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Artificial intelligence · Data and compute

Reports における人工知能と自律システム

Trustworthy artificial intelligence, robotics-enabled autonomy, computational methods and social effects. This page shows the series it feeds, the evidence behind it and how to contribute.

シリーズ
2
システム
4
手法
7
01In brief

What this area brings to the editions.

Trustworthy artificial intelligence, robotics-enabled autonomy, computational methods and social effects.

02In the editions

9 findings of the drafted editions that bear on Artificial Intelligence and Autonomous Systems.

Drawn from the Baseline Edition 2026 drafts through the システム this area reads. Each opens at its anchor in its edition, with its numbered sources.

  1. AREアラブ首長国連邦Gas gave 68% of electricity generation in 2025, down from 97% in 2019, while nuclear reached 21% and solar 10%; total generation rose from 138 to 184 TWh.REPORTED · COUNTRY-ARE-ENE-003
  2. ARGアルゼンチンLow-carbon sources supplied 42% of electricity in 2025, and renewables including large hydro covered 40.2% of demand.REPORTED · COUNTRY-ARG-ENE-003
  3. AUアフリカ連合In 2024, 55.1% of people in Sub-Saharan Africa had electricity, up from 46.4% in 2018; about 579 million had none (derived).REPORTED · COUNTRY-AU-ENE-002
  4. AUSオーストラリアWind and solar supplied 33% of electricity in 2025; fossil fuels supplied 61% and coal 43%.REPORTED · COUNTRY-AUS-ENE-003
  5. BRAブラジルRenewables supplied 86.8% of electricity in 2025. Hydropower fell 4.8% to 401.4 TWh while gas generation rose 22.7%, and wind and solar together supplied 26.4%.REPORTED · COUNTRY-BRA-ENE-005
  6. CHEスイスIn 2025 hydropower supplied 55.5% of domestic electricity generation, nuclear power 27.2% and photovoltaics 11.8%, and final electricity consumption was 57,970 GWh.REPORTED · COUNTRY-CHE-ENE-003
  7. CHN中国Coal supplied 54.8% of electricity in 2025 and 51.4% of total energy consumption, while wind and solar supplied 21.9% of electricity.REPORTED · COUNTRY-CHN-ENE-006
  8. EU欧州連合Renewables supplied 25.2% of gross final energy consumption in 2024, 17.3 points below the 42.5% target for 2030.REPORTED · COUNTRY-EU-ENE-003
  9. GS-02世界のエネルギーGlobal energy demand grew 1.3% (8 EJ) in 2025, down from 2% in 2024, and electricity demand grew nearly 3%, more than twice as fast.REPORTED · SECTOR-ENERGY-GLOBAL-ENE-001
03Evidence path

From Foundry evidence to the series.

The evidence, step by step, from the システム this area reads to the series it feeds.

How Artificial Intelligence and Autonomous Systems reaches 報告書: what it reads, how it reads it, the sealed cut and the series it feeds.

ステップ何が起きるか出典
01 What it readsArtificial Intelligence and Autonomous Systems reads NXS-NXQ(ソフトウェア、モデル、能力のライフサイクル) と NXS-LAB(研究、実験、シミュレーション): governed sources with their releases, never a value without its source.
02 How it reads themArtificial intelligence and machine learning and AI evaluation and assurance engineering turn the evidence into findings, with assumptions and limits stated beside each value.
03 The cut is sealedEach quarter the evidence is sealed in one cut, so OBSERVED, REPORTED and ESTIMATED values stay apart and every edition can be rebuilt.
04 The series it feedsThe cut feeds Exponential Technology and ラボ Evidence, from the Baseline Edition 2026 into the quarterly series.
05 Who decidesDecisions stay with the authorities that hold them, under their own rules; an edition informs a decision and never makes it.

A teaching model of the evidence path, not a forecast and not a record of any run; the systems, methods and series named come from the registries. Sources: Reports における人工知能と自律システム (2026); Artificial Intelligence and Autonomous Systems home (2026).

04シリーズ

The series it feeds, and what backs each.

シリーズFoundry systems it draws onAcademy disciplinesSeries home
指数関数的テクノロジーNXS-NXQ the capability catalogue and fitness assessments of machine capabilities
NXS-LAB benchmark comparisons and experiment records for fast-changing technologies
人工知能と機械学習
イノベーションと先端技術のガバナンス
量子技術
Exponential Technology series home
ラボ エビデンスNXS-LAB what was tried, under which conditions, and what happened, including negative results研究、エビデンス、科学と政策のインターフェース
複雑 システム and systems modelling
Labs Evidence series home
08貢献する

Contribute on Artificial Intelligence and Autonomous Systems.

Evidence, a case, a correction, a method or profile input on this subject. The composer tags it with this area and its series.

Contribution composer

Write a contribution the editor can act on.

Say what it is, where its record is kept and on which licence. It arrives tagged with this page, its area and its gateway, so it reaches the editor who owns it.

Your email opens with the subject and a template already filled in for GW-GCRI.

  • エビデンス
  • 訂正
  • 事例研究
  • Analysis or method
  • 査読
  • 翻訳
  • Profile input

Never send personal data or sensitive infrastructure detail. A contribution is reviewed before use; sending it confers no authorship or editorial rights.

09オープンサイエンス

Open science for Artificial Intelligence and Autonomous Systems.

How a contribution on this subject is deposited, identified, credited, licensed and found, and the metadata for it prefilled from this page.

Artificial Intelligence and Autonomous Systems’s open record

エリア
人工知能と自律システム
Feeds
Exponential Technology, Labs Evidence
記録
A UNI for every accepted contribution; cited with its DOI in the edition that uses it
リンク
isSupplementTo the edition it informs; isNewVersionOf its earlier version
ライセンス
CC BY 4.0 (SPDX CC-BY-4.0) for original material; metadata CC0 1.0

Credit and identity

ORCID
Your iD in the deposit and the contribution record; DataCite can then add the work to your ORCID record
ROR
Your organisation by its ROR identifier, never by a typed name alone
CRediT
Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualisation, Writing, review and editing
アカウント
None needed to contribute; never a password

Find and follow

Search the open indexes for Artificial Intelligence and Autonomous Systems; software is cited by its SWHID from Software Heritage. Annotation is your choice: Hypothesis opens this page in its own viewer.

Mirrors and harvest

The DOI is canonical. At release each signed bundle is also given an IPFS content identifier and a bloxberg anchor as mirrors; both are listed in the record once they exist. Zenodo exposes every record over OAI-PMH, and reviews and endorsements can arrive through COAR Notify where the repository supports it.

InvenioRDM metadata for a contribution on Artificial Intelligence and Autonomous Systems, prefilled from this page
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10最新

Releases for this area.

Releases tagged to this area appear here once released.

報告書貢献する

Send evidence on Artificial Intelligence and Autonomous Systems.

Reports is the Consortium’s quarterly publication, written by six desks. This page sits with the Global Centre for Risk and Innovation (GCRI) システム ・エビデンスデスクに属します。このテーマについてご存じのことは、次の版でエビデンス、事例、訂正となり得ます。ご自身の成果であれば、あなたの名前を付し、CC BY 4.0 で公開します。誤ったデスクに送られた場合も、断られることなく転送されます。

GCRI システム・エビデンスデスク人工知能と自律システム指数関数的テクノロジーLabs のエビデンス
Reports · GCRI

Bring what you know to the next edition.

Every quarter closes on a sealed evidence cut. Contributions received before the cut are reviewed for that edition; later ones wait for the next.

CC BY 4.0 Free to read. Text and figures: CC BY 4.0. Data: CC0 1.0. Authors keep copyright. Published by GCRI Canada.