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インシデント 75: Google Instant's Allegedly 'Anti-Semitic' Results Lead To Lawsuit In France

概要: The organizations SOS Racisme, Union of Jewish Students of France, Movement Against Racism and for Friendship Among Peoples are suing Google due to its autocomplete software suggesting "jewish" when the names of certain public figures were searched on the platform.

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組織

すべての組織を表示
推定: Googleが開発し提供したAIシステムで、Jewish people と Jewish public figuresに影響を与えた

インシデントのステータス

インシデントID
75
レポート数
1
インシデント発生日
2012-01-05
エディタ
Sean McGregor, Khoa Lam
Applied Taxonomies
CSETv0, CSETv1, GMF, MIT

CSETv1 分類法のクラス

分類法の詳細

Incident Number

The number of the incident in the AI Incident Database.
 

75

Notes (special interest intangible harm)

Input any notes that may help explain your answers.
 

Google search results auto-filled "Jewish" after the names of certain Jewish public figures, a phenomenon not observed with public figures of other religions.

Special Interest Intangible Harm

An assessment of whether a special interest intangible harm occurred. This assessment does not consider the context of the intangible harm, if an AI was involved, or if there is characterizable class or subgroup of harmed entities. It is also not assessing if an intangible harm occurred. It is only asking if a special interest intangible harm occurred.
 

yes

Date of Incident Year

The year in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the year, estimate. Otherwise, leave blank. Enter in the format of YYYY
 

2012

CSETv0 分類法のクラス

分類法の詳細

Problem Nature

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.
 

Unknown/unclear

Physical System

Where relevant, indicates whether the AI system(s) was embedded into or tightly associated with specific types of hardware.
 

Software only

Level of Autonomy

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.
 

Medium

Nature of End User

"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.
 

Amateur

Public Sector Deployment

"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.
 

No

Data Inputs

A brief description of the data that the AI system(s) used or were trained on.
 

user searches

MIT 分類法のクラス

Machine-Classified
分類法の詳細

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

1.1. Unfair discrimination and misrepresentation

Risk Domain

The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
 
  1. Discrimination and Toxicity

Entity

Which, if any, entity is presented as the main cause of the risk
 

AI

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Post-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Unintentional

インシデントレポート

レポートタイムライン

+1
Google Instant's Allegedly 'Anti-Semitic' Results Lead To Lawsuit In France
Google Instant's Allegedly 'Anti-Semitic' Results Lead To Lawsuit In France

Google Instant's Allegedly 'Anti-Semitic' Results Lead To Lawsuit In France

huffingtonpost.co.uk

Google Instant's Allegedly 'Anti-Semitic' Results Lead To Lawsuit In France
huffingtonpost.co.uk · 2012

A new lawsuit alleges that Google's search engine has an anti-Semitism problem.

French anti-discrimination organization SOS Racisme, in association with the Union of Jewish Students of France, the Movement Against Racism and for Friendship …

バリアント

「バリアント」は既存のAIインシデントと同じ原因要素を共有し、同様な被害を引き起こし、同じ知的システムを含んだインシデントです。バリアントは完全に独立したインシデントとしてインデックスするのではなく、データベースに最初に投稿された同様なインシデントの元にインシデントのバリエーションとして一覧します。インシデントデータベースの他の投稿タイプとは違い、バリアントではインシデントデータベース以外の根拠のレポートは要求されません。詳細についてはこの研究論文を参照してください

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テキスト類似度による

Did our AI mess up? Flag the unrelated incidents

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