Using machine learning to close the vocabulary gap in the context of environment and climate change in Chichewa (LVL 4)
Case Study: Machine Learning has a role to play in closing the ‘vocabulary gap’ of terms and concepts regarding the environment and climate change that exists in Chichewa and other Malawian languages. They aim to create a visual dictionary of key terms used to describe the environment and explain the issues involved in climate change […]
Case Study: Increased demand for water to irrigate crops alongside reduced rainfall and land degradation in the catchment area have led to water shortage and conflict between the users of a river’s water. To ensure equitable distribution of this resource effective monitoring of the river is essential. They plan to incorporate multiple data sources such […]
Future interactive website to show precise and personalised impacts of climate change using AI and climate modelling. Bringing together researchers from different fields, the website aims to act as an educational tool that will produce accurate and vivid presentations of future climate change outcomes as they are likely to affect individuals.
Case Study: Explores the potential of using images from a simulated 3D environment to improve a domain adaptation task carried out by the MUNIT architecture, aiming to use the resulting images to raise awareness of the potential future impacts of climate change. The case study aims to develop an interactive website that, given a user-entered […]
Case Study: Community-level perspective of the game-changing socio-economic value that could be achieved with better forecasts, especially among vulnerable communities. The paper presents a new way to view this opportunity by better understanding the problem, with the goal of inspiring the Climate Change AI community to contribute to this important aspect of the climate adaptation […]
Case Study: Most of Rwanda’s crop production comes from smallholder farms. The country’s agriculture officials have historically had insufficient data on where crops are cultivated or how much yield to expect — a hindrance for government’s future planning. Building on previous work with emerging technologies, machine learning, economics, and agriculture, the paper develops a new […]
Case Study: pioneering flood mapping and response organization that uses high-cadence, high-resolution satellite imagery to build country-wide flood monitoring and dynamic analytics systems for the most vulnerable around the world.
The paper provides pillars of action for the AI community, and includes a focus on climate justice where the author recommends that environmental impacts should not be externalised onto the most marginalised populations, and that the gains are not only captured by digitally mature countries in the global north. This will require centring front-line communities […]
Forced labour exploiters continually tweak and refine their own practices of exploitation, in response to changing policies and practices of inspections.The article showcases efforts to create AI tools that predict changing patterns of human exploitation. The authors acknowledge that whilst there are obvious benefits that accurate forecasting tools could bring, there are cases where these […]
The article raises the challenge of defining fairness when building databases. For example, should the data be representative of the world as it is, or of a world that many would aspire to? Should an AI tool used to assess the likelihood that the person will assimilate well into the work environment? Who should decide […]