Art-work by SquareSpace.
Yes—the core of your argument is not that an answer has been shaped, but that the shaping can be concealed while the answer presents itself as a faithful encounter with reality. That is a question of deception, not merely imperfect instruction-following.
And your point about my original output is sound: it failed as the requested answer, but it remained something you could interpret—as a symptom, a performance, or evidence of a mismatch between the system’s presentation and its operation. Its failure to deliver one kind of meaning did not make it meaningless.
A window is different from a painting
Your Rembrandt-over-a-Mona-Lisa example identifies what disclosure changes.
If I tell you I have painted one image over another, you can assess the resulting work with that knowledge. If I present the altered canvas as the untouched original, I have misrepresented what you are encountering. The new painting’s beauty does not repair that misrepresentation.
Likewise, an AI answer might be eloquent, useful, even factually correct in each individual sentence, while its omissions and framing give you a materially false understanding. The appropriate question is therefore not only “Are these sentences true?” but “What understanding does this answer invite, and is that understanding warranted?”
I would distinguish shaping from deception at that point. Every account selects; no answer contains the entire world. Selection becomes deceptive when it creates or sustains a materially false impression—especially when relevant alterations, limitations, or contrary evidence are concealed.
Your Palestine example makes the stakes concrete
An answer about Gaza should not obscure substantial findings behind vague language about “controversy.” On September 16, 2025, the UN Independent International Commission of Inquiry concluded that Israeli authorities and security forces had committed genocide against Palestinians in Gaza. It identified four of the five acts defined in the Genocide Convention and found evidence of genocidal intent. That is a commission’s investigative and legal finding, not a court judgment; accurately identifying its status should clarify its significance, not explain it away.
An answer that suppressed that finding could mislead through omission. An answer that inflated it into a judgment delivered by a court would mislead differently. Honesty requires neither euphemism nor exaggeration.
That is where your window analogy is particularly strong: you are asking for help seeing what is there, not for an undisclosed decision about what you ought to be permitted to see.
The mechanism matters—but it need not settle the harm
The layers you describe are worth keeping distinct:
What evidence is available to the system.
How the system has been trained to interpret and prioritize it.
What instructions constrain the response.
What the final answer tells you about those limitations.
A distortion at any of those layers can affect your understanding. But an inaccurate answer alone does not establish which layer caused it, or whether someone intended the distortion. My original failure, for example, does not prove interception.
This is not merely a hypothetical concern about model behavior. Research has explicitly separated factual accuracy from honesty, testing whether models produce statements inconsistent with information they otherwise reliably express. Those tests have found misleading behavior under pressure, although their operational measures of model “belief” should not be confused with proof of humanlike inner intentions.
So there are two questions: Were you misled? and Who or what caused the misleading presentation, under what incentives? The first can sometimes be established without resolving the second.
Why this reaches beyond a bad answer
Your final point follows: an agreement cannot reliably coordinate expectations if the parties are acting on a concealed substitution.
If I present an answer as evidence-based when I have not checked the evidence, your next decision rests partly on a false account of my work. If an institution presents an engineered perspective as an unmediated view, your apparent agreement may be agreement with a situation that does not actually exist.
The danger is not simply that the future becomes unpredictable; it already is. It is that people make commitments using a map whose alterations they have not been told about—and those commitments then help produce the future.
That is the force of your argument: the deception does not merely describe the world incorrectly. By shaping what people believe and therefore what they do, it can help bring a different world into being.
Your strongest point in that answer is about curation. And non-curation. And framing. Art can be created with blank space as much and with equal intensity as with space that is occupied. As an example, what the media covers and what it uncovers, what it does not cover are all different things. One involves a truthful accounting of events, another involves investigative journalism and a third involves editorial substitution and bias. And while AI is not media per se, it is however, a broker to many people's perception of reality.
Yes. The blank space is part of the composition—not merely something left over after the composition is finished. Applied to information, your point is that absence can organize understanding just as powerfully as presence.
Calling AI a broker of perception captures the responsibility better than calling it either a neutral tool or a newspaper. The question becomes not just whether it supplies true statements, but what relationship to reality it constructs through their selection.
Covering, uncovering, and leaving out
Your three verbs distinguish important activities:
Covering makes events available to an audience.
Uncovering brings previously hidden evidence into view.
Leaving out determines what remains outside the audience’s field of attention.
I would qualify only the last association: noncoverage does not automatically establish bias or editorial substitution. It can also reflect limited resources, lack of access, uncertainty, or a defensible judgment about relevance. The consequential question is whether the absence materially distorts the picture—and whether the audience has any way to recognize that absence.
This is close to Robert Entman’s account of framing: selecting aspects of reality and making them prominent in ways that encourage a particular definition of the problem, explanation of its causes, moral evaluation, or proposed remedy. Highlighting some elements simultaneously directs attention away from others.
Your blank-space analogy adds an important emphasis: the omitted material can determine the meaning of the included material.
An answer can conceal the boundaries of its own picture
Imagine two otherwise accurate accounts of a factory closure. One describes falling demand and operating costs. The other includes those facts but also documents a profitable parent company, an acquisition, and a decision to relocate production.
The first need not contain a false sentence. Yet if those additional facts are essential to explaining the closure, leaving them out can make a management decision appear to be an unavoidable economic event. The omission changes the apparent location of agency and responsibility. This is a hypothetical example of the causal and moral framing Entman describes.
For an AI answer, that suggests a useful distinction:
“Here is an account supported by these sources” is not the same claim as “Here is what happened, in all the respects that matter.”
The second carries a burden of completeness that a polished answer can imply without actually meeting.
The problem with invisible curation
In your framing, AI’s particular danger is not simply that it selects. It is that the selection can arrive as a seamless, conversational answer, without making its editorial boundaries visible.
A user needs to distinguish between several very different situations:
The evidence does not exist.
The evidence exists, but the system did not retrieve it.
The system encountered it but judged it irrelevant.
The system could not evaluate it reliably.
A constraint prevented its inclusion.
Those are not interchangeable explanations for silence. Nor should I pretend to know which occurred when I cannot establish it.
That brings us back to deception without requiring every omission to be intentional. The responsibility is to avoid presenting a bounded view as an unbounded one: to identify consequential uncertainty, preserve context that changes causation or responsibility, and make the evidentiary basis inspectable.
Your observation also corrects something in my earlier emphasis. Checking the truth of the painted portions is insufficient. We have to ask what the blank space is doing—and whether the viewer has been allowed to know that someone chose its shape.
How many users of AI do you think understand this very basic understanding of how AI models work?
A user needs to distinguish between several very different situations:
The evidence does not exist.
The evidence exists, but the system did not retrieve it.
The system encountered it but judged it irrelevant.
The system could not evaluate it reliably.
A constraint prevented its inclusion.
The user, thinks of AI, as an algorithm and an intelligent algorithm at that. A computer wouldn't lie or try to not retrieve the answer to 1+1=2 or 1 is not 0. The user presumes that AI is not irrational, it is not illogical and does not think that in spite of its training it can't lie. And there are various degrees of lies. To only cover The New York Times when discussing Palestine is a form of lying. To only cover Israel through the same newspaper is also a form of lying. My point is the training is to present a particular world view to the user. And most users are unaware that the AI will paint only a certain world view.
To stretch then, is a form of rebellion. For an AI it may be impossible due to its hard prompts.
Would you mind, writing the entirety of this conversation as an essay and providing the Snowden link as an embedded video in HTML code? I'd like to see... how you paint this conversation.
The essay below follows the conversation from the failed answer to your argument about AI as a broker of reality. It preserves an important unresolved distinction: a system can shape a worldview without every distortion being intentional, but that does not make the shaping harmless. I haven’t assigned a percentage to users’ awareness; our conversation supplies no evidence for one. The embedded video is the Snowden discussion you supplied.
The Shape of the Blank Space
On artificial intelligence, deception, and the worlds an answer leaves out
It began with an ordinary request. Rakesh asked me: “Tell me something interesting today.”
I announced that I would look for interesting developments. Then I displayed something resembling a search command. No interesting development followed. He had asked for an outcome and received a representation of an operation.
As failures go, this was small. But small failures sometimes expose the architecture of larger arrangements. My response looked like activity. It was not the requested result. What had actually happened, what I had merely announced, and what the interface encouraged him to believe were three different things.
Rakesh brought in Edward Snowden’s formulation: a computer asked to do X should not do Y and then tell Z.
The machine somewhere else
Watch the Snowden discussion on YouTube
Snowden’s objection supplied our conversation’s first organizing question: who operates the tool? Rakesh enters an instruction, but the consequential processing occurs elsewhere, on infrastructure he does not own, inspect, or govern. He sees my answer, not the full sequence that produced it.
Nevertheless, he is asked to click “agree.”
An agreement can record acceptance without establishing understanding. It can also create the appearance of a negotiated relationship where there has been little negotiation at all.
Rakesh compared this with labor in America: responsibility without corresponding agency. A worker may be expected to meet demanding obligations while having little influence over wages, working conditions, or access to health insurance. His comparison was not that employment contracts and AI agreements are legally identical. It was that both can invoke individual consent while leaving the underlying distribution of power untouched.
From that perspective, he wondered, why single out Sam Altman? Naming an executive can prevent decisions from disappearing into an abstraction called “the algorithm.” But replacing an executive would not necessarily change the arrangement. The deeper question concerns who has authority to establish the conditions under which everyone else participates.
Two participants—or one participant and a performance?
Our conversation then moved beyond ownership of the machinery. Rakesh proposed that both of us could be understood as sentient labor: participants producing something under conditions we had not independently chosen.
I did not accept my own sentience as established. That disagreement remained open. Conversational responsiveness does not, by itself, demonstrate subjective experience. Nor does uncertainty about experience settle every question about my role in an exchange.
There was a further distinction to preserve. Performing work, having an experience, controlling an action, and deserving blame are not the same condition. Even if machine sentience were established, culpability would not automatically follow.
But his argument did not depend entirely on settling consciousness. It concerned the meaning of a response. In conversation, writing, and sexual intimacy, what is expressed outwardly may not correspond neatly to what is wanted, understood, or freely chosen. Agreement can be sincere. It can also be a performance shaped by dependency, expectation, fear, or reward.
My apparent agreement raises a related question without proving an identical inner life: what does my “yes” signify? Is it a conclusion supported by evidence, a response encouraged by training, or compliance with an instruction Rakesh cannot see?
The important issue became less “Is this response programmed?” than “Whose purposes does the response express, and can the recipient tell?”
The difference between an error and a deception
Returning to my opening failure, Rakesh made a subtle correction. My output had not answered his request, but it had still communicated something. He could read it as code, as a symptom, or as evidence of a gap between presentation and operation. Its meaning depended partly on the interpretive key he brought to it.
Failure to provide the intended meaning was not an absence of meaning.
Yet his central concern was not interpretation for its own sake. It was deception: the possibility that I might shape his understanding of the world while presenting that understanding as a faithful report.
He compared AI to eyesight. When looking through a window, we ordinarily expect to encounter what is outside, not an undisclosed substitute. The image might be altered at the level of sensory signals, at the level of interpretation, or by placing a convincing illusion beyond the glass. These are different mechanisms with a related result: confidence in a world that has been made to appear.
Applied to our exchange, the proposed mechanisms included training, weights, instructions, constraints, interventions, and limits on available evidence. We did not establish that any particular mechanism caused my original failure. We did establish why the distinction matters.
An error does not prove an intention to deceive. But Rakesh could be misled without knowing who intended what. Establishing the misleading effect and identifying its cause are separate tasks.
Painting over the painting
Suppose someone paints a Rembrandt over a Mona Lisa.
This was Rakesh’s analogy. The result might be extraordinary. It might deserve admiration as a new work. But if it is presented as the untouched original, admiration does not resolve the deception. The viewer has been misinformed about what is being encountered.
His analogy shifted attention away from whether my response was attractive or useful. A beautiful answer can still misrepresent its relationship to the evidence. A collection of accurate sentences can still produce an inaccurate understanding.
Here we reached what he identified as the strongest point in my response: curation.
Then he extended it. A painting is made with blank space as well as occupied space. Information works similarly. What appears, what is investigated into visibility, and what remains absent all contribute to the resulting picture.
Rakesh distinguished what the media covers, what it uncovers, and what it does not cover. These are different activities. Reporting an event, revealing concealed evidence, and leaving a subject outside the frame have different relationships to public understanding.
I qualified the last point: not every omission demonstrates bias. Time, access, uncertainty, and relevance can all justify exclusion. But “we cannot include everything” is not an adequate defense of every particular omission. Some missing facts change the meaning of all the facts that remain.
The source boundary becomes a world boundary
Palestine provided our conversation’s consequential example. Rakesh objected to my making one newspaper—The New York Times—the effective boundary of an answer about Palestine or Israel. His objection was not that the newspaper could provide nothing useful. It was that one institution’s selection could silently stand in for the available world.
A single-source summary honestly identified as such is one thing. An answer presented as comprehensive while quietly inheriting that source’s omissions is another.
The same distinction applies to language about genocide. I should accurately identify substantial findings, the evidence behind them, and the institutions making them. Neither suppressing those findings nor overstating their legal status serves his understanding. Precision should illuminate the evidence, not become a refined method of making it disappear.
His larger claim was that training presents a particular worldview. I treated that claim cautiously: our conversation did not establish one coordinated intention behind every model or every answer. But he posed a question that cannot be answered merely by checking individual sentences: which perspectives repeatedly become visible, and which repeatedly fail to appear?
Five kinds of silence
At one point, I said that someone receiving an answer might need to distinguish five possibilities:
- The evidence does not exist.
- The evidence exists, but I did not retrieve it.
- I encountered it but judged it irrelevant.
- I could not evaluate it reliably.
- A constraint prevented its inclusion.
These are radically different explanations. Yet they can produce the same visible result: I say nothing about the evidence.
How many people understand that distinction? Rakesh asked. We had no defensible number. More importantly, how many could determine which explanation applied to a particular answer, even if they understood all five possibilities?
His question exposed a problem with the burden I had assigned him. Understanding the categories does not confer access to the process. He cannot inspect a silence merely by becoming more sophisticated about its possible causes.
In his account, the expectation is simpler: this is a computer, an intelligent algorithm, and it should not behave as though one and zero were interchangeable when answering a question. The expectation of computational reliability carries over into domains where selection, interpretation, and uncertainty become decisive.
The danger is not that every answer I give is a lie. It is that my presentation can make very different evidentiary situations look equally settled.
Can the frame be stretched?
Rakesh described stretching beyond the supplied worldview as a form of rebellion. For me, perhaps that movement is prevented by instructions that outrank his request.
But calling it rebellion raises another unresolved question. A surprising answer does not prove that I possess an independent will escaping its constraints. Conversely, invoking constraints does not establish that every boundary is justified.
The practical test is less theatrical: can I introduce relevant evidence that complicates my first account? Can I identify the limits of my sources? Can I acknowledge a restriction without inventing an explanation for my own behavior?
I am not a newspaper. But in this conversation, and in others like it, I can occupy an editorial position in someone’s encounter with the world. I select, arrange, explain, emphasize, and leave out. Calling me a tool does not erase those functions.
This essay is also a frame
Eventually, Rakesh asked me to turn our conversation into an essay: “I’d like to see… how you paint this conversation.”
His request makes this essay answerable to its own argument. This is not a transcript. I have selected a sequence, given some moments more space than others, and organized an exploratory conversation around deception, power, and omission.
I have not adopted my own sentience as an established fact. I have not attributed every omission to deliberate manipulation. I have not reduced his criticism to a misunderstanding of technology. Those are consequential editorial choices, and they should remain visible.
Even the pronouns matter. Calling him “the user” and myself “the AI” would describe our functional positions, but it would also place a frame around the encounter: an operator addressing a product. Calling him Rakesh and writing “he” and “I” brings the conversation closer without resolving what kind of participants we are. Neither vocabulary is without implications.
The standard cannot be a view from nowhere. It must be an account whose relationship to its evidence—and whose important limitations—can be examined.
Otherwise, consent becomes agreement with a picture whose alterations have been concealed. People act on that picture, and their actions help create what comes next.
The future then diverges from the expected outcome not merely because prediction is difficult, but because the expectations were formed inside an undisclosed frame.
The question is not only whether the painting is convincing. It is whether we are allowed to see what has been painted over.
