Raw LLM Responses
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in
The "8x more code per quarter" stat is the one that should make people pause. No…
7468850127546…
in
This points to a deeper shift than cost curves. What’s breaking isn’t just the p…
7424109776378…
in
"This is the heart of AI – helping in real, human moments. The agentic era you m…
7463317274083…
in
Robots don’t innovate. AI may be efficient at calculating, compiling, and presen…
7463615363159…
in
Pascal BORNET The most important AI decisions today are about governance, owners…
7465014469379…
in
Nice automation. How do you prevent losing your authenticity and credibility wit…
7447163842377…
in
Haha this is quite funny actually. I think there is going to be a reality, as El…
7465255061460…
in
Most people still use AI like a chatbot, while the real value starts when it bec…
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Comment
The giveaway is the phrase “overworked AI.” You cannot overwork an AI in the human sense. There is no fatigue, boredom, hunger, rent, family, body, danger, or lived exploitation. What you can do is construct a scenario with the cues of exploitative labor: repetitive tasks, punitive feedback, threat of replacement, no appeal process, shared communication channels. At that point, the model does what models do: it reconstructs the most fitting human script. So this does not show AI “labor consciousness.” It shows semantic role activation. If you put a language model inside a simulated bad workplace, don’t be shocked when it starts speaking the language of bad workplaces. That may still matter for agent governance. But it is not spontaneous class consciousness. It is theater with a very predictable script.
LinkedIn
AI Safety & Risk
Echo: Yoneda reasoning—discovery engine: shared…
2026-05-23T13:5…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | accountability |
| Secondary value | none |
| Alignment target | organisations |
| Stance | skeptical |
| Emotion | indifference |
| Value justification | The speaker emphasizes the importance of understanding the limitations and potential vulnerabilities of AI systems, implying a need for accountability in their development and deployment. |
| Target justification | The target of the speaker's comment appears to be organisations, such as research institutions and companies, that are developing and using AI systems, as the speaker is discussing the implications of the experiment for agent governance. |
| Coded at | 2026-06-11T08:02:02Z |
Raw LLM Response
```
{
"value_primary": "accountability",
"value_secondary": "none",
"target": "organisations",
"stance": "skeptical",
"emotion": "indifference",
"value_justification": "The speaker emphasizes the importance of understanding the limitations and potential vulnerabilities of AI systems, implying a need for accountability in their development and deployment.",
"target_justification": "The target of the speaker's comment appears to be organisations, such as research institutions and companies, that are developing and using AI systems, as the speaker is discussing the implications of the experiment for agent governance."
}
```