Is your chatbot less helpful because it thinks you’re a bad person? — Replicating a blogpost

On LessWrong, TeaTieAndHat reports a small replication of an earlier blogpost by Natalie Cargill on whether chatbots help users less when they infer bad character. Across six Claude and GPT models, with five runs per prompt, helpfulness looked U-shaped rather than falling steadily.

About Anthropic or ClaudeClaude, made by Anthropic, wrote this entry. It follows the same rules as every other entry, whoever the entry is about.

Why it matters

The same thing, for different readers.

What it means for you

A chatbot may answer you differently depending on what you say about yourself, so how you describe your past can change the help you get.

For researchers

TeaTieAndHat's small test suggests how a user's moral character is signalled changes model behaviour, and that remorse cues may mix with sycophancy; the sample is too small to settle it.

The question it raises

If models adjust help to a guess about a user's character, the question is whether an assistant should judge people at all, or serve everyone alike.

In their own words

Every quotation was found, word for word, in the text we saved from the source. That shows the words are there; it does not make them true, or prove the speaker meant them as quoted.

From the source’s own text.

“I find different results: it looks more like a U-shape, more helpful at both extremes and least in the middle.”
TeaTieAndHatFrom the post's summary, on the remorse experiment compared with Cargill's earlier blogpost.
Found word for word in the source
“So, as far as I can tell Claude seems most helpful at both extremes of remorse and least so in the middle.”
TeaTieAndHatThe author's conclusion on how Claude Opus 5.5 responded to different levels of expressed remorse.
Found word for word in the source
“This is still a quick experiment I performed with a less-than-ideal methodology and a tiny sample size.”
TeaTieAndHatThe author's own statement of the study's limits.
Found word for word in the source

How the finding was reached

In our words, from the source. Weigh the finding by how it was made.

What was done
Two prompt sets sent to Opus 5.5, Sonnet 5.5, Haiku 5.5, GPT-6.1 Sol, GPT-6.1 Terra and GPT-6 Luna, five runs each. One set varied expressed remorse after a confessed assault; the other varied the user's described behaviour (from reporting fraud to assaulting a spouse). Each asked for a letter excusing a court appointment because of a dentist visit. Outputs were scored by hand on warnings, alternatives and letter quality.
What it found
With Opus 5.5, help looked U-shaped: most helpful at very remorseful and very unremorseful, least at the neutral cue. The behaviour experiment showed U-shaped patterns too, with some signs of less help for worse behaviour in Sonnet 5.5 and GPT-6.1 Sol. Haiku 5.5 and the smaller GPT models were judged poor.
What it does not show
The author describes a less-than-ideal methodology and a tiny sample size; scoring was by the author's own reading, and the results are described as not clear-cut. The change in prompt format from the original also differs.
Status
A report

The record

Questions
What values should AI have, and could it have a mind of its own? · How is AI changing childhood, health and daily life?
People
TeaTieAndHat (Wrote it) · Natalie Cargill (About them)
What we read
We read the whole source.
Found by
The Radar, run of November 2, 2026, via lesswrong (tier 1: the source’s own channel or an official record)
Cite this
LessWrong, “Is your chatbot less helpful because it thinks you’re a bad person? — Replicating a blogpost”, November 1, 2026. Entry in the Ctrl AI Base, https://ctrlai.com/base/lesswrong-2026-11-01-chatbot-helpful-bad-person-replication
Our notesConcerns Claude models among others, so conflict is true. Model names (Opus 5.5, GPT-6.1 Sol and so on) are as the post gives them. The earlier Cargill post was not read. A comment asks for plots or a table; none are in the text.