Description: Evidence of the "filter-bubble effect" were found by vaccine-misinformation researchers in Amazon's recommendations, where its algorithms presented users who performed actions on misinformative products with more misinfomative products.
Alleged: Amazon developed and deployed an AI system, which harmed Amazon Customers.
インシデントのステータス
インシデントID
139
レポート数
2
インシデント発生日
2021-01-21
エディタ
Sean McGregor, Khoa Lam
Applied Taxonomies
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.
139
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
2021
Date of Incident Month
The month 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 month, estimate. Otherwise, leave blank.
Enter in the format of MM
01
Date of Incident Day
The day on which the incident occurred. If a precise date is unavailable, leave blank.
Enter in the format of DD
21
Estimated Date
“Yes” if the data was estimated. “No” otherwise.
Yes
CSETv1_Annotator-1 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.
139
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
2021
Date of Incident Month
The month 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 month, estimate. Otherwise, leave blank.
Enter in the format of MM
01
Estimated Date
“Yes” if the data was estimated. “No” otherwise.
No
Multiple AI Interaction
“Yes” if two or more independently operating AI systems were involved. “No” otherwise.
no
CSETv1_Annotator-2 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.
139
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
2021
Date of Incident Month
The month 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 month, estimate. Otherwise, leave blank.
Enter in the format of MM
01
Date of Incident Day
The day on which the incident occurred. If a precise date is unavailable, leave blank.
Enter in the format of DD
21
Estimated Date
“Yes” if the data was estimated. “No” otherwise.
No
インシデントレポート
レポートタイムライン
arxiv.org · 2021
- 情報源として元のレポートを表示
- インターネットアーカイブでレポートを表示
Abstract: There is a growing concern that e-commerce platforms are amplifying vaccine-misinformation. To investigate, we conduct two-sets of algorithmic audits for vaccine misinformation on the search and recommendation algorithms of Amazon…
iol.co.za · 2021
- 情報源として元のレポートを表示
- インターネットアーカイブでレポートを表示
New York - Amid growing concern that e-commerce platforms are amplifying vaccine-misinformation, a new study by researchers at University of Washington has found that Amazon hosts a large number of misinformative products belonging to categ…
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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