インシデント 167の引用情報

Description: Researchers at Stanford Graduate School of Business developed a model that determined, on a binary scale, whether someone was homosexual using only his facial image, which advocacy groups such as GLAAD and the Human Rights Campaign denounced as flawed science and threatening to LGBTQ folks.

組織

すべての組織を表示
Alleged: Michal Kosinski と Yilun Wang developed and deployed an AI system, which harmed LGBTQ people , LGBTQ people of color と non-American LGBTQ people.

インシデントのステータス

インシデントID
167
レポート数
1
インシデント発生日
2017-09-07
エディタ
Sean McGregor, Khoa Lam
Applied Taxonomies
GMF, CSETv1_Annotator-1, CSETv1_Annotator-2

CSETv1_Annotator-1 分類法のクラス

分類法の詳細

Incident Number

167

Special Interest Intangible Harm

yes

CSETv1_Annotator-2 分類法のクラス

分類法の詳細

Incident Number

167

Notes (special interest intangible harm)

The algorithm was meant to discern, from facial images, if people were gay.

Special Interest Intangible Harm

maybe

GMF 分類法のクラス

分類法の詳細

Known AI Goal Snippets

(Snippet Text: Presented with photos of gay men and straight men, a computer program was able to determine which of the two was gay with 81 percent accuracy, according to Dr. Kosinski and co-author Yilun Wang’s paper., Related Classifications: Behavioral Modeling, Snippet Discussion: Pairwise classification)

インシデントレポート

レポートタイムライン

Incident OccurrenceWhy Stanford Researchers Tried to Create a ‘Gaydar’ Machine
Why Stanford Researchers Tried to Create a ‘Gaydar’ Machine
nytimes.com · 2017

Michal Kosinski felt he had good reason to teach a machine to detect sexual orientation.

An Israeli start-up had started hawking a service that predicted terrorist proclivities based on facial analysis. Chinese companies were developing fac…

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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