視覚的な生成AIの交差点分析:安定した拡散のケース
Petra Jääskeläinen1, Nickhil Kumar Sharma2,3, Helen Pallett2
1Division of Media Technology and Interaction Design, Department of Human-Centered Technology, EECS, KTH Royal Institute of Technology, Stockholm, Sweden.
まとめ
ビジュアル・ジェネラティブ・AI (vGenAI) のツールでは 社会的権力構造を反映することで 人種差別やセクシズムを含む有害なバイアスを永続化させています この研究は,vGenAIの開発と展開に社会的正義のアプローチを求めています.
科学分野:
- コンピュータ科学
- 社会学
- メディア研究
背景:
- ビジュアル・ジェネラティブ・AI (vGenAI) ツールは,フォトリアリスティックな画像作成に迅速に採用されています.
- これらの技術は 社会的偏見や権力構造を反映し 永続させることができます
- Stable Diffusion (SD) は重要なオープンソースのvGenAIツールであり,批判的な検討が必要である.
研究 の 目的:
- ステーブル・ディフュージョン (SD) で生成された画像の美学と底辺のパワー・システムを批判的に分析する.
- 人種差別,セクシズム,植民地主義などの社会的不平等を永続化させる方法を調査する.
- vGenAIの開発に社会正義を重視したアプローチを提案する.
主な方法:
- SDで生成された180枚の画像の視覚と断面分析.
- フェミニストの科学技術研究,ビジュアルメディア研究, 批判的理論に基づいています.
- 審美学,制度的文脈,そして電力システムの交差点を検討する.
主要な成果:
- SDのイメージは 性差別,人種差別,ヘテロノーマティビズム,能力主義を永続させています
- 作成された画像は 通常は 白人,健常,男性的な表現になります
- ヨーロッパと北米を中心とした文化表現への傾向が確認された.
結論:
- SDのようなvGenAIのツールは 文化的にも美学的にも 中立ではありません
- これらの技術を通して,有害で暴力的なイメージが絶えず再現されています.
- vGenAIの被害に対処するには 修復的で社会正義を重視したアプローチが必要です
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