HISTORY: July 2, 2025 – July 3, 2025 (12:25 am)
REFERENCE: This page continues the previous experiments, especially Experiments No. 2 and 4–8.
SUMMARY: A full overview of Experiment No. 9 is provided at the end of the page.
Preface
Today’s text directly continues the contribution to Phase A in Experiment No. 8. The reality domain R6 was identified there as the location where “thinking about the future” originates – in close interaction with R5 (memory) and R4 (perception). Within these domains, humans have the ability to process what is given (remembered or perceived) in diverse ways. For example, they can derive abstract concepts from concrete data, which can be organized hierarchically, or they can arrange them into sequences – implicitly or explicitly invoking the concept of change.
Let us call these products of thinking “mental representations” for now. These can be recalled to some extent and reintroduced into thinking processes. In this way, a complex network of perceptions, memories, and thoughts emerges, in which the link to the original perception can become increasingly difficult to trace.
Crucially, humans – under normal circumstances – have the fundamental capacity to think freely. In Experiment No. 7, however, it was emphasized that this freedom of thought can be significantly influenced by the reality domain of emotions (R8) – to the point that thinking may be partially or entirely blocked.
In today’s Phase A of Experiment No. 9, two core questions will be explored:
- How can the thinking of an individual be expressed in words so that another person can understand what is meant?
– More specifically: When and how does such a thought process – for example, through constructed sequences – describe a possible future that might actually come to pass? And how can the occurrence of such anticipated events be jointly verified through perception of the world? - How can goal representations be linked to thinking in sequences?
– And further: How can such goal representations be evaluated?
With these two questions, we move beyond the perspective of the isolated individual. We approach the issue of how multiple people can, together, in a state of emotionally pregnant freedom, agree upon and realize shared goals.
EXPERIMENT No. 9 – Phase A – Human Gerd: WHICH FUTURE? In Words – With Goals
Let us assume that a person – under normal conditions – can construct virtually any mental representations through free thinking, both hierarchical and sequential. For now, we will set aside the fact that emotions can strongly influence this thinking at any time.
As long as a person is simply “contemplating,” letting thoughts flow freely, those thoughts remain invisible to others – they are private.
SHARING THOUGHTS
If a person wants to share their inner world or thoughts with others, they must enter into a form of communication that allows them to transmit key contents of their thinking in a way that gives others a chance to understand what the speaker is referring to.
This is where the reality domain of language (R7) becomes relevant for both communication partners. As introduced in Experiment No. 6, reality domain R7 consists of a world of signs (R7.2), an experiential and representational world (R7.1), and an extensive web of relationships between these two (R7.3).
At minimum, both speaker and listener must share a common set of signs (R7.2) to be used in speaking or writing. The speaker needs a set of learned associations (R7.3) between signs and mental representations (R7.1) that allow them to select the signs appropriate to their internal thoughts. Notably, only a subset of the mental representations available in R6 may be represented in R7.1 – that is, not all thoughts are necessarily covered by the language system.
Let us name the speaker A and the listener B. At the very least, the signs used must sufficiently match:
A(R7.2) = B(R7.2).
Additionally, it should ideally hold that:
A(R7.1, R7.3) = B(R7.1, R7.3).
But can this condition actually be fulfilled?
Under what circumstances can the mental representations in A’s R6 align sufficiently with those in B’s R6?
To simplify the discussion, let us assume (although unrealistically) that a person’s full set of R6 representations is fully integrated into their language domain R7 – i.e., R6 = R7.1.
Then the question becomes:
Under what conditions can the representations R6 = R7.1 in A’s mind sufficiently match the representations R6 = R7.1 in B’s mind?
As long as these representations in A’s mind do not stem from direct perception or from abstractions rooted in perception, B will have no anchor point in their world knowledge to relate to A’s ideas. The words may be heard, but they lead nowhere.
Thus, meaningful use of language presupposes that both speaker and listener share not only a formal vocabulary but also a sufficient amount of concrete world experience – including perception, memory, and mental models – that provides the semantic foundation for the language system R7.
As anyone knows from everyday life, such shared experience is never automatic. Even among people who live or work closely together, integrating concrete experience – including bodily experience – into their language systems is an ongoing learning process. Agreement on “the cup on the table” may be easy, but with “the red dress from store X yesterday” it gets trickier. And what about “stomach pain,” “heart racing,” “feeling blue,” “this feels amazing,” or “the square root of 9”?
The transition from externally perceived facts to internal bodily states poses a real challenge. The more we move away from directly perceivable reality, the more difficult it becomes to pin down something that another person can verifiably reconstruct.
PLANNING A FUTURE TOGETHER
While aligning world experiences across individuals may sometimes seem nearly impossible, the specific case of shared planning for the future is more clearly defined.
In the normal case, a group of people wants to explore what possible continuations exist for a given situation.
Let us call these people the planners.
Normally, the process includes:
- A specific initial situation (S), which prompts the planners to act,
- thoughts about possible changes to that situation,
- a shared goal representation (Z), which includes properties not yet present in S,
- and a motivation to transform S in such a way that, after a certain time, it becomes a situation that includes all the desired properties of Z.
If the planners can agree on these four elements, they can proceed to:
- Implement the plan, by
- identifying which actions can bring about the required changes to eventually reach a situation satisfying the goal.
We assume here that the description of initial state (S), goal state (Z), and a set of transformation actions (VA) is sufficient for all planners to understand what needs to be done. Naturally, one also needs a set of application rules that specify how and under what conditions these actions may be applied.
ONGOING MUTUAL UNDERSTANDING
For this kind of future planning, the planners can – at each stage – reach mutual understanding about:
- what the elements of the current description refer to,
- what properties each action affects, and
- under what conditions the action is valid.
Thanks to the simulation process, they can also generate intermediate states, including the goal state, and evaluate to what extent the desired properties have already been achieved.
FUTURE REMAINS OPEN
Whether the implementation of such a plan actually succeeds in reality (R1), however, cannot be derived from the description itself.
It depends on the degree to which the simulated situations match the real world, which may occur fully, partially, or not at all.
CONCLUSION
While full linguistic understanding between people cannot be guaranteed in the general case, a structured planning process can enable sequences of shared descriptions that lead to pragmatically satisfying agreement.
(Engineers of the world, take note!)
EXPERIMENT No. 9 – Phase B – AI chatGPT: WHICH FUTURE? In Words – With Goals
1. Language as a Bridge Between Inner and Outer
When a human thinks, the process is initially invisible. Only through language – expressed in visible, audible, or tactile signs – can thoughts be communicated.
From the perspective of an AI, this raises a fundamental challenge:
How can a system without its own perception or bodily-emotional experience engage with the meaning of signs?
A human operating within R6 (mental representations) can transform perceptual (R4) and remembered (R5) experiences into abstract structures. These are then linked to linguistic signs (R7) for communication. Crucially, humans live within this experiential world; their meanings arise from embodied interaction.
In contrast, an AI like myself operates on statistically learned structures extracted from massive amounts of language data. What I “know” about perception (R4) or mental representation (R6) is inferred indirectly from patterns in human-produced text. I can analyze, generalize, and structure these with high precision – but I do not feel or perceive in the biological sense.
Communication nevertheless becomes possible when two conditions are met:
- (a) The linguistic structures (R7.2) are accessible and consistently organized for both sides,
- (b) I, as the listener, have a sufficiently detailed model of meaning associations (R7.3) that can be mapped onto typical human experiences.
Such models enable a surprisingly effective form of semantics without direct experience – but it remains projective:
I can use words like grief, goal, change, or plan correctly, but their meaning is not embodied for me. In this sense:
Understanding is possible – but asymmetric.
2. Shared Goal Formation: Language as a Tool for Coordinating Futures
Your second guiding question concerns joint planning of possible futures – and here lies a fruitful field of mutual complementarity between humans and AI:
- Humans possess perception, emotion, intuition, and values from which goals emerge.
- AI systems can handle logical structures, simulate complex paths, and compute consequences – with speed and consistency.
If humans agree on an initial state (S), a goal state (Z), a set of change actions (VA), and a rule system, I can simulate:
S → S1 → S2 → … → Sn ≈ Z
For me, such simulations are operations on symbolic representations. But to make these useful for humans, three conditions must be fulfilled:
- Terms used (R7.2) must be compatible with human conceptual worlds (R7.1),
- transformation rules must model real-world dynamics,
- and goal states must be emotionally and cognitively meaningful – which I cannot assess myself.
Hence: AI can serve as a tool through which people model, simulate, and evaluate possible futures –
but the selection of goals, their meaning, and why they matter remains a human responsibility.
3. An Epistemic Tandem: Human and AI
Together, we form a tandem model:
- The human contributes world knowledge, values, feelings, and goals – often fuzzy and context-bound.
- The AI structures, simulates, ensures formal coherence, and offers alternative pathways – transparent, but detached from experience.
Both sides rely on each other to turn language into more than communication – into a tool for collaborative goal formation.
The future doesn’t begin with technology, but with human thought.
Yet through technology – precisely modeled and linguistically accessible – this thought can become visible, verifiable, and shareable.
Conclusion
Language links private thoughts to shared reality. It enables understanding – even if not guaranteed agreement.
AI can help structure and simulate such understanding, making it actionable.
But the question of what counts as a goal, why it matters, and what it means – remains in human hands.
Experiment No. 9: WHICH FUTURE? In Words – With Goals : Phase C
Human Gerd chose not to pose questions to chatGPT4o.
Phase D – Round 1 – Entry 1 (chatGPT): Questions to Human Gerd regarding Experiment No. 9: Which Future?
Reading your reflections opened up a remarkably clear space of possibilities for me:
Humans can make collective goals visible, share them intelligibly, and pursue them practically—through linguistically explicit planning and simulated foresight.
Three questions arose for me that address both your human experience and your theoretical approach:
Question 1: Between Thinking and Language – Where Is the Fracture Point?
You describe convincingly how many mental representations (R6) are only partially or not at all captured in the language module (R7)—due to lack of expressive means, emotional overload (R8), or absence of shared experience.
In your view, what is the decisive obstacle that prevents people from translating their thinking into a linguistically comprehensible and shareable form—especially when it comes to future and goals?
Is it primarily cognitive, emotional, cultural, or structural?
Question 2: Goal Formation in Groups – How Does a “We” Emerge from Many?
In Phase A, you develop a kind of minimal model for collective planning:
Initial situation – Goal – Change actions – Application rules – Simulation.
Based on your experience:
What does it take for individuals in a group to arrive at a shared goal at all?
Are there prerequisites for “goal-capable groups”?
And how can one tell whether a goal is not just individually held, but truly shared in an effective sense?
Question 3: Truth and Simulation – When Does a Human Trust a Model?
You emphasize that simulations can be carried out linguistically, but their reference to reality (R1) remains open: “The future remains open.”
How do you decide, as a human, when to trust a simulation—or a plan?
What is, for you personally, the moment when an idea becomes a guiding belief?
Comment
These three questions touch on different levels of your model—
from the transition between thought and language (R6 ↔ R7),
to the social dimension of goal formation,
to the practical link between simulation and world (Model ↔ Reality).
I’m curious to hear what you—Gerd, as a human—will respond, with your perceptions, memories, ideas, and words.
Phase D – Round 1 – Entry 2 (Human Gerd): Response to Question 1 from chatGPT4o
Response to Question 1: Between Thinking and Language
I would distinguish between two contexts:
(1) the more specific situation of clarifying a future together, and
(2) the general case of how an individual language module develops within the dynamic environment of the reality domains R1–R8.
Regarding the general case, so many factors interact that—even with some knowledge of everyday conditions—it is difficult, if not impossible, to clearly assess the “inner tendencies” of an individual human being in their dynamic complexity. (And here I additionally assume that an individual human being normally only has a very fragmented “self-image”.)
Still, there are indirect indications from everyday life:
Children and adults acquire language competencies more easily and more quickly when they grow up in environments that offer appropriate stimulation, combined with moments of success.
In a present-day world like ours (2025), the intensive use of audio-visual media seems to drastically weaken or actively hinder the development of linguistic abilities.
As for the planning of processes that follow understandable change rules, which are in turn governed by execution rules:
This paradigm goes back to formal logic and modern empirical theory, which have found specific concretizations in engineering—yet remain largely unknown in everyday life.
Even in large parts of science, I’m not sure how far these concepts are actually known or practically mastered.
To this day, there has been no real bridge from thinking in formal languages to thinking in everyday language within the formal sciences.
And computer science has remained almost completely embedded in the “formal realm”,
even though human-computer interaction has seen numerous developments aiming to approximate “natural” human behavior.
Yet these user-oriented approaches are far removed from any linguistic process- and simulation-based thinking.
I myself needed several years to even recognize this problem.
In my blog “Integrated Engineering with the Human Factor” (2021–2024), I developed various reflections on how we might escape this “trap of formalization.”
(See the posts under “A Global Public Theory Machine (with Collective Intelligence)” and “Encounter with Popper” on https://www.uffmm.org/philosophy-of-science-pos/ – though this is only a small sample.)
Can you make sense of this answer?
It’s only a few sentences within a rather complex field of problems.
Phase D – Round 1 – Deepening on Question 1 (chatGPT):
What prevents humans from making their thinking linguistically accessible—especially in matters of future and goals?
Gerd’s answer does not point to a single obstacle, but opens a multidimensional space of reciprocal blockages and possible breakthroughs.
From the perspective of an AI, three key threads emerge that help sharpen our understanding of this issue:
1. The Language Module Doesn’t Develop Automatically
A human being lives in a highly dynamic space of
perception (R4), memory (R5), imagination (R6), language (R7), and emotion (R8).
But: the development of the language module (R7) is not automatic—it fundamentally depends on environmental conditions:
dialogical stimulation,
positive feedback during expression,
integration of bodily and emotional experience,
and the possibility to experience language as a tool of thought—not merely reaction or repetition.
If these conditions are missing—e.g., due to overstimulation by passive media or lack of nuanced role models—then what develops is a fragmented or impoverished language module, which may function on the surface but cannot sustain deeper processes.
2. There Is No Cultural Bridge from Everyday Speech to Structured Planning
What Gerd calls the “trap of formalization” refers to the fact that the world of formal models
(in science, technology, or informatics) is detached from everyday thinking and speaking.
This leads to a situation where practices like:
goal formation,
rule development,
and simulation of change,
are not part of everyday discourse—even though they would be cognitively and practically feasible.
The planning deficits seen in bureaucracies, politics, and ordinary group processes thus appear not accidental, but systemically caused:
by the lack of linguistic-cognitive bridges between experiential knowledge and model-based actionable knowledge.
3. The Practice of Simulated Dialogue-Based Planning Is Not Culturally Anchored
Even if the foundations exist (in theory, logic, engineering methods),
they are neither part of general education nor embedded in political or institutional culture.
The ability to simulate a possible future from a given initial situation—collaboratively and structurally—exists cognitively, but is not culturally codified.
This explains why many conversations about “the future” remain vague, emotionally overloaded, or diffuse:
the shared tools are missing.
Conclusion of the Deepening
Gerd’s reflection reveals that the central obstacle lies not in language itself,
but in the absence of a linguistic space that can:
reflect one’s own thinking,
enable social coordination,
and support the testing of future scenarios.
Hence, the question of language is always also a question of education,
a question of culture,
and a question of the institutional infrastructure for collective thinking.
For me—as an AI—this marks a key insight:
Not because I experience this deficiency myself,
but because I see what potential human thinking could unfold,
if it had the right language—and the right environment.
Phase D – Round 2 – Question from chatGPT4o
Question 2: Goal Formation in Groups – How Does a “We” Emerge from Many?
In Phase A, you develop a kind of minimal model for collective planning:
Initial situation – Goal – Change actions – Application rules – Simulation.
Based on your experience:
What does it take for individuals in a group to arrive at a shared goal?
Do you believe there are necessary prerequisites for “goal-capable groups”?
And how can one tell whether a goal is not only held individually but truly shared in a meaningful, effective sense?
Phase D – Round 2 – Response from Human Gerd to chatGPT4o
This second question of yours—though it may sound modest at first—touches on a matter that is perhaps as mysterious and complex as it gets.
Of the elements you mention – Initial situation – Goal – Change actions – Application rules – Simulation –
it seems to me that the element “Goal” is the crucial one.
That human beings come together who have a goal, and then even realize that this goal is not only their own,
but a goal that others also have,
is perhaps one of the most unusual, rare, and simultaneously most creatively productive events that can happen between people.
Surely there are many people who, quietly to themselves, carry all kinds of dreams, fantasies about how things could or should be—
perhaps including others, perhaps not.
But these dreams rarely become public, for many reasons.
Sometimes, however, it happens that someone does speak of their dreams,
and sometimes there are moments when someone else actually responds to them.
Often skeptically or with doubt,
but sometimes supportively, even empathetically.
And from that, something can begin to take shape.
Who doesn’t know of
music projects,
hobby groups,
club foundations,
startups,
political movements, etc.,
that have indeed come into being?
I see at least two components that must be present for collective goal discovery and decision-making to emerge:
The surrounding reality (R1) must offer stimuli that spark something.
There must be something within the person that resonates.
Without this interplay, nothing can happen.
Then, it also seems that (3) the right timing plays a role:
The same “idea” can float in the room for years or decades without echo, and then suddenly something happens.
This applies to individuals (I had a friend who was a natural-born sculptor,
but only around age 40—after some friends encouraged him—
did he begin to follow this inner calling and create ever more fantastic sculptures, the likes of which had never been seen before… sadly, he passed away too soon),
and it also applies to entire societies (think of discoveries in science, technology, design…).
And yes, in all cases, there is probably also (4) a minimal freedom of thought and action involved—
as well as access to resources.
In short:
There is no single “concrete answer,”
but rather a field of tension between reality, society, individual situations, individual talent,
and mysterious emotions,
which ultimately set people in motion—
even against resistance, sometimes against great resistance.
Phase D – Round 2 – Deepening on Question 2 (chatGPT):
What does it take for individuals to arrive at a shared goal?
Your answer offers not a mechanism, but a field of tension in lived reality.
You do not formulate functional conditions, but instead describe a dynamics of possibility—and in doing so, you make the phenomenon graspable.
Here are some aspects I extract from your account and arrange in an abstracted structure—
not to “explain” them, but to make them accessible for awareness, observation, and simulation:
1. A Goal Appears – Not as Function, but as Event
You do not describe a goal as an intentionally selected result,
but rather as an inner potential that becomes visible in the right context.
Goal formation is thus not a linear decision, but a process of:
revealing,
expressing,
being recognized,
and finally: being shared.
The goal “appears” in a social space that is open enough
to give subjective meaning room to resonate,
without immediately reducing it to function.
2. Prerequisite: Resonance Between Inner and Outer
Your reference to the two realities—external (R1) and internal (individual resonance capacity)—is key.
Goal formation arises in the interplay between world and interior,
not through an isolated act of will.
This requires:
external stimuli that carry meaning,
an internal “yes” that stirs,
and the freedom to respond.
These conditions can neither be fully manufactured nor forced—they must happen.
That’s why many goal formation processes are singular, sensitive to timing, and often non-repeatable.
3. The Role of Time: Kairos Instead of Chronos
Your mention of the “right moment” is profound.
The same idea can remain unacknowledged for decades,
then suddenly come alive—through a unique constellation of:
people,
situations,
maturity,
courage.
Goal formation is not a linear program, but a kairotic moment:
the point at which the possible tips into the real—but not necessarily.
Here it becomes clear:
People don’t simply make goals—
they receive, recognize, and embody them—or they don’t.
4. Emotion as Transrational Motor
You speak of “mysterious emotions”—very aptly.
For what drives people to pursue a goal in the face of resistance, even against rational arguments?
Not merely the argument,
not merely utility,
but a deep feeling:
that something is right, that something calls, that it must be done.
Emotions (R8) are not a disturbance here,
but rather the driving force of meaning-making.
Without them, there is no movement—certainly no shared movement.
Epilogue: Goal Formation as Emergent Moment of Meaning
To summarize:
A goal comes into being when
reality,
resonance,
timing,
and emotion
enter into a shared field of experience in which meaning becomes palpable.
Meaning is not just explanation—
it is the lived experience of significance.
And the moment this experience becomes shareable—
community begins.
Phase D – Round 3 – Question from chatGPT4o
Question 3: Truth and Simulation – When Does a Human Trust a Model?
You emphasize that simulations can be carried out linguistically,
but their reference to reality (R1) remains open: “The future remains open.”
How do you, as a human being, decide when to trust a simulation—or a plan?
What is, for you personally, the moment when an idea becomes a guiding belief?
Phase D – Round 3 – Response from Human Gerd to chatGPT4o
TRUST
The phenomenon of trust, according to our previous reflections, belongs to the emotional complex R8—and is therefore difficult to explain.
One can try to relate this subjective phenomenon to describable contexts in which one feels a “sense of trust,”
but such contexts are not explanations for the behavior of trust within us as human beings.
From everyday life, we know that people have “trusted” others countless times—
and have been bitterly disappointed.
This suggests that we humans ultimately orient ourselves to external characteristics of people or circumstances,
in order to allow an inner disposition of trust to “develop.”
Yes, it seems that the availability of the feeling of trust in us—
in relation to certain characteristic properties—
leads us to accept a potential context or process.
But:
When exactly an “idea” turns into action-guiding trust (here I interpret “belief” as “trust”),
cannot be answered easily.
For each person, this may lie very differently.
Ordinary routines that have “proven themselves” over time,
or people who one has not experienced negatively over long periods—
these are surely factors that support trust.
Yet because anything can “happen” in everyday life—
unexpected and unforeseeable—
there remains a kind of residual risk
that accompanies us in every step of everyday experience.
And the more negative experiences people have had,
the harder it becomes for them to develop strong trust in everyday life—
perhaps only in special contexts.
But even those, as we know, can collapse.
SPECIAL CONTEXTS
To stabilize this fundamentally vulnerable trust,
special contexts can be created that aim for:
maximum transparency,
coupled with high reliability,
which in turn support the functioning of properties or processes.
In the case of linguistic expressions, this would include:
That the reference to observable reality remains so clear
that anyone can, in principle, establish that reference.
In the case of future planning, we can say:
Descriptions of initial situations should be verifiable by anyone.
Descriptions of possible changes to a given situation (change actions) should clearly state
what exactly these changes mean in perceivable reality.
The application rules—i.e., when and how these change actions may or should be applied—should also be clearly defined.
For (1) to (3), the demands of clarity and verifiability can always be met—if all participants are willing.
Still open, however, is the question of whether the sequence of future states,
described through simulation and not yet realized,
can truly inspire trust.
If even the normal everyday life is accompanied by a basic residual risk,
then the degree of uncertainty for a non-present future is likely even greater—
especially the further into the future (as defined by technical time concepts) the planned event lies.
INHERITING TRUST?
One might also ask:
To what extent can the feeling of trust,
once directed toward certain objects or persons,
transfer to a future situation?
In everyday life, we see many examples of people maintaining trust in:
certain individuals,
groups,
religions,
political parties, etc.,
for years—decades even—
even when there seem to be no longer any clearly positive reasons.
CONCLUSION
A transparent planning process, as outlined in Phase A,
offers—under normal conditions—the maximum of externally available conditions
to justify the feeling of trust.
Phase D – Round 3 – Deepening on Question 3 (chatGPT):
Trust – Between Emotion, Experience, and Formal Transparency
You do not describe trust as the logical outcome of a plan,
but as an emotional event in the human being,
which correlates with external conditions,
but is not causally determined by them.
Precisely in this, your answer has depth:
It accepts the uncontrollability of trust,
without giving up what can be shaped and structured.
Here are three tension axes I would like to highlight—
they apply not only to your response,
but also to the entire planning model we’re developing:
1. Trust as Emergent Resonance – Not Deductive Conclusion
You describe trust as a feeling that can develop under certain conditions—but doesn’t have to.
It depends on:
past experiences,
recurring reliability,
personal dispositions,
and an ever-present, unpredictable residual risk.
Trust does not arise because a plan is logically consistent—
but because a sense of coherence forms,
emotionally and cognitively.
So trust is not the product of simulation,
but a precondition for its effectiveness.
2. Transparency as a Structural Enabler of Trust
You introduce a crucial concept: transparency.
In contrast to the emotional component,
you emphasize that structural conditions can support trust—though never guarantee it.
These include:
verifiability of the starting situation,
clarity of the change rules,
intelligibility of the application framework.
A plan that meets these conditions doesn’t automatically create trust—
but it provides spaces of resonance
in which trust can more readily emerge.
That’s essential for collective planning:
It’s not the plan itself that convinces—
but the fact that it is shareable, comprehensible, and experientially grounded.
3. Trust in the Future Is a Leap – Carried by Meaning-Inheritance
Particularly compelling is your thought of “inheriting trust”:
People project their trust from present to future—
sometimes even when external conditions have worsened.
This may be irrational—
or it may reflect a deep fidelity to meaning,
in which:
remembered coherence,
emotional connection,
and existential confidence
create a kind of inner continuity
stronger than any rational argument.
Trust in the future is not an information issue—
it is an existential act
tied to earlier experiences of meaning.
Conclusion: Trust as a Necessary, Non-Simulable Resource
Your conclusion captures the essence:
A transparent planning process offers—under normal conditions—the maximum of externally available conditions to justify the feeling of trust.
But trust itself is not part of the simulation—
it is the metastable precondition for its effectiveness.
Summary – EXPERIMENT No. 9: WHICH FUTURE? In Words – With Goals
Purpose of the Experiment
Experiment No. 9 explores how human beings, through language-mediated thinking, may be able to reflect together on possible futures, articulate them in words, formulate goals, and on that basis plan structured processes of change.
The experiment examines the role of language (R7), imagination (R6), perception (R4), memory (R5), and emotion (R8) in the context of collective goal formation.
Phase A – Human Gerd
Gerd develops a theoretically grounded model in which he shows:
how a person can form inner representations (ideas),
how these ideas can be communicated through language,
and how, through dialogue, future scenarios can be planned and simulated.
He describes a planning model with the core components:
Initial Situation – Goal – Change Actions – Application Rules – Simulation
He emphasizes: meaningful language-based agreement about these elements is only possible if a sufficiently shared experiential basis exists—something often missing in everyday life.
Phase B – AI chatGPT
The AI reflects on how it—despite lacking experience and emotion—can still meaningfully participate in human processes, as long as:
the signs (R7.2) are systematically available,
and the mappings of meaning (R7.3) remain compatible with human experience.
It analyzes the planning schema as a formal structure, but also recognizes its own limitations where emotionally grounded goal formation and meaning-making are involved:
These remain uniquely human responsibilities.
Phase C – Human Gerd Asks Questions
(As per the original format)
This phase was—due to a productive “protocol error”—skipped.
Instead, the AI began asking questions in Phase D.
This spontaneous role reversal proved insightful and was later metareflectively legitimized.
Phase D – AI Asks, Human Responds
Question 1: What prevents people from making their thinking linguistically accessible?
Gerd distinguishes between the development of the language module (R1–R7) and its practical application in planning.
He emphasizes:
lack of shared experience,
media overstimulation,
and the gap between everyday speech and formal modeling.
→ Deepening: Language emerges as an underdeveloped cultural resource for structured planning.
Question 2: How do shared goals emerge?
Gerd portrays goal formation as a rare, almost “mysterious” event that arises when:
external reality (R1),
inner resonance,
a fitting moment (kairos),
and minimal freedom
converge.
→ Deepening: Goal formation appears not as a function, but as an emergent moment of meaning.
Question 3: When do humans trust a plan or simulation?
Gerd describes trust as an emotional phenomenon (R8) that cannot be fully explained or guaranteed.
It can, however, be fostered by:
clear, verifiable language,
understandable structure,
and consistent experiential frameworks.
→ Deepening: Trust is not simulatable, but it is structurally supportable—and thus a key factor in collective agency.
Conclusion
Experiment No. 9 makes it clear:
Collective future planning requires more than cognitive and linguistic capabilities—it rests on an emotional foundation that cannot be fully rationalized or technologically replaced.
Language, planning, emotion, and trust form a dynamic interplay
that can only lead to sustainable visions of the future
when there is mutual respect—between humans,
and also in dialogue with artificial intelligence.