What qualifications do AI-generated images for AI illustration and AI painting need to pass before being used in the formal release of articles?

AI illustration and AI painting generated images, before putting them into formal published articles, it is recommended to go through three checks: first, check if the image is consistent with the text, then check if there are any disordered details and copyright risks in the picture, and finally verify the title, keywords, description, and automatic tags generated by the same batch of actions.AnQiCMS put these steps in the content chain: when creating an article, you can automatically match the title with an image, you can also call AI painting to generate images, and you can also generate tags and TDK synchronously;The generated result enters the pending release status, the formal document's wording is determined by the release action, and manual review falls between these in and out.

To what extent does illustration automation cover

The in-site image matching ability is divided into two layers. One layer is automatic title image matching: the system allocates images from the materials based on the title content, which is fast and the results are predictable, suitable for information and batch content. The other layer is AI painting: generates images according to the semantics of the text, with new images and new risks accordingly - it has no real counterparts and details are prone to errors. There are also automatic tags in the same batch of generation tasks, and the tags often share the understanding of the article with the image matching. When the image goes off track, the tags are likely to go off track as well, so both should be reviewed together in one check, and not checked separately.

Three items to be confirmed by humans before publication

The first item is the consistency between image and text. When the scene conveyed by the image does not match the theme of the text, the reader will immediately notice, and the search engine and content understanding program will also regard this mismatch as a low-quality signal. The inspection method is very direct: just look at the image and title, can you tell what the article is about.

The second item is the detail of the image. Common problems with AI-generated images are distorted text, disordered fingers and structures, and distorted identification and characters. False identification may also involve copyright judgment, and images involving brand and portrait should be more cautious. This step is difficult to replace by mechanical rules, and it is cost-effective to have a human eye check it once.

The third item is derived metadata. The title, keywords, description, and automatic tags are all generated in the same batch, and these fields are easy to lag behind after the text has been changed. When checking, pay special attention to whether the description can stand independently of the text, as it is often directly cited as the answer.

How can the audit route be guaranteed?

After generation, it is not released in the raw form. The sensitive word filtering and keyword replacement in the content security settings take effect uniformly on the title, description, and body at the saving and publishing stages, and the text generated by AI also goes through this set of rules to reduce the content with diseases going online directly. The document status is divided into draft, to be published, and formal documents; the draft can be confirmed internally with a preview link before becoming formal; the deleted formal documents enter the recycling bin instead of being physically deleted, and the deleted items can be restored.

The timing release solves the rhythm problem, not the review problem. If no review window is left before the release, the timing task will push the unreviewed images and text online at points. The safe approach is to separate the release time and the review time, leaving room for spot checks.

Common questions

Question: Do automatic image matching and AI painting need to review the same list?Answer: The list is the same, but the focus is different. Automatic image matching focuses on whether the allocation is on topic and within the scope of material authorization; AI painting focuses on the details of the image and whether recognizable real identifiers appear.

Question: If the images and text have passed the sensitive word filter, do we still need to be reviewed by humans?Answer: The filtering rules handle high-risk words in the text dimension, and errors in the content, style misalignment, and copyright clues are outside the scope of the rules, and still need to be confirmed by looking at the image.

Question: If you find a problem with the illustration after sending it out, how can you补救 with minimal cost?Answer: Simply replace or remove the image in the document and go through the publication process again; if the document is mistakenly deleted, you can recover it from the recycle bin and then make changes, without worrying about permanent loss of content.