All eyes on Rocket Lab’s next lift-off

educating [frontline staff], showing them these models can help them, and aren’t going to replace them.

‘‘Once they understand the models can help them achieve their performance indicators, they start to use them and like them. In turn, that helps the models improve.

‘‘So it’s a feedback loop. We were starting to see that at the time I left.’’

MSD is widely regarded as leading the public sector in its use of these technologies. ‘‘I get the feeling we were leading, and MSD still is,’’ Nik says. ‘‘But the gap is closing, quickly, which is a good thing.’’

At the end of the day, he says, these models are just serving up recommendations. He finds the current hype about them rather bemusing.

‘‘The use of data has always been there. Maybe at a different level, but it’s always been there and people have always used it to make decisions.’’

Quoting AI boffin Andrew Ng, he adds: ‘‘Worrying about machines taking over the world is like worrying about overpopulation on Mars.’’

Almost all participating agencies use operational algorithms to inform human decisionmaking, rather than to automate significant decisions, the stocktake found. ‘‘Humans, rather than computers, review and decide on almost all significant decisions made by government agencies.’’

While these tools are helping agencies deliver better and more efficient services, ‘‘there’s plenty of scope to lift our game’’, MacPherson says. ‘‘New Zealand has robust systems and principles in place around the safe use of data, but as techniques become more sophisticated we must remember to keep the focus on people and make sure the things we are doing are for their benefit.’’

The report’s recommendations include maintaining human oversight, involving those who will be affected, promoting transparency and awareness, regularly reviewing algorithms that inform significant decisions, and monitoring adverse effects.

‘‘Even the best algorithms can perpetuate historic inequality if biases in data are not understood and accounted for,’’ the stocktake said. Yet, it continued: ‘‘Few agencies reported any regular review process for existing algorithms to ensure they are achieving their intended aims without unintended or adverse effects.’’

When asked about this, MacPherson says that, while few agencies ‘‘explicitly referenced a review process for algorithms, there are a range of different safeguards and assurance processes that they did specify’’. Those include getting advice from experts, or employing a dedicated data steward.

T he report found agencies could also benefit from a fresh perspective by looking beyond government for privacy, ethics, and data expertise. This could be achieved by bringing together a group of independent experts that agencies could consult for advice and guidance.

No decisions have been made about how the Government will respond to the report’s recommendations, MacPherson says.

Evelyn Wareham, chief data and insights officer at the Ministry of Business, Innovation and Employment, says as one of the government’s largest and most complex policy and operational agencies, it relies on good-quality evidence to inform decisions.

‘‘The data received by algorithms provides insights on a wide variety of operational and policy decisions.’’ ‘‘Activity’’ is under way to ensure ‘‘transparency, accountability and best practice for algorithm use across MBIE’’, she says.

Paul James, government chief digital officer and chief executive of the Department of Internal Affairs, says the Government is working with ‘‘communities, interest groups, business and other nations to ensure we are developing and making best use of tools to benefit New Zealanders’’.

‘‘Take-up of technologies is relatively advanced in New Zealand, but AI applications are still emerging.’’