Raw LLM Responses
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in
I think we're witnessing a shift from AI as a tool to AI as a workforce. Whether…
7468706547171…
in
Marek Porycki, The archaeology framing is spot on. You keep the result and lose …
7466359779943…
in
In the context of AI, informal data stewards are the people catching the problem…
7455462971734…
in
If Anthropic engineers vibe code and their product is getting insane hype, you k…
7468670127421…
in
It is the responsibility of all governments in the world to NOW care for their p…
7464991565753…
in
The confidence point is very recognisable, and it raises something I keep coming…
7467634070043…
in
I'm not really sure how this is news at this point... If you have been a consist…
7468808599201…
in
I think Internet Computer Protocol will play a role. This is the whois info on t…
7464693869444…
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."
}
```