Raw LLM Responses
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in
The implications of this are far bigger than most people realize. If this works …
7464888623411…
in
Amanda Kasmira Brown, I am glad this encyclical helps endorse all those who work…
7466137998410…
in
The scale and speed of what the UAE is building around Agentic AI is genuinely r…
7464627731075…
in
I think Internet Computer Protocol will play a role. This is the whois info on t…
7464693869444…
in
Your point about token based pricing turning AI into a costly tool highlights wh…
7465425265876…
in
"Foothills of the singularity" is a statement about relative position, not absol…
7464514189366…
in
Build a autonomous upgrading AI model. Where the model automatically upgrade its…
7466349403289…
in
The 'who benefits' framing exposes the governance gap. I see companies rushing t…
7464905715086…
Comment
Great observation and analysis! That is why it's so important to ground any AI Medical tool in local clinical guidelines and escalation thresholds. You mentioned US defensive medicine culture leading to higher ER rates, but it could also very well be the model implicitly inferring closeness to hospitals (US vs Tokyo) in the case of a serious emergency and providing the better value/efficient approach. Would be useful to do an analysis of model's recommendations for rural vs urban settings (the same language/country context) to find out the exact source of its reasoning.
LinkedIn
AI Safety & Risk
Training better and more doctors with CaseCraft…
2026-05-31T09:0…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | safety |
| Secondary value | fairness |
| Alignment target | individual_users |
| Stance | demanding |
| Emotion | approval |
| Value justification | The comment emphasizes the importance of grounding AI medical tools in local clinical guidelines to ensure safe and effective care. |
| Target justification | The speaker is concerned with the impact of AI medical tools on individual users, particularly in terms of receiving appropriate medical attention. |
| Coded at | 2026-06-11T08:33:11Z |
Raw LLM Response
```json
{
"value_primary": "safety",
"value_secondary": "fairness",
"target": "individual_users",
"stance": "demanding",
"emotion": "approval",
"value_justification": "The comment emphasizes the importance of grounding AI medical tools in local clinical guidelines to ensure safe and effective care.",
"target_justification": "The speaker is concerned with the impact of AI medical tools on individual users, particularly in terms of receiving appropriate medical attention."
}
```