COP27 in Sharm El Sheikh in 2022 would be remembered for the historic agreement . For the first time in the history of Climate Negotiations under UNFCCC countries officially agreed to establish a “loss and damage” fund for the developing countries . the fund is intended to  help poorer nations recover from the impacts of climate change, such as destroyed homes, flooded land or lost income from dried-out crops. 

Previously, developing countries  have only received money for reducing the emission of Green House Gases mitigation which helps these countries to move away from fossil fuels. There is another fund at global level called ‘ Adaptation Fund’, to prepare for the future impacts of climate change and to pursue climate resilient development. 

Now there is yet another fund that has been agreed -‘Loss and Damage Fund. The modalities to contribute to the fund and its disbursement to the developing countries is yet to be decided . How much fund is needed and when would be initial considerations along with the concrete definition of what is ‘ Loss’and what is ‘damage’.

The issue of loss and damage has been highly controversial. Richer nations have previously not wanted to agree to a new fund as they thought it would make them liable to cover all economic losses from climate change. Defining such losses and damages  and calculating the numbers would be challenging and complex jobs. Considering that adequate contributions have not been made even for earlier two funds, the third fund makes the situation chaotic.

AI could help not only assessing the ‘Big Data’ of losses from 147 developing countries based on the losses till date and making prediction of the future losses.   Limited work has been done even for the Adaptation fund . Cost of building barriers , flood and storms resistant buildings and infrastructure , adapting to climate friendly agricultural practices are some of the topics that would need assessment, predictions and aggregating the demand for the financial resources. 

Fixing the value of loss and damage sounds a long drawn process. Can AI help in expediting?