Data Science Lead Alvaro Orsi introduces ESR's groundbreaking 'digital twin' platform, offering advanced simulations of New Zealand’s health, environment, and climate within a dynamic 3D interactive model.
Imagine a world where we could foresee the path of a new virus before it struck, mapping its spread through a community with precision. Or a future where we could predict the ripple effects of rising sea levels on coastal towns, preparing people for challenges before they arrive. This isn’t the realm of science fiction—it’s a glimpse into the groundbreaking work being done at the Institute of Environmental Science and Research (ESR).
ESR's digital twin platform seeks to revolutionise evidence-based decision-making through the power of artificial intelligence. This remarkable platform brings together an orchestra of cutting-edge AI capabilities to offer unprecedented insights into our society's most complex challenges.
The power of a synthetic population
At the heart of the platform beats a sophisticated synthetic population—a dynamic 'digital twin' of Aotearoa's demographic landscape. Unlike conventional static datasets, the platform's virtual citizens come alive with rich life diaries and realistic behaviours, powered by advanced generative AI. These synthetic agents move, interact, and are influenced by their environment just as real people do, whilst ensuring absolute privacy and confidentiality.
This synthetic population approach offers significant advantages for data sovereignty and privacy protection. By using artificially generated agents based on aggregated census data and socioeconomic patterns, it eliminates the need to handle sensitive personal information while maintaining statistical accuracy.
The synthetic population preserves the rich demographic tapestry and behavioural patterns of Aotearoa's communities without compromising individual privacy.
Advanced AI integration
What truly sets ESR's digital twin apart is its integration of multiple AI technologies. Through groundbreaking Large Population Models, developed in collaboration with MIT Media Lab, it can simulate millions of individual agents simultaneously, capturing the intricate dance of human interaction at an unprecedented scale.
The platform's sophisticated time series modelling has the potential to forecast and simulate different ‘what-if’ scenarios, whilst its causal inference algorithms uncover the hidden drivers behind social outcomes.
When combined with powerful optimisation techniques, the platform doesn't just analyse—it seeks to provide actionable insights for decision making. Think of it as laboratory for testing policy impact, social innovation, and for navigating complex societal challenges.
But how could the digital twin be utilised? Here, we delve into just a few of its exciting potential applications.
Transformative applications
The platform offers a range of capabilities that enable public sector organisations to enhance their decision-making processes and improve service delivery outcomes. The platform's sophisticated modelling capabilities have the potential to support several key areas where evidence-based insights are crucial for effective policy development:
Social development and welfare
Through sophisticated modelling capabilities, the digital twin provides policymakers with precise insights into how support programmes impact different demographic groups. The platform could eventually be used to evaluate social mobility patterns and wellbeing outcomes, enabling evidence-based decisions about early intervention strategies.
This systematic approach has exciting possibilities for testing of policy scenarios before implementation.
Health system planning
The platform has opportunities to deliver advanced simulation capabilities for public health scenarios, from disease outbreak modelling to preventive programme evaluation. A practical demonstration of this capability is already evident in its application to model potential measles outbreak responses across New Zealand, helping health authorities prepare effective intervention strategies.
Economic policy
In the economic sphere, it could offer sophisticated analysis of policy impacts across diverse population segments. The platform's dynamic modelling capabilities have the capacity to illuminate how different economic interventions affect labour markets and business resilience, with the promise of crucial insights for policy development.
Climate change resilience
The platform has the power to model urban environment responses to climate-related challenges. For example, simulating population behaviour and adaptation during extreme weather events and natural disasters, while also projecting long-term impacts of climate change on public health and socioeconomic wellbeing. This capability could help urban planners and councils develop robust resilience strategies and targeted intervention programmes.
Advancing policy development
The digital twin also has the potential to transform traditional policy development by creating a sophisticated digital testing environment. This innovative approach could enable policymakers to make informed, data-driven decisions, optimise resource allocation, and test interventions comprehensively before real-world implementation. The platform's ability to make complex social dynamics comprehensible represents a significant advancement in evidence-based decision-making.
Looking forward
The evolution of ESR's digital twin continues to expand its potential applications. By combining privacy-preserving synthetic population modelling with sophisticated AI capabilities, the platform has the extraordinary potential to offer deeper insights into population dynamics and consumer behaviour. It could one day support policy interventions that are effective and equitable, providing a robust framework for responding to complex challenges and market shifts in shaping New Zealand's future.
To demonstrate these capabilities, ESR has released a platform demo version that showcases the digital twin's potential. While not implemented for a specific use case, this demo serves as an interactive showcase of its capabilities, designed to spark innovation and ideas about potential applications.
ALMA is built on top of research in Large Population Models and AgentTorch developed at MIT.
