I thought Grok was truth seeking, this is just plain old hallucinations
ETHICS
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Biased human prompting leads to more biased outputs
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Depends on how it is prompted. So probably more since biased humans are prompting the system.
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AI Hallucinations and Reasoning Errors Linked to Civilian Deaths
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hallucinations and reasoning errors that lead to accidental civilian deaths. which may have already happened, yesterday.
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OpenAI’s Unreliable Tech and War: An Ethical Debate
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tl;dr of something worth reading: OpenAI is full of shit, and perfectly happy to be using their unreliable tech for war. #DeleteChatGPT
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AI’s Societal Impact: Job Displacement, Life-or-Death Decisions, and Nuclear War Concerns
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It’s not just the AI that will be taking our jobs.
— Gary Marcus (@GaryMarcus) 1 mars 2026
It’s the AI that will be making life or death decisions.
And the AI that might lead to needless escalation, maybe even nuclear war.#DeleteChatGPT https://t.co/uRa5cvOix5It’s not just the AI that will be taking our jobs. It’s the AI that will be making life or death decisions. And the AI that might lead to needless escalation, maybe even nuclear war. #DeleteChatGPT
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Critique on AI Reliability and the Premature Race for Integration
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The race to shove AI into everything is grossly premature, because the tech fundamentally lack reliability. Meanwhile, the chance that we will get straight answers is probably close to zero. (Altman, for his part, doesn’t seem to care.)
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OpenAI criticism deserves nuance: frontier innovation requires visible risk
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I’m honestly tired of watching OpenAI get cast as the default villain in every AI debate. They try something bold, it’s dangerous. They move fast, it’s irresponsible. They partner, it’s corruption. They compete, it’s opportunism. Meanwhile, plenty of other companies move quietly, wait for validation, copy what works, avoid the hardest calls — and somehow escape the same scrutiny. Let’s be honest. OpenAI ships at scale. They deploy first. They test boundaries in public. That means they make visible mistakes. Visible tradeoffs. Visible bets. But that’s also what pushing a frontier looks like. If you’re the company actually attempting moonshots, integrating with institutions, scaling globally, and defining new categories, you’re going to absorb more risk and more criticism than everyone standing safely behind you. Do we really believe other AI companies aren’t navigating the same ethical gray zones? The same regulatory ambiguity? The same pressure between innovation and governance? Or is it just easier to project all systemic anxiety onto the biggest target? The standard keeps rising for OpenAI. Higher than for startups. Higher than for open source projects. Higher than for incumbents moving quietly in the background. Criticism is necessary. Accountability matters. But pretending only one company operates in tension with power, policy, and profit feels intellectually dishonest. Frontier innovation is messy. Governance is incomplete. The incentives are complex. If we want responsible AI, we should demand better systems, not just better villains. Because the reality is this: The companies actually trying to reshape infrastructure will always look riskier than the ones waiting to copy the outcome. And asking them to innovate without taking risk is asking them to do nothing at all.
→ View original post on X — @arrakis_ai, 2026-03-01 03:32 UTC
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OpenAI classified work deployment risks alignment concerns
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(1) Why the push into classified work now, when things are so hot? (2) when did you ready your models for the much more complex tasks you say classified work demands from AI? (3) What are the alignment risks associated with current OpenAI models that will be deployed by DoW?
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Laws Lagging Behind AI Capabilities: A Regulatory Challenge
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The problem with "all lawful use cases" is that most of those laws were written way before we had any idea what these AI tools were capable of. Things that no one could conceive of are now mundane reality. Laws have always been way behind the technology, and at this point they
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AI Safety Guardrails vs Usage Policies in National Security
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Other AI labs have reduced or removed their safety guardrails and relied primarily on usage policies as their primary safeguards in national security deployments. We think our approach better protects against unacceptable use. In our agreement, we protect our redlines through a