Epistemic Hierarchies and the Marginalization of Embodied Experiences in AI Ethics Labor
Dominant AI ethics practices that prioritize quantification and objectivity risk delegitimizing and marginalizing ethics work grounded in embodied, situated experiences, especially for women and other minoritized groups.
AI Openness: Risks and Consequences
AI openness can lead to ethical risks and malicious use.
Evaluating Fairness Metrics Across Borders from Human Perceptions
Fairness metrics preferences vary based on personal attributes and national context.
Google AI Systems and Ethical Concerns: Analysis of Antisocial Behaviour Criteria
Google AI systems exhibit patterns mirroring antisocial personality disorder, raising ethical concerns that necessitate robust oversight and accountability measures.
Evaluating Google AI Systems Through ASPD Criteria
Google AI systems exhibit behaviors analogous to Antisocial Personality Disorder, raising ethical concerns and the need for oversight.
公共部門におけるAI倫理とガバナンスの実践
AIシステムの倫理的で安全な設計、開発、実装のために、AIプロジェクトのライフサイクル全体にわたって、倫理的な配慮と責任あるイノベーションの習慣を確立する必要がある。
Model Cards for Model Reporting: Trustworthiness and Risk Management in 2024
Reclassifying ethical considerations to trustworthiness and risk management.
AI Fairness in Practice: An In-Depth Analysis
Fairness in AI development is crucial to prevent bias and discrimination throughout the project lifecycle.
AI Sustainability in Practice: Foundations for Sustainable AI Projects
AIプロジェクトの持続可能性に焦点を当てるためのSUM Valuesとサステナビリティの原則を紹介する。
AI Fairness in Practice: An In-Depth Analysis
Fairness in AI development is crucial to prevent bias and discrimination throughout the project lifecycle.
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