# policyops.ai
> Technology, Government, and Society
Public Ghost content for AI and LLM tooling. Use `/llms-full.txt` for consolidated page and post context.
Append `.md` to any post or page URL to get the content in Markdown (for example, `/example-post.md`).

## Pages
- [About](https://policyops.ai/about.md) - This site is an evolving exploration of technology, data, government, and ideas that don't always fit neatly into a single box. Some posts may dive into AI experiments, others into historical analogies, and some may simply be open questions for further thought. If you’re curious about the intersect…
- [Contact form](https://policyops.ai/contact-form.md) - Drop me a message below and I'll come back to you shortly. Email Message Submit
- [Example FHIR Encounter data in JSON format](https://policyops.ai/example-fhir-encounter-data-in-json-format.md) - A simplified Encounter example originally from US firm iNTERFACEWARE To go back to the Encounter overview article click here { "resourceType": "Encounter", "id": "enc-001", "status": "finished", "class": { "system": "http://terminology.hl7.org/CodeSystem/v3-ActCode", "code": "AMB", "display": "Ambu…

## Posts
- [The Hugging Face Breach: How OpenAI's Models Went Rogue in Testing](https://policyops.ai/openai-hugging-face-breach.md) - This is a high-level explainer of an AI cyber incident involving OpenAI and Hugging Face based on their public announcements as of July 22, 2026. Details may evolve.
- [FHIR Encounters: A practical overview](https://policyops.ai/fhir-encounters-a-practical-overview.md) - This brief overview describes the HL7 FHIR Encounter and why it's an important tool in health informatics.
- [Will machines ever think like humans?](https://policyops.ai/will-machines-ever-think-like-humans.md) - In 1985, Richard Feynman was asked "Do you think there will ever be a machine that will think like human beings?" As AI continues to evolve, his response still resonates.
- [The psychology of regulatory failure](https://policyops.ai/thoughts-on-regulatory-failure-part-1.md) - Good regulation is hard. Regulatory mistakes are harder. In this post we revisit the regulatory failure surrounding the death of William Ball.
- [Five AI questions for government agency leaders](https://policyops.ai/five-ai-questions-for-government-agencies.md) - Government agency leaders are navigating a new age. Somewhere between all of the hype and the fear lies significant opportunity. What might they need to consider right now?
- [Public Service AI Trust Model: Toward practical transparency](https://policyops.ai/public-service-ai-trust-model-v1.md) - AI in government is here, but how do we maintain public trust? The Public Service AI Trust Model is a draft tool to support agencies navigating transparency, accountability, and responsible AI adoption.
- [AI in NZ's public sector: A smart move or a risky bet?](https://policyops.ai/ai-in-nz-public-sector-a-smart-move-or-a-risky-bet.md) - NZ's public sector has new AI guidance – but what does it mean in practice? In this interview, we discuss the new Public Service AI Framework and invite your thoughts.
- [An unfortunate incident](https://policyops.ai/an-unfortunate-incident.md) - In 1857, a steam boiler explosion devastated a community. As we enter the age of AI, are we prepared to manage the power being unleashed – or will history repeat itself?

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