Environmental Intelligence
Overview
This theme’s case study research is driven by the need to improve access to, and comprehension of, different kinds of complex, time-varying environmental data, for example:
- outputs from climate, weather and ocean model ensembles and empirical observations;
- high-volume geospatial, ecological, satellite and remote sensing data;
- socioeconomic data on resource flows, supply chains, energy consumption and carbon emissions, and
- online media including news media and cross-platform social media content.
Many decision-makers (including citizens and policy-makers) would benefit from better environmental information. A huge volume of this data is now available, but it often requires a high level of expertise to obtain it and interpret the associated uncertainties.
Large language models are increasingly suggested as a potential solution to part of this problem. Meanwhile, public debate is weakened by the profusion of poor quality or deliberately false information, especially concerning the contested issue of climate change.
Case study
This theme’s case studies work towards AI tools that overcome these challenges by democratising access to good quality information about environmental change. Novel “climate avatar” agents act as simple interfaces between complex environmental data and the people who need it in order to improve their decision-making. They ingest weather and climate data from existing large datasets, peer-reviewed climate science literature and other trusted sources (for example, IPCC reports), and expose this data via natural-language interfaces that allow users to access information and gain understanding in a conversational style.
By summarising scientific literature and generating on-the-fly visualisations from raw data, climate avatars enable lay users to make sense of complex climate data and uncertainties, tailored to their specific context (for example,, where they live or the sector in which they work).
Similar smart agents engage with other environmental data sources, such as geospatial data, satellite imagery and ecological data. Once created, validated and trusted, these avatars can be deployed to interact with human users in different contexts, for example:
- allowing expert and non-expert academics to interrogate complex federated models of natural and human capital
- enabling chatbots to explain extreme weather events and provide warnings/guidance
- providing timely responses to policy formulation queries
- defusing toxic discourse on social media
Data ethics, governance and usability challenges must be addressed in order to ensure that agents are explainable, trustworthy, and able to effectively influence public understanding in order to achieve positive social outcomes.