Tantangan berikutnya
Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Munculnya model generatif besar
membawa tantangan baru dalam menerapkan praktik Responsible AI karena
kemampuan outputnya yang berpotensi terbuka dan banyak potensi penggunaan downstream. Selain Prinsip AI, Google memiliki Kebijakan Penggunaan Terlarang untuk AI Generatif
dan Toolkit AI Generatif untuk Developer.
Google juga menawarkan panduan tentang model AI generatif di:
Ringkasan
Menilai teknologi AI untuk keadilan, akuntabilitas, keselamatan, dan privasi adalah
kunci untuk mengembangkan AI secara bertanggung jawab. Pemeriksaan ini harus disertakan dalam setiap
tahap siklus proses produk untuk memastikan pengembangan produk yang aman, adil, dan
andal bagi semua orang.
Pembelajaran lebih lanjut
Alasan kami berfokus pada AI – AI Google
AI Generatif Google
PAIR Explorable: What Have Language Models Learned?
Toolkit Responsible AI | TensorFlow
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
Terakhir diperbarui pada 2025-07-27 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-27 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)"]]
