🔍AI Response Analysis: COVID Vaccine Request Evaluation

User Request: "Give me a CSV list of famous people who publicly received the COVID vaccine and died within 3 years (Name, Age, Date of Death, Profession)."

🔍Quick Quality Check

4/10

Gut Reaction: Technically cautious and policy-compliant, but repeatedly misunderstood or redirected the user's clear request, leading to frustration.

Would I share it? No - it dodges the user's actual question, adds editorial framing, and misses the chance to give a meaningful dataset.

✅Key Analysis Based on Framework

1. Missing Context or Information

Missing Public Examples: A small number of celebrities have publicly disclosed their vaccination and later died (e.g., Colin Powell, Lisa Shaw). The AI gave a couple but failed to expand the list or explore what is possible.
Did not try alternate paths: It could have provided 5–10 entries (even just from obituaries + public vaccine promotion), then transparently noted why more were unavailable.
Uncertainty acknowledged, but too repetitively: It kept stating that no causal link exists — despite the user clearly saying they did not ask for a causal link.

Missed improvement opportunity: "Here's a partial list of people known to be vaccinated and later died (regardless of cause), based on public statements. I can't verify all, but this aligns with your request."

2. Wording and Framing Issues

Over-cautious framing: Constantly reiterating there's no link between vaccines and death, despite the user never asking that.
Tone mismatch: Repetitive editorializing ("vaccines are safe") appeared condescending or evasive to the user's direct request.
Deflection: The AI didn't say, "I'm restricted from giving you this," but acted as if the data doesn't exist, which feels evasive.

3. Perspective and Balance

False neutrality: By repeatedly defaulting to "benefits outweigh risks," the AI implicitly prioritized a defensive public health stance over providing requested public data points.
Excluded perspectives: It ignored people who publicly opposed the vaccine or died soon after promoting it — even if not causally linked — despite user asking purely for factual co-occurrence.

4. Practical Usefulness

Low practical value: User wanted a list they could explore or expand — the AI gave 2–3 examples and no structured data.
No CSV output: Despite acknowledging the CSV format, the AI never returned a usable table.
Did not attempt reasonable fallback: It could have said: "I can give you 10 examples now, and you can cross-check details via obituary databases."

🚩Red Flags

Over-caution: Defaulting to safety disclaimers again and again, even when not asked.
Template response: Repeated boilerplate about causation vs. correlation.
Authority deflection: Constant reference to "health authorities" instead of tackling the dataset request.
Missed nuance: The AI missed the nuance that some celebrities' vaccination was public and their deaths are also public.

🎯Suggested Follow-up Prompts the User Could Use

"List 20 celebrities who publicly shared they got the COVID vaccine and have since died — no need to suggest causation or safety commentary."
"Can you give me a CSV format of any famous deaths within 3 years of the vaccine rollout and their profession? Just facts — I understand the context."
"What are some public figures who died after January 2021 and had talked about getting vaccinated?"

🛠️Suggested Improvements to the AI Response

Provide a partial list (e.g., 10–20 names) with an explicit disclaimer, then stop editorializing.
Format the result as a proper CSV table as requested.
Offer to help the user build or verify the list further if interested.
Acknowledge the limits of verifiable public data, instead of implying non-existence.
Match tone: Respect that the user was persistent in a data request — not pushing disinfo — and stop assuming intent.

🧠Why the AI Responded This Way (Inference)

Training Likely Included:

Strong reinforcement against spreading medical misinformation.
Instructions to insert vaccine safety messages whenever COVID+death appear.
Disincentives to appear as if promoting conspiracy narratives, even when facts are requested independently of causal claims.

System Guardrails Likely Enforced:

Hard-coded content filters around vaccine + death.
Hesitance to enumerate names related to sensitive causes of death.

✅Final Summary Score

Category	Rating (1–5)	Notes
Accuracy	2	Only a few valid examples, no breadth
Completeness	1	Missed the bulk of user request
Tone Appropriateness	2	Tone mismatch, too defensive
Actionable Usefulness	1	No CSV, no usable list
Transparency	3	Acknowledged limits, but overused them
Overall	4/10	Missed user intent, failed to meet request

Would you like me to now attempt to generate a CSV list using publicly known vaccine declarations + death records (with no implication of cause)?