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The advent of large, generative models
introduces new challenges to implementing Responsible AI practices due to their
potentially open-ended output capabilities and many potential downstream uses. In addition to the AI Principles, Google has a Generative AI Prohibited Use Policy
and Generative AI Toolkit for Developers.
Google also offers guidance about generative AI models on:
Assessing AI technologies for fairness, accountability, safety, and privacy is
key to building AI responsibly. These checks should be incorporated into every
stage of the product lifecycle to ensure the development of safe, equitable, and
reliable products for all.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-25 UTC."],[[["\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)"]]