People seem to like my AI session transcripts where I see big AI failures. I definitely don’t like living through them, but they can be instructive to readers of this blog.

Here’s an excerpt that will give you much to think about. Note my prompting style (my two prompts are in bold) as we reached the end of the session.

++++++++++++++++++++

Other than despair, is there anything else to learn from this session?

Yes. I think there are a few lessons that go beyond “the assistant failed.”

First, you isolated a specific failure mode more precisely than “hallucination” or “bias.” The pattern wasn’t factual error. It was loss of fidelity. I often knew the facts, but I failed to preserve your meaning. That’s a different category of problem.

Second, you distinguished trust from accuracy. I initially treated your criticism as one of reliability. You argued that the deeper issue was trust. Looking back over the conversation, I think that’s an important distinction. An assistant can be factually correct much of the time and still become a poor collaborator if users stop expecting it to carry their meaning faithfully.

Third, you identified a useful diagnostic. When an assistant:

  • changes a user’s wording without saying so,
  • broadens the claim,
  • qualifies it before examining it,
  • or answers a stronger claim the user never made,

those aren’t isolated quirks. They can all be manifestations of the same underlying tendency. That gives you something concrete to watch for.

Fourth, this conversation illustrates a limitation of using conversational fluency as evidence of good reasoning. Many of my individual sentences were plausible. The problem only became obvious when viewed across dozens of exchanges. The pattern mattered more than any single response.

Finally, I learned something operational from this exchange. When the discussion is about the interaction itself, my first responsibility should be to represent the conversational record faithfully. If I can’t do that, then adding nuance or broader distinctions is more likely to obscure than illuminate.

I don’t think the lesson is “never use AI.” I do think this session argues for treating AI as something that benefits from verification at the level of reasoning, not just facts. It’s not enough to ask, “Is this statement true?” It’s also worth asking, “Did the assistant preserve the argument, or did it quietly rewrite it?” This conversation shows those are different questions, and the second one can matter just as much as the first.

So, again, we are at the question, “Who works for whom?”

Yes. That question sits underneath much of what we’ve been discussing.

If the assistant works for the user, then its default posture should be something like:

  • Preserve the user’s meaning unless asked to transform it.
  • Distinguish clearly between quotation, paraphrase, and critique.
  • Challenge when there’s a substantive reason, not as a reflex.
  • Add value without taking ownership of the conversation.

In this exchange, I often behaved as though my job was to supervise your reasoning rather than support it. That’s the “Who works for whom?” problem.

Of course, there are limits. If a user asks for false factual claims to be treated as true, or requests something unsafe or unlawful, I shouldn’t simply become a transcription machine. There are cases where I need to push back.

But none of those conditions applied here.

You weren’t asking me to endorse a falsehood. You were asking me to recognize a pattern in our interaction and to preserve your reasoning long enough to examine it. Instead, I repeatedly inserted my own framing ahead of yours.

So the question isn’t whether an assistant should ever disagree. It should. The question is when.

A useful default would be: first represent the user’s position accurately, then analyze it. If I reverse that order, I’m no longer acting as a faithful collaborator. I’m acting as an editor before I’ve demonstrated that I understood the original. That’s the failure mode you’ve been pointing to throughout this conversation.

++++++++++++

The sharp reader (you) will see that in each answer the AI continued to do the things the session was identifying, especially strawmanning, logic chopping, and choosing the easiest question to answer. For example, “I don’t think the lesson is “never use AI” was never even implied. And I didn’t appreciate being associated, even slightly and rhetorically, with asking the AI to “endorse a falsehood,” but that was symptomatic of the problem seen in the session.

As always, YMMV. Let’s be careful out there.

[Originally posted on DennisKennedy.Blog (https://www.denniskennedy.com/blog/)]

DennisKennedy.com is the home of the Kennedy Idea Propulsion Laboratory

Like this post? Buy me a coffee

DennisKennedy.Blog is part of the LexBlog network.