Synthetic Media Provenance Kit

AI生成の映像と音声に、検証可能な来歴を与える。

AI生成の映像・音声に透かし、メタデータ、開示声明を付与する実践キット。Genie 4のすべての出力に含まれるとGoogleが説明する透かしシステム、SynthIDを基盤に。

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AI生成メディアを共有するクリエイター、マーケター、パブリッシャー

所要時間

アセット1件につき15分

レベル

中級

3ステップでインストール

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Pro — 全531件のスキル

ご自分で入れたい場合は、スキルを購入（$4.99）し、購入完了画面からZIPをダウンロードして、上のディレクトリに展開し、AIのセッションを再起動してください。結果は同じです。すでに購入済みの場合は、AIアシスタントにダウンロードしてもらうこともできます。

パックの内容

SKILL.md（手順書）1点とスターターテンプレート1点が入っています。プレビューはこちらです：

Synthetic Media Provenance Kit

The idea in one paragraph

When a world model can generate two minutes of photorealistic video with native audio in real time, the question stops being "can it fool someone" and starts being "can we prove where it came from." This skill is a provenance kit: a repeatable checklist for attaching watermarks, metadata, and plain-language disclosures to synthetic video and audio, anchored on SynthID — the watermark Google states all Genie 4 generations carry.

What it is built on

Per DeepMind's October 27, 2026 announcement, all generated video and audio from Genie 4 carry SynthID watermarks.
Genie 4 is described as the first world model with natively generated real-time audio — ambience, music, and interactive dialogue — per Google's announcement; reporting notes (datanorth.ai) that Runway's earlier GWM Worlds 2 also ships playable worlds with audio, so the "first" claim is Google's own framing, not settled fact.
Genie 4 is a research preview for trusted testers with a waitlist; access is planned for Google AI Ultra subscribers (inside Project Genie) and early Gemini API / AI Studio partners. No dates, prices, or published benchmarks were announced.

Workflow

Inventory the asset (input: media file -> output: asset record). Note the generator, model name and date, prompt or seed, and who produced it. Provenance starts with knowing what you have.
Verify the built-in watermark (input: asset record -> output: watermark status). Check whether the platform's native watermark (e.g., SynthID for Genie 4 outputs) is present and intact. Record the check; do not assume it survived editing.
Attach portable metadata (input: asset -> output: tagged file). Add creator, generation date, model, and prompt summary into the file's metadata or an accompanying manifest. Metadata travels where watermarks sometimes do not.
Write the disclosure line (input: asset record -> output: disclosure text). Draft one plain sentence: what is AI-generated and what is not. Put it where the audience will actually see it — caption, description, or first comment.
Lock the chain (input: tagged file + disclosure -> output: publish package). Keep an unedited original alongside the published version, and record both hashes or IDs. If someone questions the asset, you can show the chain.
Recheck after edits (input: edited version -> output: updated package). Every cut, re-encode, or re-upload can strip watermarks and metadata. Re-verify after any edit and update the record.