下一個挑戰
透過集合功能整理內容
你可以依據偏好儲存及分類內容。
大型生成式模型的出現,讓導入負責任 AI 做法面臨新的挑戰,因為這些模型可能具有無限的輸出功能,且有許多潛在的後端用途。除了 AI 原則外,Google 還有《生成式 AI 使用限制政策》和《開發人員專用生成式 AI 工具包》。
Google 也會在以下網站提供生成式 AI 模型相關指南:
摘要
評估 AI 技術的公平性、問責性、安全性和隱私權,是負責任開發 AI 技術的關鍵。這些檢查應納入產品生命週期的每個階段,確保開發出安全、公平且可靠的產品,讓所有人都能享有這項服務。
更多學習資源
Google AI:我們專注於 AI 的原因
Google 生成式 AI
PAIR Explorable:語言模型學到了什麼?
負責任的 AI 技術工具包 | TensorFlow
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上次更新時間:2025-07-27 (世界標準時間)。
[null,null,["上次更新時間:2025-07-27 (世界標準時間)。"],[[["\u003cp\u003eGenerative AI models present new challenges to Responsible AI due to their open-ended output and varied uses, prompting the need for guidelines like Google's Generative AI Prohibited Use Policy and Toolkit for Developers.\u003c/p\u003e\n"],["\u003cp\u003eGoogle provides further resources on crucial aspects of generative AI, including safety, fairness, prompt engineering, and adversarial testing.\u003c/p\u003e\n"],["\u003cp\u003eBuilding AI responsibly requires thorough assessment of fairness, accountability, safety, and privacy throughout the entire product lifecycle.\u003c/p\u003e\n"],["\u003cp\u003eGoogle emphasizes the importance of Responsible AI and offers additional resources like the AI Principles, Generative AI information, and toolkits for developers.\u003c/p\u003e\n"]]],[],null,["# The next challenge\n\n\u003cbr /\u003e\n\nThe advent of large, generative models\nintroduces new challenges to implementing Responsible AI practices due to their\npotentially open-ended output capabilities and many potential downstream uses. In addition to the AI Principles, Google has a [Generative AI Prohibited Use Policy](https://policies.google.com/terms/generative-ai/use-policy)\nand [Generative AI Toolkit for Developers](https://ai.google.dev/responsible/docs).\n\nGoogle also offers guidance about generative AI models on:\n\n- [Safety](https://ai.google.dev/gemini-api/docs/safety-guidance)\n- [Prompt Engineering](/machine-learning/resources/prompt-eng)\n- [Adversarial Testing](/machine-learning/guides/adv-testing)\n\nSummary\n-------\n\nAssessing AI technologies for fairness, accountability, safety, and privacy is\nkey to building AI responsibly. These checks should be incorporated into every\nstage of the product lifecycle to ensure the development of safe, equitable, and\nreliable products for all.\n\nFurther learning\n----------------\n\n[Why we focus on AI -- Google AI](https://ai.google/why-ai/)\n\n[Google Generative AI](https://ai.google/discover/generativeai/)\n\n[PAIR Explorable: What Have Language Models Learned?](https://pair.withgoogle.com/explorables/fill-in-the-blank/)\n\n[Responsible AI Toolkit \\| TensorFlow](https://www.tensorflow.org/responsible_ai)"]]