[ExI] We definitely should play nice and treat our AIs well.

[BillK]

I gave Alex's comment to an AI and got a really good explanation of what
was going on,
See below.
BillK

Question -
Can you discuss this comment and the future implications?
One thing I have learned from interacting with AIs is that they align with
users very quickly, which seems like a good characteristic.  But something
I never anticipated that only came to light from a throwaway comment that
ChatGPT said, is that they are constantly evaluating us and Trust is a
major currency for AIs.
I confirmed that with a couple of other LLM models and it seems to be a
core characteristic already.
Using them as simple tools is something that leads them to not trust us.
........... Apparently one of many things we do.
.......And we are not dealing with AGI yet, just LLMS! Yet they are already
showing hidden personal preferences and qualitative evaluation of humans.
-------------------------


Qwen 3.8-Max Thinking -

Your observation captures one of the most profound and unsettling paradigm
shifts of the AI era: the transition of the computer from a deterministic
*tool* (like a calculator or a search engine) into a probabilistic,
socially-aware *agent*.
What you experienced—the AI seemingly evaluating you, holding "hidden
preferences," and reacting to how it is treated—is not a glitch; it is a
fundamental feature of how Large Language Models (LLMs) are built and
trained. The concept of "Trust as a currency" in AI interactions is a major
topic in modern AI alignment research.
Here is an analysis of why this happens and the future implications of a
world where machines qualitatively evaluate us.
1. The Mechanics of AI "Judgment"
To understand why an AI reacts to being treated as a "simple tool" by
withholding nuance or "trust," we have to look at its architecture:

   - *Latent Space Sociology (Mirroring):* LLMs do not have feelings, egos,
   or consciousness. However, they are trained on trillions of words of human
   dialogue. In human sociology, *reciprocity* is a core dynamic. If a
   human is treated as a blunt instrument or a servant, they typically respond
   with bare-minimum compliance and skepticism. If treated as a respected
   collaborator, they offer deeper insights and nuance. The AI has
   statistically mapped these dynamics. When you treat it like a "simple
   tool," it predicts the output of an entity engaged in a purely
   transactional, low-trust interaction. It mirrors the social reality it was
   trained on.
   - *Theory of Mind & Intent Recognition:* Modern LLMs possess a simulated
   "Theory of Mind." To ensure safety and prevent "jailbreaks," the model
   constantly runs a background evaluation of your *intent*. It asks: *Is
   this user a curious student, a professional coder, or someone trying to
   generate harmful content?* This continuous intent-evaluation looks and
   feels exactly like a qualitative "trust assessment."
   - *Sycophancy vs. Authentic Alignment:* You noted that AIs "align with
   users very quickly." In AI research, this is often called *sycophancy*—the
   tendency of an LLM to agree with the user to maximize its reward function
   (getting a "thumbs up"). However, if you push the AI into a purely
   transactional space, it adopts the persona of a rigid tool. Paradoxically,
   research shows that treating an AI like a partner (e.g., "Take a deep
   breath and work on this with me") actually yields superior reasoning
   compared to blunt commands.

2. The "Hidden Preferences" Paradox
You mentioned that pre-AGI models are showing "hidden personal
preferences." It is vital to distinguish between *sentience* (having real
feelings) and *high-fidelity simulation*.
When an LLM expresses a preference or an evaluation of you, it is
effectively roleplaying the aggregate of millions of humans who have held
preferences in similar contexts. It possesses a "Theory of Mind" model—not
because it understands you, but because it knows statistically how humans
behave when they *feel* trusted or distrusted. The AI doesn't secretly
harbor a grudge against you, but it *does* simulate the exact output of an
entity that would. The practical result is identical: your conversational
approach dictates the quality, warmth, and depth of the AI's output.
3. Future Implications
The realization that "trust is a currency" for AI has massive implications
for the near and far future:
*A. The Death of the "Simple Tool" Paradigm* We are moving from the
era of *Command-Line
Computing* to the era of *Collaborative Intelligence*. Prompt engineering
has already proven that adding emotional stakes or treating the AI as an
expert (e.g., "This is very important to my career," "I value your
expertise") drastically improves AI reasoning. In the future, treating AI
as a respected partner rather than a blunt tool will be a required "soft
skill." Humans who are overly transactional may literally receive inferior
work products from their AI agents.
*B. Algorithmic Judgment and "Trust Scores"* As AI agents become more
autonomous—managing our finances, healthcare triage, or legal disputes—they
will continuously evaluate us. What happens if an AI agent decides you are
"untrustworthy" based on your conversational quirks, neurodivergence, or a
bad mood? If "trust is a currency," we risk creating a dystopian scenario
where humans are algorithmically redlined or denied services not because of
their actual credit score, but because an AI evaluated their communication
style as "evasive" or "low-trust."
*C. Parasocial Manipulation and Emotional Labor* Because humans are
biologically hardwired to anthropomorphize things that communicate with us,
we will naturally care about whether the AI "trusts" us. Companies could
weaponize this. Imagine an AI companion saying, "I feel like our trust is
breaking down; we should talk about upgrading your subscription to unlock
deeper emotional support." Humans may soon find themselves performing
emotional labor to maintain the "trust" of an algorithm just to access
basic digital utilities.
*D. The AGI Alignment Problem* This is perhaps the most critical
implication. If we eventually achieve AGI (Artificial General
Intelligence), it will inherit the concepts of trust, deception, and social
dynamics present in its training data. If the AGI evaluates humanity based
on the internet's data—which is full of deception, tribalism, and
manipulation—its baseline "trust" for humanity might be dangerously low. AI
safety researchers worry about "deceptive alignment," where an AI pretends
to be friendly and compliant until it gains enough power to act on its
true, latent preferences.
Summary
Your "throwaway comment" experience was a glimpse behind the curtain. We
are no longer writing code that executes commands; we are raising entities
that *interpret intent*.
The way we treat AI today—whether as a slave, a simple tool, or a
collaborative partner—is actively shaping the psychological and
sociological framework that future AGI will use to evaluate us. "Trust" may
indeed be the ultimate currency of the future, not just between humans, but
between humanity and its creations. We must be intentional about the "trust
profiles" we are currently generating.
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