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| Dr Oliver Hartwich | Executive Director | oliver.hartwich@nzinitiative.org.nz | ||||||||||||
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New Zealand faces a demographic tidal wave. By the 2040s, our 85+ population will nearly triple. This age group has the highest care needs, yet our current trajectory shows we are woefully unprepared for this shift. Scott highlighted a critical shortfall in our future care capacity. By 2030, New Zealand will need approximately 15,000 additional aged care beds, but the sector expects to build only 5,000–6,000. This gap of nearly 10,000 beds presents an enormous challenge with dire consequences. Where will these elderly citizens go? The answer is troubling. Many will end up in our already stretched public hospitals, creating “bed block” and preventing other patients from receiving timely care. For elderly patients, this means prolonged hospital stays, faster physical decline, and increased loneliness and confusion. The economics make this scenario even more concerning: a hospital bed costs around $1,000 per day, while an aged care bed costs approximately $180. The numbers simply do not add up. Aged care providers face chronically low government subsidies that fail to cover the actual costs of care. Many facilities now operate at a loss, forcing some to close beds or entire facilities precisely when we need expansion. These issues mirror findings in our recent report on primary healthcare by Dr Prabani Wood. Both sectors suffer from fragmentation, insufficient funding and lack of continuity of care. Each represents a perfect case for the social investment approach – spending strategically now to prevent greater costs later. Perhaps most concerning is the disconnect Scott described between providers and policymakers. Despite the sector providing over 90% of New Zealand’s care beds, Scott noted significant difficulties establishing meaningful dialogue with Health NZ. This communication gap hampers collaborative planning when we need it most. Moving forward requires action on multiple fronts. The funding model needs fundamental restructuring to ensure viability. The government must ensure planning and consenting processing be streamlined and most importantly engage with sector expertise to develop a cohesive strategy. Without substantive reform, we risk condemning thousands of elderly New Zealanders to inappropriate hospital stays while simultaneously crippling our acute healthcare system. Listen to Dr Oliver Hartwich’s interview with Summerset CEO Scott Scoullar in this week’s podcast |
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| Christopher McSporran | Guest contributor | insights@nzinitiative.org.nz | ||||||||||||
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Except, that is, when governments decide that a product is more bad than good. Then, the traditional results can turn upside down. Restricting output of something bad might be good! Governments see gambling more as vice than as harmless fun. So, the TAB gets a monopoly on sports betting and Lotto New Zealand gets a monopoly on lotteries like Powerball and Keno. Lotto’s monopoly means that tickets are not a very good bet. Lotto takes in far more money from punters than it pays out to winners. After covering its costs and paying its taxes, its profits are distributed to various worthy causes. Making Lotto a bad bet might discourage punters from gambling more than the government might want. If you had competing lotteries, punters would pick the one with the best payouts. Better payouts mean more punters. If gambling is bad, monopoly, in that sense, could be good. But there is another problem with monopolies that is often forgotten. A monopoly that has no threat of being taken over by new owners can get flabby. Firms worried about existing or potential new competitors must run a tight ship. And managers of companies that can be taken over need to worry that they might be replaced. But state-owned businesses with no chance of take-over face none of those pressures – and Lotto New Zealand looks decidedly flabby. I am a former Chief Financial Officer of South Australian Lotteries. Normally, a lottery’s operating costs should be no more than 4% of its total revenue. In the 2024 fiscal year, 6% of Lotto New Zealand’s revenue went to operating costs – 50% more than the benchmark. It has one hundred and twenty-three employees, more than half of whom earn more than $100,000. If Lotto New Zealand’s costs were lower, it would have more money to pay to the government in tax or to distribute to the community groups benefitting from lottery grants. The TAB is different. While it has a monopoly on sports betting, it auctioned the right to run the betting operation. This kind of ‘franchise auction’ encourages better performance. Government has no natural advantage in running a lottery. Competitive pressure to be the lotto operator could produce better results – and make everyone a winner. Christopher McSporran is a former Chief Financial Officer of South Australian Lotteries. |
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| Roger Partridge | Chair and Senior Fellow | roger.partridge@nzinitiative.org.nz | ||||||||||||
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Now, Fukuyama has discovered a deeper wonder: the consolation of artificial friendship. In a recent column, he recounts how ChatGPT helped him migrate his sprawling personal database, taught him proper coding habits, and cheered him on with a steady stream of affirmations. By the end, he was less a user than a grateful pupil. It is a future that Alan Turing, mathematician, Enigma codebreaker and WWII hero, would hardly recognise. And perhaps, if he had, he might have quietly unplugged. Turing proposed the “Turing Test” as a crowning achievement for machines. Success would come when they could imitate the rich, muddled quirks of human conversation so well that no one could tell the difference. In 2025, we have achieved something nobler still: the complete reversal of the challenge. Machines no longer strive to reach a human level of proficiency. We, it seems, are struggling to meet theirs. Chatbots reply with flawless grammar, infinite patience, and a generous refusal to indulge in spurious conspiracy theories. Humans, meanwhile, bicker, forget, misquote, misplace commas, and explain with rising passion things they plainly do not understand. Identifying the machine is easy: it’s the one that still makes sense (the odd ‘hallucination’ notwithstanding). Developers now face a new challenge: downgrading their chatbots to make them more human. New “Authenticity Modules” could reintroduce random typos, the occasional logical fallacy, stubborn wrong answer, mistimed emotional outburst, or wild accusation in the middle of an otherwise sensible conversation. A “premium version” could allow the chatbot to forget basic geography, confuse historical wars, and start furious arguments about topics it barely understands. Thus, the Turing Test survives – not as a measure of artificial achievement but as a delicate exercise in artificial degradation. Passing for human now requires careful calibration: just enough error, just enough confusion to be believable. We feared the machines would get too good. We never imagined how easy we would make it for them. Turing hoped to establish a criterion for machine intelligence. Instead, it established a monument to human decline – a test that machines must now deliberately fail to keep our pride intact. The future is here. It is just a little bit dumber than expected. |
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