does not name a grading scale.
04 Report
- 10Review reportتۆمارThe guideline helps authors report why the review was done, what they did and what they found.
ReportsOutline of an externally published reporting guideline, not a Nexus process and not a record of operation. PRISMA 2020 mainly covers reviews of intervention effects. No Nexus page names it. Every programme is at service level R0.
Where uncertainty in AI analysis comes from, and how it is shown.
| سەرچاوە | Why it matters here | How it is reported |
|---|---|---|
| Benchmark validity | Benchmarks saturate and leak into training data | Several evaluations, held-out tests, dates stated |
| Capability elicitation | Measured capability depends on prompting and tools | Elicitation effort described |
| Deployment context | Risk depends on use, not only the model | Use-specific assessment |
| Incident data | Reporting is voluntary and uneven | Incident sources and coverage stated |
Evaluation results carry the model version, date and setup; AI capability changes quickly and old results expire.
How uncertainty is reported.
- 01
State assumptions
Each analysis lists its assumptions and the data it depends on.
- 02
Quantify where possible
Ranges and confidence are reported alongside central estimates.
- 03
Validate and compare
Models are checked against observations and, where possible, against other models.
- 04
Publish limits
What an analysis cannot show is stated beside what it can.
Where this page’s references lead.
ئەو لەش و بەڵگەنامانەی ئەم لاپەڕەیەیان لەگەڵ دەخوێنرێتەوە. دۆخ و وەشانەکان دەگۆڕێن؛ هەر بەستەرێک دەچێتە لای لەشی دەرکەر.
پرسیار و وەڵام.
Are the methods open?
لەم لاپەڕەیەوە بەڵگە پێشکەش بکە.
Reports is the Consortium’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.
- ئیمەیڵدەروازەی GW-GCRIلەم لاپەڕەیەوە بینێرەبەڵگە، ڕاستکردنەوە، بابەت، ڕێگا، پێداچوونەوە، وەرگێڕان یان تێکردنی پڕۆفایل. بە نیشانەی ئەم لاپەڕەیە دەگات، بۆ ئەوەی دەستکاریکەری خاوەنەکەی وەریبگرێت.
- Zenodoتەکیەی کراوەدایبنێ و بیدە بە کۆمەڵگاتۆماری خۆت لە Zenodo بە ORCID iD ی خۆت بڵاو بکەرەوە، پاشان لەوێ بیدە بە کۆمەڵگای Reports. سەرپەرشتیارەکان پێداچوونەوەی بۆ دەکەن؛ DOI هەر هی تۆیە.
- ReportsGCRIهەموو ڕێگاکانی بەشداری ببینەجۆرەکانی بەشداری، هەریەکە چۆن پێداچوونەوەی بۆ دەکرێت، چ ناوبردنێک وەردەگریت، مۆڵەتەکە و ئەوەی هەرگیز وەرناگیرێت.
هەرگیز داتای کەسی، وردەکاریی هەستیاری ژێرخان یان هیچ شتێک مەنێرە کە مافی بڵاوکردنەوەت نییە. بەشدارییەک پێش بەکارهێنان پێداچوونەوەی بۆ دەکرێت؛ ناردنی ماف نابەخشێت بە نووسەرایەتی یان بەڕێوەبردنی ڕاگەیاندن، و پاڵپشتی دارایی هەرگیز دۆزینەوەیەک ناکڕێت.
ڕێگایەک، کۆمەڵە داتایەک یان پرسیارێک بهێنە.
زانیاری و پرسیار ئەمڕۆ کراوەن. پرسیارێک ژمارەی ئاماژەی پێدەدرێت و هەنگاوی دواتر دیاری دەکات؛ داواکاری، پارەدان، تەرخانکردنی کۆمپیوتەر و تۆمارکردن تەنیا کاتێک دەکرێنەوە کە تیم، مەرج و توانای پێداچوونەوەیان هەبێت.
بەڵگەنامە یاساییەکان.
نەخشە، داتا و وێنەکانی ئەم ماڵپەڕە بۆ ناوەڕۆک و زانیاریی گشتی پیشان دراون. ئامۆژگاری، پێشبینی یان ئاگادارکردنەوە نین؛ سنوورەکانی زانیارییەکە لە ڕەتکردنەوەی بەرپرسیارێتی و ئاگاداریی داتادا دەستنیشان کراون.