Paolo Garcia’s valedictory speech highlights the darker side of politics. He described the abuse he has faced and said safety concerns forced him to move house. What does his experience say about the need for political civility?

Te Pāti Māori has released a sweeping tax plan, including a $30,000 tax-free threshold and a wealth tax on net assets above $2 million. What behavioural effects could follow, and how much of it could a minor party realistically take into coalition talks?

Wrapping the show is our favourite segment: Fantasy Beehive. MP performance is ranked using our highly advanced, completely proprietary technology.

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So you’re sitting opposite your GP. It’s been months since your last appointment. This time, though, your doctor isn’t hunched over a computer screen double-checking Dr Google.

She’s looking directly at you.

Emboldened, you explain that your symptoms first appeared “in the morning”.

Instead of this, the AI scribe records: “every morning”.

It may not seem like much, but there’s a real problem here. A medical symptom appearing “in the morning” versus “every morning” can be the difference between a situational issue and a chronic one. Treatment then would differ, as would outcomes.

This transcription error actually happened, reminding us that even apparently low-risk AI tools need careful oversight.

Of course, if you’ve ever asked AI to summarise a meeting, you’ll recognise the problem: it gets most things right - until it doesn’t. In healthcare, small differences really matter. For example, a thunderclap headache that peaks in 60 seconds might be mistaken for a migraine; in fact, it can signal a ruptured brain aneurysm. Taking aspirin instead of calling an ambulance could delay urgent treatment, potentially leading to coma or even death.

New Zealand’s health system needs help. As our population ages, demand is rising. Workforce shortages leave clinicians carrying heavier patient loads. Long waits for treatment and ageing hospital infrastructure continue to place pressure on patients and staff alike.

That’s one reason medical AI’s promise is so compelling.

Used well, it can reduce paperwork, improve access to care, and make better use of scarce clinical expertise. Every emergency department now has access to an AI scribe, and early reports show doctors averaging one additional patient per shift. In South Auckland, AI-assisted retinal screening is helping identify diabetes-related eye disease. And Health NZ is preparing to use AI for one of the two reads required for mammograms.

The opportunities are real, and they’re multiplying. However, medical AI is moving into everyday clinical practice faster than we are designing systems to govern it. So what do we do?

A public national register of medical AI systems is a practical first step. Health leaders should know which AI tools are being used for what, how they have been validated for New Zealand populations, and who is responsible for monitoring their performance.

Even if a model functions well overseas, it may not here. Its accuracy depends on the data used to train it, so the data needs to reflect the people receiving care. Populations with different genetic, environmental, and behavioural profiles do not look the same when they are reduced to data points. Patients who are least well served by the health system now are at the greatest risk of being poorly served by AI tools.

And like their human counterparts, AI tools continue “learning” and so must be constantly evaluated. If performance is allowed to drift, problems could remain hidden until patients are affected.

A national register should tell us where AI is being used, who is accountable for overseeing each system’s performance, and when they should be reviewed. It will allow health leaders to decide when to pause, replace, or withdraw systems. That isn’t bureaucracy; it’s good governance.

Crucially, we also have to decide what we want AI tools to achieve. If AI scribes save clinicians time, we shouldn’t just assume that extra time will be used to see more patients or have longer consultations. Free time gets absorbed quickly if it is not directed towards something intentionally. Let’s aim for better conversations between physicians and patients, more time for careful diagnosis and less burnout of medical staff.

The same principle applies to screening and diagnostic tools. Earlier detection and wider access are genuine gains, but patients are not collections of data moving through an increasingly efficient pipeline. Good medicine requires trust, careful judgment, and relationships built on careful listening.

AI can strengthen these aspects of care. It can reduce paperwork, identify patterns clinicians might otherwise miss, and help professionals use their expertise where it matters most.

It can also quietly reshape healthcare around what is easiest to measure: speed, throughput, and cost.

New Zealand is already embracing medical AI. Let’s ensure we test it before deployment, monitor it throughout its life, and retire systems that don’t deserve our confidence.

This isn’t an argument to shackle technology. It’s an argument to pursue technology with a purpose: ensuring that humans remain at the heart of healthcare.

This op-ed was originally published in The Post on 21 August 2026.

Next: allegations of ballot theft and fraudulent voting in the 2025 local elections. A secret whistleblower and gang threats are also claimed. What does it mean for our general election?

Finally, ACT’s “one law for all” policy would strengthen property rights and reinforce parliamentary sovereignty over the courts. Is this a different version of the Treaty Principles Bill?

Wrapping the show is our favourite segment: Fantasy Beehive. MP performance is ranked using our highly advanced, completely proprietary technology.

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We then turn to Te Pāti Māori’s election strategy, with its focus on winning Māori electorate seats while encouraging supporters to party vote elsewhere. If successful, the move could create an overhang in Parliament—a quirk of our MMP system.

Finally, we reflect on the fallout from the attempted National Party coup. We discuss Christopher Luxon’s demotion of Minister Chris Penk: How this will affect National going forward?

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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Prime Minister Christopher Luxon has survived a coup attempt less than 90 days out from the election. We ask what this reveals about dissatisfaction within the caucus—and the media’s role in amplifying instability. Can National now present a genuinely united front?

We then turn to Labour's two bad polls. It may be a good week for them to land, but what can Chris Hipkins do—and what role is The Opportunity Party playing in all this?

Finally, we consider what comes next for National: another coup attempt, or is bad publicity actually good publicity?

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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We then turn to ACT’s classroom behaviour policy, which would allow disruptive students to be removed using reasonable and proportionate force. Is this a necessary intervention that protects students’ ability to learn, or does it risk escalating conflicts with students?

Finally, we discuss Winston Peters describing a statement by Chris Hipkins as a “lie”, and Chlöe Swarbrick’s ejection from the House after accusing Speaker Gerry Brownlee of “double standards”. We ask whether Parliament’s declining standards are weakening the quality of political debate.

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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We then turn to National’s decision to rule out The Opportunity Party as a coalition partner. With TOP polling close to 5%, we consider whether the move legitimises the party and whether its “centrist” reputation matches its policies.

Finally, we discuss the Greens’ campaign launch and proposed one-year pause on new AI data centre consents. We ask what the rise of minor parties says about political fragmentation, coalition incentives, and voting as self-expression.

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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We then turn to the Government’s proposed changes to council–iwi agreements as part of Resource Management Act reform. Will national rules provide greater certainty?

Finally, we discuss the names chosen for the new Cook Strait ferries, Kupe and Cook, and explain how the political reaction reflects a culture war in search of an opponent.

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We then turn to the latest polls, examining why individual results can mislead and how the Poll of Polls offers a clearer picture of an increasingly competitive election.

Finally, we discuss New Zealand’s newly announced strategic partnership with India and what it signals geopolitically. We also examine the $20 billion investment target in the free trade agreement, and why there are differing accounts of what it means.

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We then turn to the proposed under-16 social media ban, asking whether a law intended to protect children can be enforced without sacrificing online privacy.

Finally, we consider China’s nuclear-capable missile test in the South Pacific, and what New Zealand’s measured but uneasy response reveals about diplomacy as a small state caught between major powers.

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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We then turn to National’s KiwiSaver announcement, weighing compulsory saving against concerns that making KiwiSaver mandatory and lifting contribution rates changes the scheme people signed up for.

Finally, we consider ACT’s Regulated Professions Neutrality Bill and the difficult question of whether professional regulators can be made politically neutral when competence, expression, and contested political questions overlap.

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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The Digital Government Target State is coming.

That’s not a scary name I invented; it’s the name of an official government strategy. And recent announcements suggest the Government’s ambition is already taking shape.

Nearly 9000 public service jobs are set to be cut over the next three years, driven by anticipated AI efficiency gains.

The Social Security (Modernisation) Amendment Bill is the most recent example. Having passed under urgency, the bill allows the use of automated electronic systems to “make any decision, exercise any power, comply with any obligation, or take any other related action under any specified provision” under the statute. The stated intention is simple enough: use AI for routine eligibility checks in cases that are “straightforward and do not require discretion”. Fair enough.

But the legislation is not constrained to simple, rules-based decisions.

Many have raised concerns about whether automated decisions can effectively evaluate benefit eligibility.

The ghost of the Robodebt scandal looms large. Beginning in 2016, Australia used an automated debt assessment tool that miscalculated debts owed to the government, leaving a trail of stress and hardship in its wake. No one wants that here, but technical problems are not the only kind we face. There are political and constitutional questions as well.

What kinds of tasks are we comfortable automating? Are there things we think only a human should do?

Imagine three different scenarios.

In an understaffed emergency room, AI triages who gets care first.

Traffic chokes roads. AI decides not only congestion pricing, but recommends where new roads should be built.

The crime rate spikes. Widespread surveillance uses AI tools to process information and direct where police resources are deployed.

Each of these scenarios is already being trialled overseas. In every case, a subtle shift is being made. AI is moving from providing analysis to making judgements—about priority, trade-offs, and the allocation of resources.

How would you feel sitting in a hospital waiting room knowing a human hasn’t yet thought about you? Or receiving a letter informing you that your land is being acquired for a new road because an algorithm says so? Or knowing the police may or may not visit your neighbourhood based on datasets and risk probabilities?

Every time AI tools step into the realm of important political decisions, the typical response is “get a human in the loop”. The Social Security (Modernisation) Amendment Bill still requires a “specified person” to be accountable for the tool. All well and good.

But let’s be honest. Humans take the path of least resistance. If the decision-making machine keeps making reasonable recommendations, at some point, we will all fall into the trap of saying “yes” by default. The effects of automation bias are well known, especially when we are busy and under pressure.

Do this for long enough and we lose the capability to challenge automated decisions. We forget what independent judgement feels like. The mental muscle weakens.

That doesn’t mean we should we reject AI entirely. Used well, AI could enhance government capability, speed up services for people who need support, and help keep rising costs under control.

Will we have government with algorithms or government by algorithms? The difference matters, and we need a strategy that embraces the former without falling prey to the latter.

The first step is to implement “cognitive forcing” in decision-making systems.

Put simply, a human reviewer should record an initial judgement before seeing an AI recommendation. Once the recommendation is revealed, the human can accept or reject it, but any decision must be logged with a justification for the final decision.

Where AI processes decisions at scale, we should also use blind testing. Take a sample of cases and have them assessed by humans without seeing the AI output. Then compare the results.

Transparency matters too. New Zealanders should be able to check a single public register to see where AI is being used across government, how much autonomy it has, and who is accountable for it.

Most people will be happy with the AI notetaker at the GP.

I am happy with AI triaging the emergency room, but that might make some people a bit queasy.

I’m not sure I want a Ministry of Health GPT choosing funding allocations or where to build a hospital. But it’s hard to explain why that’s different.

We will inevitably disagree about where to draw various lines, but let’s have a debate about where those lines should be.

To govern is to choose. If we let those choices migrate quietly into systems we cannot see, question, or hold to account, we could lose democratic oversight. Worse, we might not even notice.

This op-ed was originally published in The Post on 16 June 2026.

We then turn to Labour’s disputed policy costings, election-year sparring over fiscal credibility, and whether an independent costing agency would clarify the debate.

Finally, we discuss Matthew Hooton’s appointment as editor of The Post, and what it reveals about the changing shape of legacy media.

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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We then turn to Labour’s unofficial campaign launch, following its first policy announcement in more than six months. We also discuss the controversy around Labour candidate Rakesh Naidu and the party’s newly unveiled list.

Finally, we head to Fieldays to ask whether National can still rely on the rural vote, as ACT sharpens its pitch to farmers and Labour looks for a way back into the regions.

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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We then turn to the Social Security (Modernisation) Amendment Bill and the broader powers it grants to use artificial intelligence tools in welfare decisions. We ask whether the promise of efficiency can be balanced with human judgement and accountability.

Finally, we look at Winston Peters’s efforts to rescue Moana Pasifika after the Super Rugby franchise entered liquidation. Can government support for the team be justified as a form of sports diplomacy?

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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We then turn to Mike Smith’s climate case against major emitters and the Government’s plan to respond with legislation, asking whether Parliament is protecting legal certainty or interfering with a case already before the courts.

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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We then turn to the proposed social media ban for young people, weighing the good it seeks against the privacy risks, enforcement problems, and unintended consequences it may create.

Finally, we consider Winston Peters’ proposal to buy BNZ, and whether it’s substantive policy or a well-timed headline grab.

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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We then turn to superannuation, following National’s campaign pledge to raise the age of eligibility. Can New Zealand afford to keep the pension age at 65 in the face of mounting fiscal and demographic pressure?

Finally, we unpack the NZ Herald–Motu Research Poll of Polls and consider whether coalition-level modelling offers a more realistic, if less dramatic, picture of the next election. With potential overhangs complicating the numbers, could the race still be closer than it appears?

We wrap the show with our favourite segment, Fantasy Beehive, where we rank MP performance using our highly advanced, completely proprietary technology.

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In this episode, we speak with MP Greg Fleming about his Modern Slavery Bill and the process of bringing it before the House. He outlines how the bill evolved from a narrow amendment into a broader attempt to address forced labour within global supply chains.

The conversation explores how modern slavery is defined and its connection to everyday consumption in New Zealand. It also examines whether measures like supply chain reporting can meaningfully reduce harm, or whether they risk falling short of their intent.

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