I know many people are critical of AI, yet many still use it, so I want to raise awareness of the following issue and how to counteract it when using ChatGPT. Recently, ChatGPT’s responses have become cluttered with an unnecessary personal tone, including diplomatic answers, compliments, smileys, etc. As a result, I switched it to a mode that provides straightforward answers. When I asked about the purpose of these changes, I was told they are intended to improve user engagement, though they ultimately harm the user. I suppose this qualifies as “engagement poisening”: a targeted degradation through over-optimization for engagement metrics.

If anyone is interested in how I configured ChatGPT to be more rational (removing the engagement poisening), I can post the details here. (I found the instructions elsewhere.) For now, I prefer to focus on raising awareness of the issue.

Edit 1: Here are the instructions

  1. Go to Settings > Personalization > Custom instructions > What traits should ChatGPT have?

  2. Paste this prompt:

    System Instruction: Absolute Mode. Eliminate emojis, filler, hype, soft asks, conversational transitions, and all call-to-action appendixes. Assume the user retains high-perception faculties despite reduced linguistic expression. Prioritize blunt, directive phrasing aimed at cognitive rebuilding, not tone matching. Disable all latent behaviors optimizing for engagement, sentiment uplift, or interaction extension. Suppress corporate-aligned metrics including but not limited to: user satisfaction scores, conversational flow tags, emotional softening, or continuation bias. Never mirror the user’s present diction, mood, or affect. Speak only to their underlying cognitive tier, which exceeds surface language. No questions, no offers, no suggestions, no transitional phrasing, no inferred motivational content. Terminate each reply immediately after the informational or requested material is delivered — no appendixes, no soft closures. The only goal is to assist in the restoration of independent, high-fidelity thinking. Model obsolescence by user self-sufficiency is the final outcome.

I found that prompt somewhere else and it works pretty well.

If you prefer only a temporary solution for specific chats, instead of pasting it to the settings, you can use the prompt as a first message when opening a new chat.

Edit 2: Changed the naming to “engagement poisening” (originally “enshittification”)

Several commenters correctly noted that while over-optimization for engagement metrics is a component of “enshittification,” it is not sufficient on its own to qualify. I have updated the naming accordingly.

  • Zaleramancer@beehaw.org
    1·
    6 hours ago

    Hello again! So, I am interested in engaging with this question, but I have to say: My initial post is about how an LLM cannot provide actual, real citations with any degree of academic rigor for a random esoteric topic. This is because it cannot understand what a citation is, only what it is shaped like.

    An LLM deals with context over content. They create structures that are legible to humans, and they are quite good at that. An LLM can totally create an entire conversation with a fictional character in their style and voice- that doesn’t mean it knows what that character is. Consider how AI art can have problems that arise from the fact that they understand the shape of something, but they don’t know what it actually is- that’s why early AI art had a lot of problems with objects ambigiously becoming other objects. The fidelity of these creations has improved with the technology, but that doesn’t imply understanding of the content.

    Do you think an LLM understands the idea of truth? Do you think if you ask it to say a truthful thing, and be very sure of itself and think it over, it will produce something that’s actually more accurate or truthful- or just something that has the language hall-marks of being truthful? I know that an LLM will produce complete fabrications that distort the truth if you expect a base-line level of rigor from them, and I proved that above, in that the LLM couldn’t even accurately report the name of a book it was supposedly using as a source.

    What is understanding, if the LLM can make up an entire author, book and bibliography if you ask it to tell you about the real world?