Raw LLM Responses
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in
Exactly, Jeremiah. Isolated layers can’t deliver the full value of enterprise AI…
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in
I'm not really sure how this is news at this point... If you have been a consist…
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in
We must always put humans first and government must have human oversight always,…
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in
Evan Hunter Evan the nuclear analogy lands hard because it's exact. We didn't le…
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in
What a poor view of the future and of the way private economy works... the most …
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in
Nejdet Çağdaş Y. honestly, this might be the most underrated reason in the entir…
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JMS -- Digital engineering (with twins and simulation) is one side of a coin tha…
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in
This is the correction phase of the AI hype cycle that many experienced engineer…
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Comment
This really resonates with something I’ve been thinking about for a long time: AI isn’t just an intelligence race anymore, it’s becoming a trust race. The biggest challenge ahead may not be building more powerful models, but building systems that help humans validate, compare, and trust the outputs responsibly. Different AI systems already produce different answers, biases, and interpretations depending on the data, incentives, and framing behind them. That’s part of the philosophy behind ConsensusAI;not another standalone AI model, but a consensus and validation layer designed to compare multiple AI systems and identify the common thread, confidence level, and “Truth Index” between them. Ethical AI won’t come from blind trust in a single system.It will come from transparency, adjudication, accountability, and collective validation. The future probably belongs to AI systems that can explain not only what they concluded... but why multiple systems arrived there together.
LinkedIn
AI Safety & Risk
Founder | Building ConsensusAI – AI Consensus &…
2026-05-28T17:4…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | transparency |
| Secondary value | accountability |
| Alignment target | humanity |
| Stance | demanding |
| Emotion | approval |
| Value justification | The speaker emphasizes the need for transparency, adjudication, and collective validation in AI systems to build trust and ensure ethical AI. |
| Target justification | The speaker's focus on building systems that help humans validate and trust AI outputs responsibly implies a concern for the well-being of humanity as a whole. |
| Coded at | 2026-06-11T08:28:23Z |
Raw LLM Response
```
{
"value_primary": "transparency",
"value_secondary": "accountability",
"target": "humanity",
"stance": "demanding",
"emotion": "approval",
"value_justification": "The speaker emphasizes the need for transparency, adjudication, and collective validation in AI systems to build trust and ensure ethical AI.",
"target_justification": "The speaker's focus on building systems that help humans validate and trust AI outputs responsibly implies a concern for the well-being of humanity as a whole."
}
```