The recommendations
- Comprehensive demand analysis: understand demand for funding against available resources, and align the two for a fair and efficient process
- Expert driven assessment: ensure every application is evaluated by field specific experts
- Detailed feedback: give principal investigators thorough, constructive feedback rather than generic comments, recognising the time they invest in proposals, partnerships and budgets
- AI technology: use emerging AI based assessment tools to improve consistency and objectivity
- Timely communication: close the gap between the announcement of results and the release of feedback
- Support and mentorship: offer targeted mentoring and training, particularly to applicants who narrowly missed out
- Prioritise research funding: recognise its central role in national success and resilience
The reasoning
The recommendations come from the assessor’s side of the table. He has evaluated proposals for the Ministry of Business, Innovation and Employment and assessed for the Royal Society Te Apārangi, and has also led applications as a principal investigator. From both positions the same problems recur: success rates so low that strong proposals fail, panels without the specialist knowledge to judge them, and feedback too brief to help applicants improve.
The proposals are practical rather than structural. Better matching of reviewers, fuller and faster feedback, and mentoring for near misses would raise the quality of the next round at modest cost. The suggestion to use AI tools is framed around consistency, not replacing expert judgement.
Context
He addressed the recommendations to the Royal Society Te Apārangi, the Ministry of Business, Innovation and Employment and Callaghan Innovation, at a time when New Zealand’s science system was under review. They sit alongside his wider service in national research assessment and his membership of the AI reference group for the Prime Minister’s Chief Science Advisor.
Why feedback matters
Of the seven recommendations, the call for detailed feedback addresses the most widely felt frustration. Principal investigators invest weeks or months in proposals, building partnerships and budgets, and receive in return a decision with little explanation. Meaningful feedback turns an unsuccessful application into a learning opportunity and improves the next round of proposals, which benefits the funder as much as the applicant.