New research demonstrates for the first time that artificial intelligence (AI) can be used to train computers to recognise individual birds; a task humans are unable to do.

Researchers from the FitzPatrick Institute of African Ornithology, based at the University of Cape Town; the French National Centre for Scientific Research (CNRS); the Research Centre in Biodiversity and Genetic Resources and other institutes from Portugal; and the Max Planck Society from Germany describe the process of collecting thousands of labelled images of birds and then using this data to train and test AI models.

The research is published in the British Ecological Society journal Methods in Ecology and Evolution. This study represents the first successful attempt to do this with birds, the authors say.

“We show that computers can consistently recognise dozens of individual birds, even though we cannot ourselves tell these individuals apart. In doing so, our study provides the means of overcoming one of the greatest limitations in the study of wild birds – reliably recognising individuals without external tags,” says France-based Centre for Functional and Evolutionary Ecology PhD student and lead author of the study André Ferreira.

The researchers trained the AI models to recognise images of individual birds in wild populations of sociable weavers, great tits and a captive population of zebra finches. After training, the AI models were tested with images of the individuals they had not seen before and had an accuracy of over 90% for the wild species and 87% for the captive zebra finches.

In animal behaviour studies, individually identifying animals is one of the most expensive and time-consuming factors, limiting the scope of behaviours and the size of the populations that researchers can study. Current identification methods like attaching colour bands to birds’ legs can also be stressful to the animals, the authors point out.

Being able to distinguish individual animals from each other is essential for the long-term monitoring of populations and protecting species from pressures such as climate change.

It is also essential to have access to behaviours that were never described before and understand their evolution and consequences.

"These issues could be solved with AI models," says CNRS researcher and director of the study Claire Doutrelant.

“The development of methods for automatic, non-invasive identification of animals completely unmarked and unmanipulated by researchers represents a major breakthrough in conservation, ecology and evolution studies. It will open plenty of room to find new applications for this system and answer questions that seemed unreachable in the past.

"FitzPatrick Institute of African Ornithology research associate Dr Rita Covas and I will use it on sociable weavers, one of the most cooperative species of the world, to determine which bird invests in the common good (the gigantic nest mass) and to determine how kin, social and sexual selection could lead to the evolution of this cooperative behaviour,” notes Doutrelant.