Title

Blueprint for an AI bill of rights

EU AI Act

EU GPAI Art.53 point.1 a

EU GPAI Art.53 Point.1 b

EU GPAI Art53 other

AI事業者ガイドライン

Model AI Governance Framework

新一代人工智能伦理规范

生成式人工智能服务管理暂行办法

生成式人工智能服务安全基本要求

Country

USEU

EU

EU

EU

Japan

Singapore

China

China

China

Use of AI

an automated system is being usedinteracting with an AI system

2条1項

using an emotion recognition system or a biometric categorisation

中華人民共和国内の公衆にテキスト、画像、音声、動画およびその他のコンテンツを生成するサービスを提供するsystem

AI を利用しているという事実

whether AI is used in their products and/or services

ための生成AI技術の使用

where applicable, the technical capabilities and characteristics ofthe highrisk AI system to provide information that is relevant toexplanation of outputs

explanations of outcomes

explanation of reasons

how and why it contributes to outcomes that impact you.

overall explanation

overall system functioning and the role automation plays

explain its output;
the degree to which the AI system can provide an explanation for
decisions it takes
Where applicable, a detailed description of the system

how the model interacts, or can be used to interact, witharchitecture explaining how software components build or feedhardware or software that is not part of the model itself, where

what AI is, how AI is used in decision-making in relation to consumers

into each other and integrate into the overall processing.

applicable;

the role and extent that AI plays in the decision-making process
第2条
人工知能の管理、研究開第22条（2号・3号）

発、供給、使用およびその ●生成AIサービス・プロバイダーとは、生成AI技術を用いて生成AIサービスを提供（プログラマブル・インター他の関連活動に従事する自 フェースの提供等による生成AIサービスの提供を含む）する組織又は個人をいう。
然人、法人およびその他の ●生成AIサービス利用者とは、生成AIサービスを利用してコンテンツを生成する組織又は個人をいう。

the identity and the contact details of the provider and, where
Who is responsible

the individual or organization responsible for the systemapplicable, of its authorised representatives;

Change of models

significant use case or key functionality changes.

changes to the high-risk AI system and its performance

責任者の明示関連組織等

the identity and the contact details of the entity that carried out
assessment

the algorithmic impact assessments

第17条

the conformity assessment

安全评估[安全性アセスメント]
the tasks that the model is intended to perform and the type andnature of AI systems in which it can be integrated;

purposes or how to use

the goal and use cases for the systemusers

identified users

impacts by AI

impacted populations

intended purpose

18条：善意による利用
the tasks that the model is intended to perform and the type and19条：誤用・濫用の回避

nature of AI systems into which it can be integrated;

提供先における適切/不適切な利用方法

20条：悪用の禁止
the manner in which an AI decision may affect an individual consumer,

22条3号

known or foreseeable circumstance... which may lead to risks toand whether the是指使用生成式人工智能服务生成内容的组织、个人。

the health and safety or fundamental rights

decision is reversible.

（生成AIサービスを利用してコンテンツを生成する組織又は個人）【12条】
プロバイダーは、「インターネット情報サービスディープフェイク管理規定」に照らして、画像や動画等の生成コ

the assessment of notice clarity and timeliness

12条

the assessment of the explanation’s validity and安全性と透明性の強化

accessibility
the assessment of the level of risk
assesment of trancparency

ンテンツにマークを付さなければならない。
【17条】
世論属性を有する、または社会に働きかける機能を持つ生成AIサービスを提供する者は、国内の関連法規に従って安全性評価を実施し、「インターネット情報サービスのアルゴリズム推奨管理規則」に従ってアルゴリズムの申請

assessment of how explanations are tailored

および変更・取消申請手続を行わなければならない。
enable providers of AI systems to have a good understanding of

performance and limitation

characteristics, capabilities and limitations of performancethe capabilities and limitations of the general-purpose AI model

22条

and to comply with their obligations pursuant to this Regulation;

利用性能の向上andA detailed description of the evaluation strategies, including
evaluation results, on the basis of available public evaluation

accuracy

the level of accuracy, robustness and cybersecurity ..., and any

protocols and tools or otherwise of other evaluation

clearly known and foreseeable circumstances that may have anmethodologies. Evaluation strategies shall include evaluation

impact on that expected level of accuracy, robustness andcriteria, metrics and the methodology on the identification of

学習及び評価の手法

cybersecurity;

limitations.

AI システム・サービスの能力、限界

when appropriate, its performance regarding specific persons orperformance on certain people

groups of persons on which the system is intended to be used;
relevant information about user actions that may influence

appropriateness of input datasystem performance, including type or quality of input data,
information on the data used for training, testing and validation,【7条】

where applicable, including the type and provenance of data and・合法なソースのデータ及びベースモデルを使用すること（1号）

curation methodologies (e.g. cleaning, filtering etc), the number of・学習データの質を向上させ、学習データの真実性、正確性、客観性及び多様性を向上させるための効果的な措置

data points, their scope and main characteristics; how the data

draw up and make publicly available a sufficiently detailed

specifications for the input data, or any other relevant information was obtained and selected as well as all other measures toinformation on the data used for training, testing and validation,summary about the content used for training of the general-in terms of the training, validation and testing data sets used,

detect the unsuitability of data sources and methods to detect

where applicable, including the type and provenance of data andpurpose AI model, according to a template provided by the AI

data used for training

taking into account the intended purpose of the AI system.

identifiable biases, where applicable;

curation methodologies.

Office.

Contents produced by AI

the content has been artificially generated or manipulatedを講ずること（4号）【8条】
データアノテーションのための生成AI技術の研究開発の過程において、プロバイダーは、本弁法の要求を満たす、データの収集及びアノテーションの手法明確で具体的かつ運用可能なアノテーションルールを策定しなければならない。
第8条

Risk mitigation

the human oversight measures

how your organisation has taken steps to mitigate risks

the computational and hardware resources needed, the expected
Maintenancemaintenance and care measures,

Log

AI Act Article12

Usage of logs

that allows users to properly collect, store and interpret the logs

リスク予防の強化

15条：苦情投稿・通報システム

第11条

lifetime of the high-risk AI system and any necessary

データの品質の維持

a description of the mechanisms included within the AI system
where applicable, information to enable deployers to interpret theInformation for deployer

output of the high-risk AI system and use it appropriately
a description of the mechanisms included within the AI system

Usege of logs by usersthat allows users to properly collect, store and interpret the logs
3.5
複数の下流タスクに最適に適応し、広範な目標のためにビッグデータで学習されたディープニューラル

Foundation models

基盤としているAIモデルに関する情報ネットワークモデル。
【1条】「中華人民共和国サイバーセキュリティ法」、「中華人民共和国データセキュリティ法」、「中華人民共和国個人第4条情報保護法」、「中華人民共和国科学技術促進法」

管理規範、研究開発規範、 【12条】
供給規範、利用規範
AI システム・サービスの提供先や AI 利用者が所在Rules「インターネット情報サービスのアルゴリズム推奨管理規則」
第3条

Measures for AI ethics

AI原則への対応状況の説明

usage policy

the acceptable use policies applicable;

the acceptable use policies applicable;

release datethe date of release and methods of distribution;

the date of release and methods of distribution

modality

the modality (e.g. text, image) and format of inputs and outputs;

the modality (e.g., text, image) and format of inputs and outputs;

achtectures

the architecture and number of parameters;

the architecture and number of parameters;

licensethe licence.

the licence for the model

6つの倫理原則

the technical means (e.g. instructions of use, infrastructure, tools) the technical means (e.g., instructions for use, infrastructure,
how to incorpolate

required for the general-purpose AI model to be integrated in AItools) required for the general-purpose AI model to be integrated

systems

into AI systems;

the design specifications of the model and training process,including training methodologies and techniques, the key design
choices including the rationale and assumptions made; what themodel is designed to optimise for and the relevance of thedesign of models

different parameters, as applicable
the computational resources used to train the model (e.g. numberof floating point operations – FLOPs-), training time, and othercomputational resource

relevant details related to the training;energy cosumption

known or estimated energy consumption of the model.
Where applicable, a detailed description of the measures put inplace for the purpose of conducting internal and/or external
adversarial testing (e.g., red teaming), model adaptations,redteaming

including alignment and fine-tuning.
the versions of relevant software related to the use of therelated softwares

general-purpose AI model, where applicable;
the modality (e.g., text, image, etc.) and format of the inputs andoutputs and their maximum size (e.g., context window length,

outlines of outputs「インターネット情報サービスディープフェイク管理規定」【17条】

する国・地域等において適用される関連法令等etc.);

benefit by AI

what are its benefits,

reason for AI

why your organisation has decided to use AI,