インシデント 83の引用情報

Description: Gmail, Yahoo, Outlook, GMX, and LaPoste email inbox sites showed racial and content-based biases when AlgorithmWatch tested their spam box filtering algorithms.
推定: Gmail , Outlook , Yahoo , GMX LaPosteが開発し提供したAIシステムで、email users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
83
レポート数
1
インシデント発生日
2020-10-15
エディタ
Sean McGregor, Khoa Lam

CSETv0 分類法のクラス

分類法の詳細

Full Description

Gmail, Yahoo, Outlook, GMX, and LaPoste email inbox sites showed racial and content-based biases when AlgorithmWatch tested their spam box filtering algorithms. AlgorithmWatch sent hundreds of emails to 10 email accounts on the listed sites, and noticed emails would be filtered into the spam box if certain words were within the body of the email. A Nigerian students internship application was marked spam, but when the word "Nigeria" was removed it was delivered to the inbox. The same applied to a "sex education" email that was forwarded to inbox after removing "sex". A Joe Biden speech went through when the words "loan, investment, billion" were removed.

Short Description

Gmail, Yahoo, Outlook, GMX, and LaPoste email inbox sites showed racial and content-based biases when AlgorithmWatch tested their spam box filtering algorithms.

Severity

Unclear/unknown

Harm Distribution Basis

Race, National origin or immigrant status

Harm Type

Harm to civil liberties

AI System Description

Machine learning algorithms used to filter spam emails out of inboxes

System Developer

Gmail, Outlook, Yahoo, GMX, LaPoste

Sector of Deployment

Information and communication

Relevant AI functions

Perception, Cognition, Action

AI Techniques

Language recognition, content filtering

AI Applications

spam filtering

Named Entities

Gmail, Yahoo, Outlook, GMX, LaPoste, SpamAssassin, AlgorithmWatch

Technology Purveyor

Gmail, Yahoo, Outlook

Beginning Date

2020-10-22

Ending Date

2020-10-22

Near Miss

Unclear/unknown

Intent

Unclear

Lives Lost

No

Infrastructure Sectors

Communications

Data Inputs

inbound emails

インシデントレポート

レポートタイムライン

Spam filters are efficient and uncontroversial. Until you look at them.
algorithmwatch.org · 2020

An experiment reveals that Microsoft Outlook marks messages as spam on the basis of a single word, such as “Nigeria”. Spam filters are largely unaudited and could discriminate unfairly.

In an experiment, AlgorithmWatch sent a few hundred em…

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

よく似たインシデント

テキスト類似度による

Did our AI mess up? Flag the unrelated incidents