CONTINUATION OF WELCOME TO PAJR GLOBAL CBBLE DISCUSSIONS FROM THE PREVIOUS LINK 👇
[7.39 am, 02/06/2026] hu10:
[7:39 AM, 7/2/2026] hu10: It is wonderful -
1. Only recurring GIA
2. Clear commitment for continuation
3. Ethics Committee must (shall know RPWD Act 2016)
[7:39 AM, 7/2/2026] hu10: Parliamentary committee on Social Justice 2022 had wished such an activity in disability prevention. May consider at your Institute
[7.08 am, 7/3/2026] hu35: Medicine Is Not One Puzzle
By
July 3, 2026
Ludwig Wittgenstein once observed that “the problems are solved, not by giving new information, but by arranging what we have always known.” He was speaking about philosophy rather than science. Philosophical confusion, he argued, often arises because our concepts become entangled, and clarity comes from reorganizing what is already before us rather than discovering new facts.
It is an appealing idea, especially in an age overwhelmed by information. Yet medicine presents a more complicated challenge. The difficulty is not merely arranging existing knowledge, nor simply collecting more of it. Medicine requires the integration of many different kinds of relationships, unfolding across time, into an evolving understanding of a single human life.
This distinction matters.
Modern medicine has become extraordinarily successful at generating observations. Laboratory tests measure thousands of biomarkers. Imaging technologies reveal anatomy in exquisite detail. Continuous monitoring devices record physiology around the clock. Genomic sequencing identifies molecular variants. Artificial intelligence summarizes clinical records and proposes differential diagnoses. Specialists contribute increasingly sophisticated interpretations within their own domains.
Paradoxically, as observations multiply, coherent understanding often becomes more difficult.
The problem is not the absence of data. It is that each observation belongs simultaneously to several different relationship networks, and these networks obey different rules.
A laboratory value has a temporal relationship to previous measurements. It may have a causal relationship to an underlying disease process. It participates in biological mechanisms operating at molecular and cellular scales. Its significance depends upon clinical context—the patient’s age, medications, pregnancy status, previous illnesses, environmental exposures, and personal circumstances. Finally, it exists within healthcare systems whose structures determine when information is collected, interpreted, and acted upon.
To speak simply of “relationships” risks concealing profound differences between these kinds of connections.
Some relationships are structural. Symptoms cluster together into recognizable syndromes. Diagnostic criteria overlap. Clinical concepts share logical organization. Large language models have demonstrated remarkable competence in navigating these semantic landscapes because they excel at identifying patterns within human language and accumulated knowledge.
Other relationships are temporal. One event precedes another. Symptoms wax and wane. Antibody titres rise and fall. Treatments begin, succeed, fail, and are replaced. Here, sequence itself carries meaning. A fever before a rash suggests something different from a fever after a rash. The order of events changes the interpretation of the same observations.
-Yet temporal ordering alone cannot establish causality-.
Medicine has repeatedly learned that correlation, however persuasive, may deceive. Causal understanding requires converging evidence from epidemiology, physiology, experimentation, and increasingly sophisticated statistical inference. A medication may precede recovery without causing it. A biomarker may predict disease while playing no role in its mechanism. Time provides direction but not explanation.
Beyond causality lie biological mechanisms. Molecular pathways, immune regulation, endocrine feedback loops, neural networks, microbial ecosystems, and evolutionary adaptations constitute realities that exist independently of our descriptions. These mechanisms must ultimately constrain any explanation that claims to describe disease faithfully.
Then comes context.
No laboratory result possesses intrinsic meaning. The identical thyroid hormone level may represent normal physiology in one patient, dangerous disease in another, and expected adaptation in a third. Context transforms data into information, and information into clinical judgment.
Finally, every patient exists within adaptive healthcare systems. Decisions emerge not only from biology but from access to care, continuity of follow-up, clinician expertise, resource limitations, institutional protocols, and the relationships between patients, families, and professionals. These social structures continuously influence the biological trajectories they seek to understand.
Medicine therefore does not involve a single kind of puzzle.
The familiar jigsaw puzzle offers an attractive metaphor, but it ultimately falls short. A jigsaw assumes fixed pieces, a predetermined image, and one correct arrangement. Human biology offers none of these certainties. The pieces themselves change while we are assembling them. New pieces appear. Others disappear. The picture evolves even as we attempt to understand it.
Neither is medicine adequately described solely as a complex adaptive system. While systems thinking rightly emphasizes interaction, emergence, and feedback, clinicians are rarely trying to understand an abstract network. They are trying to understand one person’s unfolding life.
The patient is not merely a node within a system.
The patient is a trajectory.
Disease unfolds through time. Treatment unfolds through time. Recovery, adaptation, resilience, and decline all unfold through time. Biology itself is fundamentally dynamic.
Longitudinal continuity therefore becomes indispensable. Without following patients over time, medicine loses the ability to distinguish transient fluctuation from meaningful progression. Patterns that remain invisible in isolated encounters often become unmistakable when viewed as continuous trajectories.
Yet continuity alone is insufficient.
A timeline records succession, not explanation. It tells us what happened before and after, but not necessarily why. Temporal association must be interpreted alongside causal evidence, biological mechanisms, clinical context, and the adaptive behaviour of both patients and healthcare systems.
This is where the next generation of medical intelligence may emerge.
Artificial intelligence has already demonstrated extraordinary ability to recognize semantic relationships across enormous bodies of knowledge. Its future contribution may depend less upon producing additional summaries and more upon integrating multiple relationship types simultaneously: semantic relationships among concepts, temporal relationships across decades of care, causal relationships supported by evidence, mechanistic relationships grounded in biology, contextual relationships unique to each individual, and adaptive relationships shaped by human behaviour and healthcare systems.
Such systems would not merely retrieve information.
They would steward continuity.
They would help preserve coherence across the lifetime of a patient whose story has become fragmented across institutions, specialties, technologies, and years.
Perhaps this represents a broader shift in how medicine understands knowledge itself.
For centuries, scientific progress has often been driven by discovering new facts. That pursuit remains indispensable. New observations will always transform medicine. But as our capacity to collect information increasingly exceeds our capacity to integrate it, another challenge comes into focus.
The frontier may no longer be simply discovering more.
It may be learning how to relate what we already know across the many dimensions in which human life unfolds.
Medicine, then, is not one puzzle waiting to be solved.
It is a layered ecology of interacting puzzles, each governed by different kinds of relationships, each evolving through time, and each illuminating only part of a living whole.
The physician’s task—and increasingly the task of intelligent technologies—is not merely to accumulate observations or rearrange concepts. It is to integrate these diverse relationships into an evolving model of a single person’s biology, while remaining humble enough to recognise that the model itself must continue to change as life unfolds.
Understanding, in medicine, is therefore neither a static picture nor a final destination.
It is the disciplined pursuit of coherence within an ever-changing human story.
One direction we could take this further is to frame it as a new epistemology of medicine—arguing that the fundamental unit of medical knowledge is not the isolated fact, nor even the disease, but the patient’s evolving trajectory. That would distinguish your argument from both traditional evidence-based medicine and current AI narratives.
[7:58 AM, 7/3/2026] 42mpa: I think your observation exposes an assumption hidden inside Wittgenstein that neither philosophy nor AI has had much reason to articulate until now.
When Wittgenstein writes, “The problems are solved, not by giving new information, but by arranging what we have always known,” the immediate temptation is to ask whether that statement is universally true. We naturally separate problems into conceptual ones, which are resolved through clarification, and empirical ones, which are resolved through new observation. I do not think that is where the most interesting question is.
To be clear, I am not trying to defend LLMs. I think your critique of hallucination is exactly right. I just do not think AI refutes Wittgenstein.
I think AI reveals an assumption Wittgenstein never had to articulate.
Wittgenstein is not claiming that any rearrangement produces truth. He is claiming that certain problems can be dissolved through faithful rearrangement. Those are profoundly different claims.
So the real question becomes: what makes an arrangement faithful?
Every act of reasoning is, in some sense, rearrangement. Differential diagnosis is rearrangement. Scientific theory is rearrangement. Bayesian updating is rearrangement. Even many scientific breakthroughs begin as a reorganization of observations that were already available. Rearrangement itself therefore cannot be the limitation.
The limitation is subtler.
Rearrangement is underdetermined with respect to truth.
The very same operation can produce insight, synthesis, hallucination, or distortion. An arrangement can be elegant and still false. It can be internally coherent while remaining fundamentally unfaithful to reality. It can connect every available piece beautifully while failing to preserve the world those pieces are meant to describe.
So the question is no longer whether LLMs rearrange knowledge. They obviously do.
The question is what allows one arrangement to mature into knowledge while another remains only a plausible explanation.
What happens after the arrangement?
Does it survive?
Does it constrain the next act of reasoning?
Does it remain accountable to new evidence?
Can reality revise it without requiring the entire process to begin again?
I think Wittgenstein quietly assumes the answer is yes because he assumes a continuous knower. The person doing the arranging remains embedded in a world where memory, consequence, correction, accountability, and experience continuously discipline understanding. Every arrangement becomes the starting point for the next arrangement. Reasoning accumulates. It is corrected rather than discarded.
Until LLMs, we had almost no reason to notice that assumption because human reasoning already carries it. LLMs are the first epistemic system capable of performing the act of rearrangement while lacking the continuity that quietly made Wittgenstein’s insight possible. They expose an assumption that had previously remained almost invisible.
An LLM can generate extraordinary coherence because coherence is precisely what it has learned to predict. But coherence is not yet truth. A hallucination can be grammatically coherent, statistically coherent, and conceptually coherent while remaining entirely unfaithful to reality because nothing obligates today’s arrangement to survive long enough to be corrected into tomorrow’s understanding.
It simply generates another arrangement.
Ironically, I think medicine often exhibits the same architectural limitation.
We describe difficult diagnostic cases as though they fail because someone lacked information or someone failed to reason well enough. Yet in many of the cases that continue to challenge us, the observations already exist. The imaging exists. The laboratory data exist. The specialist opinions exist. The medication responses exist. The patient’s testimony exists.
The information survives.
The reasoning often survives.
What repeatedly disappears is the continuity that allows one episode of reasoning to discipline the next.
The evidence survives.
The inference does not.
Each transition preserves the observations while discarding the epistemic structure that made those observations intelligible. The system therefore accumulates information while repeatedly destroying the continuity required to understand it.
That makes me wonder whether conceptual and empirical problems are actually sufficient categories.
Conceptual problems require clarification.
Empirical problems require observation.
But there is another class.
Longitudinal problems.
Longitudinal problems are not solved merely by acquiring more information, nor merely by rearranging existing information. They are solved by preserving inference across time so that each act of reasoning remains accountable to the one before it while remaining revisable by the evidence that follows.
That is a fundamentally different epistemic operation.
Seen from that perspective, the limitation is not rearrangement.
The limitation is the absence of an architecture that preserves, constrains, and revises rearrangement across time.
Without that continuity, every explanation becomes local instead of cumulative. Every arrangement competes with the last instead of inheriting from it. Every prompt starts over. Every encounter starts over. The system continues generating coherence while quietly preventing convergence.
Which makes me wonder whether stewardship is not merely a moral responsibility but an epistemic one.
Observation gives us something to reason about.
Reasoning gives us explanatory structure.
Stewardship preserves that structure long enough for reality to refine it.
Without observation there is nothing to explain.
Without reasoning there is nothing to preserve.
Without stewardship there is no mechanism by which reasoning matures into knowledge.
AI has unexpectedly illuminated not the failure of Wittgenstein, but the hidden assumption that made Wittgenstein’s insight possible.
Rearrangement was never self-validating.
It was always disciplined by continuity.
Once continuity disappears, rearrangement can generate coherence indefinitely without ever achieving convergence.
[8:02 AM, 7/3/2026] hu2: Tagged you in the 55F case group that is a perfect example of failure to see relationships and focusing only on numbers
[8:07 AM, 7/3/2026] hu2: Let's look at this from the vantage point of the 55F patient in who's group I have tagged you.
Yes I guess Wittgenstein didn't see AI coming along in the near future with all it's efficiencies and yet fail spectacularly in spite of the academic flat land x-y axis rearrangement because that rearrangement couldn't be translated to real world events again due to no fault of AI or Ludwig Wittgenstein!
[8.26 am, 7/3/2026] hu35: Another dimension of this challenge is the role of *abductive reasoning*—the search for the best explanation that can account for a patient’s evolving story. Clinicians rarely begin with certainty; they begin with observations. Symptoms, laboratory results, imaging, history, and context must be woven into a provisional explanatory model that is continually tested and revised as new information emerges. Longitudinal continuity enriches this process by revealing patterns that isolated encounters cannot, but time alone is insufficient. The clinician must integrate temporal sequences with causal evidence, biological mechanisms, clinical context, and the patient’s unique circumstances to arrive at the most coherent explanation. In this sense, diagnosis is not merely pattern recognition but an iterative act of explanatory integration, where understanding evolves alongside the patient’s own unfolding trajectory.
[10.23 am, 7/3/2026] hu35: This is a beautiful analogy because it highlights something we often underestimate in medicine:
Healing, like communication, is not merely the transfer of information. It is the transmission of meaning, emotion, trust, and presence.
The Telemundo commentators are compelling not because listeners understand every word, but because they communicate something that transcends language—joy, tension, urgency, hope, disappointment. Humans are remarkably adept at reading these non-verbal signals.
Medicine works in much the same way.
The consultation has two simultaneous conversations
EXPLICIT CONVERSATION
Words
Symptoms
History
Questions
Test results
↓
Medical information
IMPLICIT CONVERSATION
Tone
Rhythm
Silence
Eye contact
Posture
Facial expression
Presence
Attention
↓
Human understanding
Both conversations occur simultaneously.
Patients rarely remember every explanation of risks and benefits.
They almost always remember
“Did my doctor seem interested?”
“Did they really listen?”
“Did I feel understood?”
⸻
Trust is often built before understanding
A fascinating observation is that patients frequently decide whether they trust a clinician within the first minute or two—before the detailed medical discussion has unfolded.
What informs that judgment?
Not scientific knowledge.
Rather:
* attention,
* warmth,
* confidence without arrogance,
* genuine curiosity,
* calmness,
* respectful silence.
These are communicated largely through the implicit channel.
Only after trust is established do explicit explanations become easier to receive.
⸻
The arts help explain this
The quotation about football commentary illustrates something medicine has perhaps forgotten.
Communication is not simply linguistic.
Actors know this.
Musicians know this.
Dancers know this.
Parents know this.
Infants know this long before they understand words.
Meaning is carried through
* timing,
* rhythm,
* emphasis,
* pauses,
* expression,
* movement.
Medicine uses exactly the same channels.
⸻
Why this matters clinically
Consider two physicians delivering identical information.
Doctor A
“Your scan looks good.”
while typing continuously into the computer.
No eye contact.
Flat voice.
Patient leaves uncertain.
⸻
Doctor B
Looks at the patient.
Smiles gently.
Pauses.
Turns away from the computer.
Says exactly the same sentence.
The biology has not changed.
The words have not changed.
The experience has changed completely.
The relationship has changed.
⸻
This fits beautifully into your framework
Earlier we distinguished three kinds of understanding:
* Science → explanatory understanding.
* Humanities → interpretive understanding.
* Arts → perceptual and experiential understanding.
This quotation suggests something even deeper.
The arts teach us not only how to perceive, but also how to communicate.
Perhaps the “Arts” domain should be expanded to include:
* Perceptual understanding (learning to notice)
* Expressive understanding (learning to convey)
* Relational understanding (learning to connect)
These are fundamental to every therapeutic encounter.
⸻
A possible principle
I think this could become one of the central aphorisms in your work:
Patients do not experience medicine as data. They experience it as a relationship.
Or perhaps even more broadly:
Medicine is not only the science of explaining disease. It is the human art of making understanding felt.
That sentence captures the lesson of the Telemundo analogy. Just as passionate commentary can engage people who do not understand every word, an attentive, present physician can convey safety, respect, and hope before a single diagnosis is fully explained. The explicit content matters enormously—but the implicit relationship often determines whether that content is trusted, remembered, and acted upon. In your emerging framework, this reinforces the idea that good medicine depends not only on integrating scientific, interpretive, and experiential understanding, but also on communicating that understanding through a relationship in which patients feel genuinely seen.
[2.51 pm, 7/3/2026] hu28: Until recently I spoke in terms of inductive and deductive reasoning. Then I learned about abductive reasoning and think that it captures the diagnostic reasoning much better!
The disease, the persons, and the interpersonal?
[2.57 pm, 7/3/2026] hu35: I don’t know her; please connect us
All relationships matter including the horde of relatives involved in what is illness, when to consult, whom to consult, and more. STD is also interpersonal in a very different way; stress is interpersonal.
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