AI-Aided Digital Twins for Public Good: Designing the Symbiosis of Functionality, Governance and Accountability for Maximum Usefulness and Public Good, in this Digital Age
AI-Aided Digital Twins for Public Good
Designing the Symbiose of Functionality, Governance and Accountability for Maximum Usefulness and Public Good, this Digital Age
AI-Aided Digital Mirrors
Imagine a world where we can simulate an entire forest biotope — its terrain, trees, wildlife, soil, water cycles — in real time. A virtual mirror of the ecosystem, constantly updated with live trustworthy data. This is a digital twin: a dynamic, AI-aided near-replica of a real-world environment that can be used to monitor, predict, and improve how we interact with physical systems.
The concept of digital twins is not new. In the 1960’s it was for instance used during the Apollo missions to replicate spacecraft conditions on Earth in real time. It is also refered to in the David Gelernter’s 1992 book Mirror Worlds, which imagined digital models that to some relevant extent reflect reality. However, what is new is the rapid advancement in AI technologies that now allow us to create sophisticated digital twins of nearly anything, from coastlines and forests to entire cities and ecosystems.
Today, these systems are being deployed to tackle urgent environmental challenges. They can help us detect early signs of drought, model the effects of climate policies, and optimise green infrastructure. Taking this into account, what if we could simulate the air we breathe, not just outdoors, but indoors, where we spend over 90% of our time? What if buildings could learn from their own environments, predicting and preventing poor air quality before it harms our health?
That is the challenge the TwinAIR project is and has been addressing: to create, deploy and test digital twins to monitor, model, and improve indoor air quality in real time. Powered by advanced data analytics and artificial intelligence, TwinAIR aims to turn buildings into responsive environments, improving health, energy efficiency, and sustainability.
This is Environmental AI in action: using artificial intelligence to make sense of complex ecological systems, guide interventions, and support sustainability.
The Promise, and the Challenge
If designed and governed well, Environmental AI can serve the public good. It can improve resource management, support climate action, and help prevent environmental disasters. But the benefits are not automatic. As with all emerging technologies, outcomes depend on how systems are designed, who controls them, and what values are embedded within them from the outset.
Environmental AI is not just a technical matter — it is deeply political, ethical, and social. And while the technology may be innovative, our governance approaches are often lagging behind.
Why Governance Matters?
To unlock the potential of Environmental AI, we should build governance and accountability into these systems from the start - during the design, deployment, and post-deployment stages.
Without accountability by each of the stakeholders – and co-accountability by the combined cooperative of stakeholders –, before, during and after deployments of these capabilities, amongst others various (lack of) trust as well as other detrimental situations will arise, such as for instance:
- Opaque decision-making: Who decides what data is collected and how it is used?
- Data injustice: How do we prevent bias or misuse in automated decision-making?
- Transparency gaps: Being clear about what a digital twin is taking in, and what not (as it will not be able to mimic the real-world, but only selected elements thereof) and how to cater for related trust and trustworthiness?
These are not just functional and technical challenges. They are organisational, ethical, social, legal and operational. It calls for a dialogue about and co-creating the contextual symbioses of design principles that both cater for the functionals as well as non-functionals – what we call: ALL-functionals –, by design and therewith embedding oversight, ethics, and accountability directly into the functional and technological life cycles.
TwinAIR and the European Vision
The TwinAIR project aligns closely with the European Union’s strategic goals. It supports The European Green Deal by improving environmental health and reducing energy use in buildings. It strengthens Europe’s digital leadership by developing innovative tools for smart monitoring and AI. And it aligns with climate neutrality goals for 2050, ensuring that indoor environments are part of the sustainability conversation.
Importantly, TwinAIR is not just about technology — it is about people. By making indoor air quality understandable and actionable, the project empowers organisations, individuals, communities, and public authorities to make healthier, more sustainable choices.
Building the Digital Future Responsibly
As Europe navigates the dual transitions of digitalisation and decarbonisation, we must ensure that technological innovation is matched by robust governance. Digital twins and Environmental AI offer powerful tools to address complex environmental challenges, but their effectiveness depends on the governance framework we establish around them.
However, governance and accountability should not become barriers to innovation. Instead, they should be of fundamental importance for public trust, fairness, and long-term impact. If we want these technologies to serve the public good, they must be designed with care, deployed with transparency, and governed with integrity.