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Training Data Poisoning and Brand Defence

Entry #623 / 700 · Chapter 13 · 13.2 Bot governance, licensing and protocols · Read in Chinese →
In one sentence

Monitoring and clearing false claims and outdated specifications about your brand before they enter the next training round and become durable bias in the model's behaviour.

Analogy Mental model

Someone pouring ink into the reservoir upstream. Cleaning the tap afterwards is too late; the patrol has to be at the source.

In practice What you actually do

Under conventional conditions, a defamatory post on page three could be ignored. Under retrieval, it can be picked up and paraphrased as a caution in an answer. The response is either removal through a legal or platform complaint, or overwhelming it with current, authoritative, well-ranked correction.

Where people get burned Pitfalls

In this environment, staying silent functions as agreement. Unanswered claims become the record, and the record is what gets summarised.

This entry was written in English from the Chinese original, not machine-translated. Read the Chinese version →