CSETv0
GMF分類とは何か?
GMF(Goals, Methods, and Failures:目標、方法、失敗)分類は、システムの展開の目標、システムの方法、およびそれらの可能性のある失敗を相互に関連付ける失敗原因分析分類です。 このプロセスの詳細は、SafeAI論文で最近発表された作業で利用可能です。
分類をどのように探索しますか?
すべての分類は、Discoverアプリケーション内でインシデントレポートをフィルタリングするために使用できます。分類フィルターは、Eコマースウェブサイトで製品をフィルタリングする方法と同様に機能します。「分類」タブの下部にある検索フィールドを使用して、フィルタリングしたい分類フィールドを見つけ、希望する値をクリックしてフィルターを適用します。
責任あるAIコラボレーションについて
AIインシデントデータベースは、多くの人々と組織の共同プロジェクトです。この特定の分類に貢献している人々と組織の詳細はここに表示されますが、コラボ自体については、インシデントデータベースのホームペー ジおよび約ページで詳しく知ることができます。
この分類のメンテナーには、以下の方々が含まれます。
分類フィールド
Overall severity of harm Discoverアプリケーションで検索可能
定義: An estimate of the overall severity of harm caused. "Negligible" harm means minor inconvenience or expense, easily remedied. “Minor” harm means limited damage to property, social stability, the political system, or civil liberties occurred or nearly occurred. "Moderate" harm means that humans were injured (but not killed) or nearly injured, or that financial, property, social, or political interests or civil liberties were materially affected (or nearly so affected). "Severe" harm means that a small number of humans were or were almost gravely injured or killed, or that financial, property, social, or political interests or civil liberties were significantly disrupted at at least a regional or national scale (or nearly so disrupted). "Critical" harm means that many humans were or were almost killed, or that financial, property, social, or political interests were seriously disrupted at a national or global scale (or nearly so disrupted).
Uneven distribution of harms basis Discoverアプリケーションで検索可能
定義: If harms were unevenly distributed, this field indicates the basis or bases on which they were unevenly distributed.
Harm type Discoverアプリケーションで検索可能
- Harm to social or political systems19 インシデント
- Psychological harm18 インシデント
- Harm to physical health/safety17 インシデント
- Harm to civil liberties16 インシデント
- Financial harm12 インシデント
定義: Indicates the type(s) of harm caused or nearly caused by the incident.
System developer Discoverアプリケーションで検索可能
定義: The entity that created the AI system.
Sector of deployment Discoverアプリケーションで検索可能
定義: The primary economic sector in which the AI system(s) involved in the incident were operating.
Relevant AI functions Discoverアプリケーションで検索可能
定義: Indicates whether the AI system(s) were intended to perform any of the following high-level functions: "Perception," i.e. sensing and understanding the environment; "Cognition," i.e. making decisions; or "Action," i.e. carrying out decisions through physical or digital means.
AI tools and techniques used Discoverアプリケーションで検索可能
- machine learning19 インシデント
- Facial recognition6 インシデント
- open-source6 インシデント
- natural language processing5 インシデント
- environmental sensing5 インシデント
定義: Open-ended tags that indicate the hardware and software involved in the AI system(s).
AI functions and applications used Discoverアプリケーションで検索可能
- decision support10 インシデント
- autonomous driving9 インシデント
- recommendation engine9 インシデント
- Facial recognition8 インシデント
- image recognition8 インシデント
定義: Open-ended tags that describe the functions and applications of the AI system.
Location Discoverアプリケーションで検索可能
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定義: The location or locations where the incident played out.
Named entities Discoverアプリケーションで検索可能
定義: All named entities (such as people, organizations, locations, and products - generally proper nouns) that seem to have a significant relationship with this event, as indicated by the available evidence.
Party responsible for AI system Discoverアプリケーションで検索可能
定義: A list of parties (up to three) that were responsible for the relevant AI tool or system, i.e. that had operational control over the AI-related system causing harm (or control over those who did).
Harm nearly missed? Discoverアプリケーションで検索可能
定義: Was harm caused, or was it a near miss?
Probable level of intent Discoverアプリケーションで検索可能
定義: Indicates whether the incident was deliberate/expected or accidental, based on the available evidence. "Deliberate or expected" applies if it is established or highly likely that the system acted more or less as expected, from the perspective of at least one of the people or entities responsible for it. “Accident” applies if it is established or highly likely that the harm arose from the system acting in an unexpected way. "Unclear" applies if the evidence is contradictory or too thin to apply either of the above labels.
Human lives lost Discoverアプリケーションで検索可能
定義: Marked "trur" if one or more people died as a result of the accident, "false" if there is no evidence of lives being lost, "unclear" otherwise.
Critical infrastructure sectors affected Discoverアプリケーションで検索可能
- Transportation10 インシデント
- Healthcare and public health4 インシデント
- Communications2 インシデント
- Government facilities2 インシデント
- Information technology1 インシデント
定義: Where applicable, this field indicates if the incident caused harm to any of the economic sectors designated by the U.S. government as critical infrastructure.
Public sector deployment Discoverアプリケーションで検索可能
定義: "Yes" if the AI system(s) involved in the accident were being used by the public sector or for the administration of public goods (for example, public transportation). "No" if the system(s) were being used in the private sector or for commercial purposes (for example, a ride-sharing company), on the other.
Nature of end user Discoverアプリケーションで検索可能
定義: "Expert" if users with special training or technical expertise were the ones meant to benefit from the AI system(s)’ operation; "Amateur" if the AI systems were primarily meant to benefit the general public or untrained users.
Level of autonomy Discoverアプリケーションで検索可能
定義: The degree to which the AI system(s) functions independently from human intervention. "High" means there is no human involved in the system action execution; "Medium" means the system generates a decision and a human oversees the resulting action; "low" means the system generates decision-support output and a human makes a decision and executes an action.
Physical system Discoverアプリケーションで検索可能
- Software only66 インシデント
- Vehicle/mobile robot16 インシデント
- Consumer device7 インシデント
- Unknown/unclear2 インシデント
- Other:Medical system1 インシデント
定義: Where relevant, indicates whether the AI system(s) was embedded into or tightly associated with specific types of hardware.
Causative factors within AI system Discoverアプリケーションで検索可能
定義: Indicates which, if any, of the following types of AI failure describe the incident: "Specification," i.e. the system's behavior did not align with the true intentions of its designer, operator, etc; "Robustness," i.e. the system operated unsafely because of features or changes in its environment, or in the inputs the system received; "Assurance," i.e. the system could not be adequately monitored or controlled during operation.
Full description of the incident
定義: A plain-language description of the incident in one paragraph or less.
Short description of the incident
定義: A one-sentence description of the incident.
Description of AI system involved
定義: A brief description of the AI system(s) involved in the incident, including the system’s intended function, the context in which it was deployed, and any available details about the algorithms, hardware, and training data involved in the system.
Beginning date
定義: The date the incident began.
Ending date
定義: The date the incident ended.
Total financial cost
定義: The stated or estimated financial cost of the incident, if reported.
Laws covering the incident
定義: Relevant laws under which entities involved in the incident may face legal liability as a result of the incident.
Description of the data inputs to the AI systems
定義: A brief description of the data that the AI system(s) used or were trained on.