Raw LLM Responses
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in
Stand by me, Demis Hassabis... I create Sarinem Chat with Opal (your multi-modal…
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“Built right and deployed responsibly”...it remains to be seen how responsibly c…
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100% - It’s all about the value system that the AIs are introduced into. The who…
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Though not still in league of claude code or even codex but the direction is rig…
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Rand Strauss There is no alignment problem for LLM tech, so long as it makes mon…
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in
This is where most people actually get value- when they stop “learning Claude” a…
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The biggest AI debate is no longer about capability. It is about control, incent…
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This really resonates with something I’ve been thinking about for a long time: A…
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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."
}
```