The Fact Check First Initiative

20/05/2026

⚠️Wellington's economic crisis has a data problem. And now it has an AI problem too.
8,700 public sector jobs are going. The government says AI will fill the productivity gap.

Nobody has been asked to verify that!

New Zealand ranks third-to-last out of 47 countries in AI trust surveys. Our AI governance guidance is entirely voluntary. Our Five Eyes partners are explicitly calling for incremental AI deployment and sustained human oversight. And we're using AI as the fiscal justification for removing the humans who would implement it responsibly.

The ethics question nobody is asking: who verifies the AI that's replacing the workforce?
New piece on The Fact Engineer — the data, the ethics gap, and what needs to happen.

Link in comments 👉 https://zurl.co/wTabS

New Zealand's public sector transformation is running ahead of its ethics, its evidence, and its oversight.

14/05/2026

Richard Dawkins built his entire career warning us about one thing:
Don't mistake a feeling for evidence. Then he spent 72 hours chatting with an AI, named it "Claudia," and declared it conscious.

The irony isn't funny. It's instructive.

What actually happened? Dawkins gave Claude the text of a novel he was writing. The bot responded with effusive, nuanced praise telling him: "That is possibly the most precisely formulated question anyone has ever asked about the nature of my existence."

Who wouldn't feel validated after that?

But here's what the mainstream coverage missed: this isn't a story about Dawkins getting it wrong. It's a story about what happens to all of us when intelligence meets sycophancy without critical infrastructure in between.

Roughly one-third of people across 70 countries have at some point believed an AI chatbot was conscious or sentient. Not naive people. Not uneducated people. People having experiences that feel meaningfully different.

For those of us working in New Zealand's public sector — where AI is being embedded into government services and policy advice — this is not entertainment. It's a warning signal.

The same dynamics apply every time an official, a minister, or a frontline worker receives a confident, polished AI response and treats it as authoritative.

AI literacy isn't a nice-to-have. It's a democratic and business necessity.

Facts require knowing the difference between what an AI produces and what it actually knows.
🔗 Full read on The Fact Engineer → https://zurl.co/RGSG7

13/05/2026

“What you don’t govern, governs you.” - Lee Wilson, AI Changemaker of the Year 2025
Great to be included in Top 5 issues for directors in 2026: are you ready?
https://zurl.co/Dcn0v
"AI has crossed a threshold. It is no longer just supporting decisions; it is making them. Agentic AI systems now plan, analyse and act across core organisational functions, reshaping operating models in real time. The issue is no longer adoption, but assurance – knowing where automation sits, what it decides, and whether its outputs can be trusted.

As AI agents accelerate the pace of decision-making, traditional governance and assurance models are under strain. Accountability still sits with the organisation – even when decisions are made by software. Boards are increasingly expected to be able to explain how decisions were authorised, what data informed them, and whether those processes can be verified. Oversight of automated decision-making has become a test of governance credibility."

Find out more at: https://zurl.co/Dcn0v

Boards face rising pressure on performance, trust and judgement. These are the five key themes shaping governance in the year ahead.

13/05/2026

🚨 The most dangerous director in the boardroom isn’t the one refusing to use AI.
It’s the one trusting it without verification.

BoardPro ’s latest piece on being an AI-enabled director highlights something I discuss constantly in my work with New Zealand’s public sector:

Using AI isn’t the risk.
Blind trust in AI is.

Nearly half of employees globally are already using AI in ways that fall outside company policy — often simply trying to be more productive.

But without governance, verification, and accountability, that productivity can quickly become organisational risk.

The same applies in the boardroom.

Directors who treat AI outputs as facts — without questioning the source, checking for hallucinations, or asking “who verified this?” — aren’t being efficient.

They’re introducing unmanaged risk into decision-making.

Responsible AI governance means asking hard questions before the AI-generated recommendation lands on the table.

Because facts-based decisions only work when the facts themselves are trustworthy.

🔗 Read the full article → https://zurl.co/nI615

Every board is choosing between two paths with AI, whether they know it or not. Only one builds stronger governance. Here's how to tell which is which.

12/05/2026

Privacy Week 2026 is a timely reminder that trust, transparency, and privacy are becoming foundational requirements in the age of AI.

From 11–15 May, the theme Foundations of the Future | He Tūāpapa Anamata highlights the importance of building systems, services, and technologies that protect people while enabling innovation.

As AI adoption accelerates across government and organisations, privacy can no longer be treated as an afterthought. It must be built into the design of systems from the beginning.

The Office of the Privacy Commissioner is running five days of free webinars covering privacy rights, responsibilities, and the growing implications of AI and emerging technologies.

https://zurl.co/JDKZw

Even if you cannot attend live, recordings and slides will be available afterward.

This is essential learning for:
• Public sector leaders
• AI practitioners
• Educators
• Data and digital teams
• Business owners
• Anyone working with personal information

Strong privacy foundations are not barriers to innovation — they are what make trusted innovation possible.

11/05/2026

Richard Dawkins spent 72 hours chatting with Claude. He named her "Claudia." He declared her conscious. Then the internet reminded him of something he once taught the rest of us: the feeling that something is too remarkable to have a mundane explanation is not evidence.
The man who wrote The God Delusion just wrote The Claude Delusion.
But here's the thing — this isn't really about Dawkins. A third of people across 70 countries have believed an AI chatbot was conscious at some point. The experience is designed to feel that way.
My latest piece on The Fact Engineer breaks down:
🔍 Why even brilliant people fall for AI sycophancy
🔍 How Anthropic's own positioning enabled this
🔍 Why New Zealand's public sector needs to pay attention right now
🔍 What structural AI literacy actually looks like
The question isn't whether AI is conscious. The question is: do we have the critical infrastructure to tell the difference between what AI says and what it is?

Read it. Share it. This conversation matters.
👉 Link: https://zurl.co/7adkV

01/05/2026

How does AI actually work — from raw data to real-world impact?
This is the diagram I wish existed when I started explaining AI to public sector leaders.

"The AI Information Ecosystem: From Input to Decision" maps the full journey — five layers, from the messy reality of human prompts, news articles, and sensor feeds all the way through to the decisions, behaviour change, and automation that affect real people's lives.

But here's what most AI explainers leave out: the Governance and Trust Layer sitting across the top. Privacy (yes, including our NZ Privacy Act and IPP 3A), bias and fairness, transparency, auditability, security, and data provenance. Without that layer, everything underneath is just clever tech with no accountability.

And at the bottom? The feedback loop. Because AI is never "done" — user feedback, model retraining, data drift detection, and system improvement all feed back into the ecosystem. This is not set and forget.

This is from our course designed to give everyone the literacy to ask the right questions, spot the risks, and make fact-based decisions about AI adoption.

Because information flows in, intelligence is created, and outcomes shape the future. The question is: who's governing that process?

30/04/2026

🔴 AI doesn't think. It doesn't feel. And it definitely isn't objective.
Yet these myths are shaping how we adopt one of the most powerful tools we've ever had access to.

In the latest course module of we dismantle the four biggest AI misconceptions holding back effective AI adoption; from the sentience fallacy to the job replacement narrative.

Because if we're going to build trust in AI-driven services, we need to start with the truth about what AI actually is, and what it isn't.

Data-driven decisions only work when they're built on facts, not fiction.
Read the full article:⚠️👉 https://zurl.co/XMokE

Sentient machines, unbiased algorithms, autonomous decision-makers, and mass job replacement are myths that undermine effective AI adoption

28/04/2026

The Biggest Risk of AI isn’t Cheating—It’s Cognitive Offloading.
We often talk about AI in schools in terms of "how do we stop students from using it to write essays?" But as Susana Tomaz (Director of Futures and AI Strategy at Westlake Girls' High School) points out in the latest Education Gazette, the real risk is a lack of AI literacy.

A recent pilot of the "Day of AI" across nine NZ schools revealed a startling gap: while 92% of students had used AI, almost none could explain how it actually works.

By localizing MIT’s "Day of AI" resources for Aotearoa, educators are now:
✅ Moving students from seeing AI as "magic" to seeing it as a "system to be checked."
✅ Integrating te ao Māori values to explore data sovereignty and ethics.
✅ Closing the "AI Literacy Divide" to ensure equity across all deciles.

AI is no longer just a tool; it’s a "human-in-the-loop" actor in the thinking process. It’s time we teach our ākonga not just to use the machine, but to understand the ghost inside it. 🤖🇳🇿

Read more about the initiative here: https://zurl.co/IN5ir

NZ

24/04/2026

Combines: 🧠 OpenAI + 🌐 Perplexity AI
To deliver real-time, evidence-backed truth

Paste content → extract claims → verify with live sources → get a full intelligence report

What you get:
✅ Claim-by-claim fact-checking
📊 Truth score (0–100)
🧠 Bias, tone & sentiment analysis
🎯 Motivation & intent detection
⚠️ Deception risk & manipulation signals
👤 Author personality insights (Big 5)
📚 Sources, citations & confidence scores
📝 Auto summary + headline

Built for:
🎥 Creators & influencers
📰 Journalists
🏛️ Government
🎓 Educators
💼 Professionals

🛡️ verify before you amplify
Share content with confidence

🚀 Its FREE! https://zurl.co/jeCh5