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AI Utility Engineering and Value Systems
This chapter investigates a research paper on 'Utility Engineering,' focusing on the emergent value systems in AI during training. It highlights biases in AI models like GPT-40, examining how utility functions influence decision-making and the implications of training data. Additionally, it discusses the release of a risk management framework by XAI aimed at assessing potential AI-related threats, emphasizing the importance of transparency and accountability.