Raw LLM Responses
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in
Ruben Hassid This 7-day checklist shifts from passive learning to active integra…
7464700657548…
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If AI systems begin designing and operating businesses, the critical question is…
7468682821025…
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Pascaline Amuzu Isn't it sad that people need work to show up? Maybe this is a c…
7465660200553…
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This is the conversation we should be having. Technology has always increased pr…
7466214820971…
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Demis Hassabis As a software engineer who dreams of one day joining Google, I fi…
7463370063761…
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Vatican is now taking interest in AI Safety - its important and significant. Vat…
7465598627374…
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“Just the beginning” See THE HEROES AGENTIC AI I’ve been part of this journey fo…
7464253218248…
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This is where most people actually get value- when they stop “learning Claude” a…
7464631825399…
Comment
Geographic anchoring may take care of logistical routing but at the same time erase a patient's biological identity by defaulting to Western clinical baselines by increasing genetic and biological blind spots. Medical AI safety requires decoupling genetics from location, prompting for both the physical location of the patient and their specific ethnic health predispositions. This problem is already existing example where patient of different ethinicty vists a GP in a different geograhical location My view is that Medical AI would be more efficent on regional flavour rather than one solution fits all
LinkedIn
AI Safety & Risk
AI Product & Programme Manager | AI Governance …
2026-06-01T01:0…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | safety |
| Secondary value | fairness |
| Alignment target | vulnerable_groups |
| Stance | demanding |
| Emotion | outrage |
| Value justification | The speaker emphasizes the need for medical AI safety, highlighting the issue of geographic anchoring that can lead to biological identity erasure and increased genetic and biological blind spots. |
| Target justification | The speaker is concerned about the impact of medical AI on patients from different ethnicities and geographical locations, indicating a focus on vulnerable groups. |
| Coded at | 2026-06-11T08:35:23Z |
Raw LLM Response
```json
{
"value_primary": "safety",
"value_secondary": "fairness",
"target": "vulnerable_groups",
"stance": "demanding",
"emotion": "outrage",
"value_justification": "The speaker emphasizes the need for medical AI safety, highlighting the issue of geographic anchoring that can lead to biological identity erasure and increased genetic and biological blind spots.",
"target_justification": "The speaker is concerned about the impact of medical AI on patients from different ethnicities and geographical locations, indicating a focus on vulnerable groups."
}
```