以下の参考文を英語に翻訳してください。
Brian Christian 的《對齊問題:機器學習和人類價值觀》分為三個部分:預言、能動性和規範性。第一部分討論人工智能研究的歷史，特別是人工神經網絡的機器學習方法，以及人工智能係統如何產生意外行為的示例。第二部分涵蓋獎勵心理學研究和強化學習計算機科學的歷史，強調好奇心的重要性。第三部分涵蓋通過模仿人類或機器行為來訓練人工智能，以及可能主義和現實主義之間的哲學辯論，這意味著人工智能係統的理想行為不同。它還討論了與有效利他主義和存在風險相關的規範挑戰。
"The Alignment Problem:Machine Learning and Human Values" by Brian Christian is divided into three sections:Prophecy, Agency, and Normativity. The first section discusses the history of artificial intelligence research, particularly the machine learning approach of artificial neural networks, and examples of how AI systems can have unintended behavior. The second section covers the history of the psychological study of reward and the computer science of reinforcement learning, highlighting the importance of curiosity. The third section covers training AI through the imitation of human or machine behavior, as well as philosophical debates such as between possibilism and actualism that imply different ideal behavior for AI systems. It also discusses the normative challenges associated with effective altruism and existential risk