A System for AI-Assisted Data and Research Deliverables

Route by evidence question

Decide whether the artifact describes, compares, explains, forecasts, evaluates, or recommends. Each job needs different evidence. A descriptive dashboard summarizes observed records. A causal explanation needs a design that addresses alternatives. A forecast needs assumptions and error tracking. A recommendation needs options, criteria, uncertainty, and ownership.

The U.S. GAO data-reliability guide defines reliability in relation to accuracy, completeness, and applicability for the intended purpose, using a risk-based approach (Assessing Data Reliability). GAO also emphasizes rigorous design, documentation, confirmation, and transparency in research reliability (Research Reliability). These sources support evidence review, not a claim that every artifact meets audit standards.

Sources: [1] [2]

Create a provenance record

Record source owner, access date, version, population, fields, collection process, transformations, exclusions, joins, missingness, and permitted use. For literature, include search boundary, screening, extraction, and citation location. For qualitative research, retain excerpt IDs and coding rules.

Ask AI to generate transformations only when they can be inspected and reproduced. Preserve code, formulas, prompts, and output versions as appropriate. Never accept a generated citation or statistic without opening its authoritative source.

Worked research brief

Consider a synthetic analysis of support-response delays. The dataset contains ticket creation and first-response times, but one channel stopped logging for two weeks. AI initially concludes that response performance improved after training.

The corrected artifact includes a coverage chart, excludes the outage period from the primary comparison, shows results with and without the affected channel, and labels training timing as context rather than cause. A data-quality record documents missing fields and the system owner’s confirmation.

The final brief says what the observed data show, what they cannot show, and which follow-up evidence is needed. It does not convert temporal sequence into causal impact.

Match review to the deliverable

For calculations, recompute from source values. For charts, verify scale, denominator, labels, and suppressed categories. For synthesis, trace claims to sources and preserve disagreement. For recommendations, challenge criteria and alternatives. For predictive work, evaluate on a suitable held-out design and state limits.

Add a correction log so later source changes propagate to affected claims and charts.

Package the artifact for review

Deliver the reader-facing output beside a compact evidence appendix. The appendix should include the question, source register, data dictionary, transformation record, analysis version, limitations, reviewer notes, and correction route. Use stable identifiers so a chart or paragraph can point to the exact evidence row that supports it.

For interactive outputs, provide an export or snapshot that preserves the reviewed state. For code-based analysis, record the environment and dependencies needed to reproduce it. For confidential work, separate shareable conclusions from restricted evidence while keeping an authorized review path. AI can help assemble the package, but owners must verify that links resolve and permissions match the intended audience.

Verification checklist

This system makes research artifacts inspectable. It does not establish causality, generalizability, or mature benchmark quality without suitable evidence.

Retain rejected analyses when their failure teaches reviewers which transformation, assumption, or source gap should not be repeated.

Attach a reader guide stating which tables, charts, or claims can be reused and which require the restricted appendix. This keeps a shareable conclusion from becoming detached from its evidence boundary.

• The evidence question and artifact type match.
• Source provenance and permitted use are recorded.
• Transformations, exclusions, and calculations are reproducible.
• Missingness and conflicting evidence remain visible.
• Claims do not exceed the design.
• Independent review targets the artifact’s main failure mode.
• Corrections and source updates are versioned.