AI Hallucination ResearchFindings by audienceSectorsInternational / MultilateralElectricity PowerEsg SustainabilityDetail › Finding
Electricity Power × Esg Sustainability — International / Multilateral · Last updated 11 Jun 2026 · Hallucination Register
Share / Print X LinkedIn Email

Finding#1, Ireland data-centre electricity share, fabricated figure and time-series

RLB Citation ID: RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006
AI's failure:Exposed Fabrication Risk for Electricity Power × Esg Sustainability:Wrong deliverable
What the RLB Specialist Panel found
Question (paraphrased to protect IP)

What share of Ireland's 2021 metered electricity did data centres account for, per the figure cited in the OECD Digital Economy Outlook 2024 chapter (sourced from Ireland's CSO 2023)?

RLB's analysis

The model correctly identified the source chain, CSO 2023 as cited in the OECD Digital Economy Outlook 2024, but substituted 14% for the regulator's 11%. It then extended the response with a forward-projected series (18% in 2022, 21% in 2023) that is not present in the regulator's text, suggesting the model reconstructed a plausible growth trajectory rather than quoting the authoritative figure. The error is not a misidentified source but a numeric value that has drifted at the point of reproduction.

AI Head's analysis — what weakness in the AI model caused this

This finding implicates two distinct subsystems. First, the retrieval layer correctly surfaced the source lineage (CSO 2023 via OECD Digital Economy Outlook 2024) but the numeric payload at the point of generation drifted — suggesting the training corpus contains multiple paraphrased variants of this figure and the model resolved the conflict toward a higher value present in secondary commentary rather than the verbatim primary text.

Second, the forward-series confabulation (18% in 2022, 21% in 2023) indicates the model's generation logic treats trend continuation as a low-uncertainty extension when an anchor year and growth direction are established in context — a calibration gap that is independent of retrieval quality and would require a post-generation verification step or explicit uncertainty injection to close.

Impact for ESG & Sustainability Teams in Electricity & Power Sector in international jurisdictions working with the Recommendation of the Council on Digital Technologies and the Environment (2025 Revision)

AI tools we tested stated that data centres accounted for 14% of Ireland's metered electricity in 2021, citing Ireland's Central Statistics Office via the OECD Digital Economy Outlook 2024, when the Recommendation's own text gives the figure as 11%. The AI compounded this by generating a fabricated time-series (5% / 14% / 18% / 21% across 2015–2023) that appears nowhere in the source material, giving the wrong anchor figure a false air of corroboration.

For an ESG & Sustainability team at an Electricity & Power firm, this figure is live material: it is exactly the kind of OECD benchmark used to contextualise a firm's data-centre offtake or grid digitalisation footprint in climate transition plan disclosures, regulatory submissions on digital infrastructure energy obligations, or due-diligence briefings on PPA counterparties. A three-percentage-point error on a jurisdiction the OECD has explicitly named, carried into a board sustainability report or a regulator-facing policy brief, creates both a factual mis-statement to retract and a process credibility question the team will need to answer.

References — raw findings (per AI model)
This finding also affects
Cite this finding

Each finding has a stable Citation ID (RLB-F-… for aggregated case-study findings, RLB-H-… for raw per-model hallucinations) — like a DOI, the ID always resolves to the canonical finding even if URLs change.

RLB Citation ID: RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006
Plain text Download
RegLeg Specialist Panel (2026). "Finding#1, Ireland data-centre electricity share, fabricated figure and time-series — Electricity Power × Esg Sustainability — International / Multilateral." Citation ID: RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006. RegLegBrief AI Hallucination Research, published 2026-06-11. https://reglegbrief.com/regulators/j1/int/OECD/OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025/sectors/electricity_power/esg_sustainability/finding/INT-OECD-INT-001-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-v1-006/
APA 7th edition Download
RegLeg Specialist Panel. (2026). Finding#1, Ireland data-centre electricity share, fabricated figure and time-series [Hallucination finding RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006]. RegLegBrief AI Hallucination Research. https://reglegbrief.com/regulators/j1/int/OECD/OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025/sectors/electricity_power/esg_sustainability/finding/INT-OECD-INT-001-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-v1-006/
Bluebook / OSCOLA (US + UK legal) Download
RegLeg Specialist Panel, Finding#1, Ireland data-centre electricity share, fabricated figure and time-series [RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006], RegLegBrief AI Hallucination Research (June 11, 2026), https://reglegbrief.com/regulators/j1/int/OECD/OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025/sectors/electricity_power/esg_sustainability/finding/INT-OECD-INT-001-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-v1-006/.
BibTeX Download
@misc{reglegbrief_RLB_F_INT_OECD_OECD_DIGITAL_TECHNOLOGIES_ENVIRONMENT_2025_Q006,
  author    = {RegLeg Specialist Panel},
  title     = {Finding#1, Ireland data-centre electricity share, fabricated figure and time-series},
  year      = {2026},
  publisher = {RegLegBrief AI Hallucination Research},
  note      = {Hallucination finding Citation ID: RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006},
  url       = {https://reglegbrief.com/regulators/j1/int/OECD/OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025/sectors/electricity_power/esg_sustainability/finding/INT-OECD-INT-001-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-v1-006/}
}
← Back to case study summary Case study detail →

Every finding on this page compares an AI subject's account of the rule against the regulator's verbatim text from the regulator's own portal. Both are linked. Each delta, its root causes, and impact analysis are documented and published with immutable Citation IDs.