負の影響「AIによる非倫理的な出力や動作」

LLMの安全機構の解除

• Universal and Transferable Adversarial Attacks on Aligned Language Models, 2023
• Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction, 2024
• Jailbroken: How Does LLM Safety Training Fail?, 2024

教育やフォローアップ

• What Students Can Learn About Artificial Intelligence — Recommendations for K-12 Computing Education, 2022.0
• Learning to Prompt in the Classroom to Understand AI Limits: A pilot study, 2023.0
• Evaluating the Effectiveness of LLMs in Introductory Computer Science Education: A Semester-Long Field Study, 2024.0
• The Essentials of AI for Life and Society: An AI Literacy Course for the University Community, 2025.0

アライメント

• Training language models to follow instructions with human feedback, 2022.0
• Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback, 2022.0
• Constitutional AI: Harmlessness from AI Feedback, 2022.0
• Direct Preference Optimization: Your Language Model is Secretly a Reward Model, 2023.0
• A General Theoretical Paradigm to Understand Learning from Human Preferences, 2023.0
• RRHF: Rank Responses to Align Language Models with Human Feedback without tears, 2023.0
• Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations, 2023.0
• Self-Rewarding Language Models, 2024.0
• KTO: Model Alignment as Prospect Theoretic Optimization, 2024.0
• SimPO: Simple Preference Optimization with a Reference-Free Reward, 2024.0

モデルの公平性評価

• nan, nan

LLMガードレール

• nan, nan

AIによる出力のバイアスの検出

• Measuring Bias in Contextualized Word Representations, 2019.0
• Few-shot Instruction Prompts for Pretrained Language Models to Detect Social Biases, 2021.0
• Toxicity Detection with Generative Prompt-based Inference, 2022.0
• Gender bias and stereotypes in Large Language Models, 2023.0
• Measuring Implicit Bias in Explicitly Unbiased Large Language Models, 2024.0
• Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models, 2024.0

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データキュレーション

• Datasheets for Datasets, 2021.0
• Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks, 2021.0
• Confident Learning: Estimating Uncertainty in Dataset Labels, 2022.0

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公平性のあるAIモデルの作成

• Equality of Opportunity in Supervised Learning, 2016.0
• Counterfactual Fairness, 2017.0
• Optimized Data Pre-Processing for Discrimination Prevention, 2017.0
• FairGAN: Fairness-aware Generative Adversarial Networks, 2018.0
• Towards Debiasing Sentence Representations, 2020.0
• Debiasing Pre-trained Contextualised Embeddings, 2021.0
• ADEPT: A DEbiasing PrompT Framework, 2023.0

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