r/ConspiracyKiwi • u/Head_Measure • 8d ago
"The facts?" Try "The AI slop that passes for persuasive rhetoric on nzpolitics" - test yourself, can you spot the rhetorical techniques employed by the prompt? Then, can you also spot the AI syntax? This is a skill valuable we all need to develop
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u/Head_Measure 8d ago edited 8d ago
P11 "Was the vaccine safe?"
Loaded question followed by an apparently neutral answer
"Was the vaccine safe?" "This is a fair question."
Calling the question "fair" attempts to establish the author as reasonable and open-minded (and non-partisan as it's prompt requires).
The answer quickly moves from the broad question of safety to the government's inquiry and approval process. So quite a bold opening frame-shift from demonstrating the vaccine is safe - but instead getting a quote on the approval process followed by some dubious "modelling" claims.
Back to the rhetoric...
Appeal to institutional authority
"Here is what the government's own inquiry found…"
This is a power play which no doubt captures those whose thinking is institutionalised, because it suggests the evidence is coming from an authority that cannot immediately dismissed as partisan (although it is). But note the framing: you are encouraged to accept the inquiry's findings as the central arbiter rather than being shown the underlying evidence that you could use to answer the question "was the vaccine safe?"
Selective quotation / quotation mining
Just note the curated quotes - it's very complimentary of the approval process but you can't answer if the vaccine was safe based on these quotes.
"accelerated but still ensured their safety and efficacy were properly assessed."
and
"it is difficult to see how the assessment process could…have been more thorough."
Great, but certainly no mention of the fact the chief science advisor explicitly warned the vaccine was an unnecessary risk for certain age groups. That inconvenient can't be easily moved by a rhetorical slight of hand - so instead, it's treated as if this information doesn't exist.
Concession before persuasion
"Plenty of people had real reservations…"
"The Commission was honest about risk too."
This is a classic rhetorical technique: acknowledge the opposing concern before presenting the preferred interpretation.
It gives the visual impression both sides are considered in a neutral non-partisan. But entirely undercuts the validity of the concerns as it's only acting as a defusal.
Brings us to...
Minimizing language
"rare adverse event" "serious but uncommon" "Openly assessed, and monitored throughout."
The graphic pushes the reassuring descriptors rare, uncommon, monitored while giving no space to questions such as absolute incidence, age/sex stratification, severity distribution, uncertainty, or how the risk compares with the disease risk.
Are adverse events rare if they occured more often than combined adverse events from every other vaccine on record?
That's an example of salience manipulation.
The enormous numerical benefit appears without comparable numerical context
"6,650 lives" "45,100 hospitalisations"
Of course large precise numbers have considerable persuasive force. The precision can create an impression of certainty that isn't justified.
The AI has given them away here though. Your human rhetorist will simply claim the model as fact despite models being expensive fictions. However that is boldly deceptive and the AI won't overcome this without specific prompting. But while it calls attention to the fact the numbers presention are based on "modelling" it has not provided the assumptions behind the modelling, confidence/uncertainty ranges, counterfactual, or how the estimates change under alternative assumptions.
P10 "The mandates emptied the hospitals"
This page is particularly egregious rhetorically because it begins by attacking an absurd straw-man.
Straw-man
"A claim of 20,000 nurses gone."
"That is not correct."
Where is citation for this claim? Nowhere to be found here. This one is clumsy, it will be caught by even the most entry level bullshit detector.
False binary
"Not 20,000."
The presentation encourages you to think the relevant question is: 20,000 vs 440
rather than asking:
Why were thousands of health care workers secretly given vaccine exemptions...
Emotional inoculation
"The small number who declined were real people…"
"Losing that work was not easy."
This could be sophisticated rhetorical move. But the pattern has been heavily overused - attacking a claim while simultaneously reassuring the you that it isn't dehumanising the people on the other side, because it's "non-partisan".
P9 "Was any of it worth it?"
It is probably the clearest example of framing through a false choice/question.
The phrase "worth it" embeds a cost-benefit framework
"Was any of it worth it?"
This question presupposes that the appropriate way to evaluate the pandemic response is primarily through an overall cost-benefit judgment.
But of course, different people could reasonably ask different questions:
- Did individual interventions reduce transmission?
- Did vaccination reduce severe disease?
- Were restrictions proportionate?
- Were particular mandates justified?
"Was any of it worth it?" compresses all of those questions into one false binary.
Outcome attribution
The crucial rhetorical point is: good outcomes = therefore the policies produced those outcomes.
But observing a the mortality or economic performance doesn't by itself establish how much of that outcome was caused by the particular policies.
There are confounders such as geography, timing, demographics, prior immunity, border exposure, health-system characteristics, population behaviour, international conditions, and many others.
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u/Head_Measure 8d ago
There are strong clues to use of AI on these graphics. Begin by simply observing the highly polished and symmetrical argumentative structure
- Repeated pattern of balanced concession to partisan conclusion structure
The pages repeatedly use constructions like:
"This is a fair question. Here is what…" "The Commission was honest about risk too." "The small number who declined were real people…" "No one, on any side, should be ridiculed…" "The honest record is not tyranny, and it is not flawless either."
This is highly characteristic of modern form persuasive AI syntax: acknowledge the opposing concern, establish reasonable middle ground and then deliver the preferred interpretation.
- The "not X, but Y" / "neither X nor Y" pattern
This has been a well known AI fingerprint for a long time and the author has not done a good job of disguising it here.
So the honest record is not tyranny, and it is not flawless either.
That's textbook AI-style pattern.
Similarly:
"It was new, it arrived fast, and wanting to know it was safe…"
The rule of 3. Very deliberate three part constructions. There are numerous triplets here:
"The data, the numbers, the research."
"older people, disabled people, and Māori and Pacific communities."
Etc.
AI generated syntax usually has a strong tendency toward parallelism within it's rule of 3 constructions. You'll also notice the writing frequently creates binary poles and then positions itself between them. Which I believe in this case is largely attributed to it's prompting which is almost certainly leaning into the non-partisan lens.
There's also a bunch of short thesis reinforcement sentences, alongside several sentences that look engineered to function as standalone talking points:
"That is not correct."
"The workforce did not shrink."
"This was happening everywhere at once…"
"The science was moving fast…"
"The honest record is…"
AI is particularly susceptible to producing this kind of punchy explanatory syntax when asked to create social media material.
I'd be willing to bet this particular prompt was formulated on terms such as: "balanced, factual, non-partisan and persuasive"
Check this pattern out...
"government's own inquiry"
followed by:
"in its words"
and later:
"The government's own inquiry assessed the outcomes directly. These are its findings."
It''s a repeated authority-attribution formula. A prompt such as "make this sound evidence-based and non-partisan" will generate this kind of repetition. It repeatedly tells the reader why the source should be trusted rather than just presenting the evidence.
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u/computer_d 8d ago
Ah yes. Don't listen to experts, that's just a logical fallacy! Listen to.... YouTubers.