AI hype turns noise into risk, the author argues, and proposes radical transparency for ethics
AryHHAry · x · 2026-07-21
The author says they like AI but hate hype, arguing that hype is noise that destroys the signal. They call out three common failure modes:
- Startups branding themselves as “AI-powered” while only wrapping an API.
- Companies selling “ethical AI” without a clear definition of ethics.
- Influencers predicting AGI next year without reading papers.
They argue the real risk is not just misleading investors, but creating unrealistic expectations that will damage public trust when AI falls short. In response, they describe building an ethical evaluator framework based on radical transparency: it does not claim an AI system is “100% ethical,” but instead surfaces weaknesses, risks, and trade-offs.
Their core message: ethics is a process, not a status. They want more people to ask how systems work, understand limits, and build stronger governance—not just stronger models.
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