Raw LLM Responses
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in
Marek Porycki, The archaeology framing is spot on. You keep the result and lose …
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Michelle L. Being obsolete after graduation will depend on their major & minor. …
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Your point about token based pricing turning AI into a costly tool highlights wh…
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So true. People never wunder why they are pushing Ai. It's not for the greater g…
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Matthew, this is an important moment. AI is no longer just technical or regulato…
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Strong explanation — especially the shift from isolated models toward layered AI…
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Pascal BORNET part of this awareness that we champion, is understanding that AI …
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Really thoughtful framing I don’t think AI can be “disarmed” in the sense that c…
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Comment
What strikes me is that we still talk about AI as if capability were the main variable, but it is not. The growing leverage point is the architecture of decision making around those capabilities. Systems don’t become fairer or wiser just because they become smarter. Without structural guardrails, acceleration only amplifies whatever logic is already in place. The question is not what AI can do, but what design assumptions we are silently scaling.
LinkedIn
AI Policy & Regulation
Architecting clarity and decision systems | Glo…
2026-05-27T05:4…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | fairness |
| Secondary value | none |
| Alignment target | society |
| Stance | critical |
| Emotion | indifference |
| Value justification | The speaker emphasizes the importance of fairness by stating that systems don't become fairer just because they become smarter, highlighting the need for structural guardrails to ensure fair outcomes. |
| Target justification | The speaker's focus on the architecture of decision making and the scaling of design assumptions implies a concern for the broader societal impact of AI, rather than just individual or organizational interests. |
| Coded at | 2026-06-11T08:21:06Z |
Raw LLM Response
```json
{
"value_primary": "fairness",
"value_secondary": "none",
"target": "society",
"stance": "critical",
"emotion": "indifference",
"value_justification": "The speaker emphasizes the importance of fairness by stating that systems don't become fairer just because they become smarter, highlighting the need for structural guardrails to ensure fair outcomes.",
"target_justification": "The speaker's focus on the architecture of decision making and the scaling of design assumptions implies a concern for the broader societal impact of AI, rather than just individual or organizational interests."
}
```