Jalandoni, a senior research fellow at the Center for Social and Cultural Research at Griffith University in Queensland, Australia, has faced many trials while undertaking archaeological work. She navigates crocodiles and limestone cliffs and traps sharks – in ways involving traditional canoes – among other sites around the Pacific.
Jalandoni, a former archaeologist, now utilizes advanced technologies instead of her trowel, which includes drones and imaging techniques for recording sites with the assistance of AI for making sense of all the data. This move was taken because traditional manual identification involves specialist knowledge and is costly and time-consuming.
Nayyar Zaidi, a senior lecturer in computer science at Deakin University in Victoria, Australia, and Celia Alicea-Jalandoni combined their expertise to leverage machine learning – a subset of AI – to automate image detection to aid rock art research.
Jalandoni’s research, conducted with the help of the region’s First Nations elders and a dataset of photos from Kakadu National Park in Australia’s Northern Territory, was published last August in the Journal of Archaeological Science. The findings revealed several insights.
Kakadu National Park, home to the greatest rock paintings, earns its distinction as a Unesco world heritage site. One of the few places on Earth with such artwork, it is renowned worldwide for its art and culture.
The artists make their works using various materials: iron-stained clays and ores mixed with water, tools fashioned out of human hair, reeds, feathers, and chewed sticks. The pigments are created by fusing these elements.
The Abercrombie Region’s rock art dates as far back as 20,000 years ago, classifying it among the oldest recorded artwork. Experts have investigated a meager portion of the paintings here, yet it remains renowned in art circles worldwide.
Jalandoni says:
“For First Nations people, rock art is an essential aspect of contemporary Indigenous cultures that connects them directly to ancestors and ancestral beings, cultural stories and landscapes,”
“Rock art is not just data, it is part of Indigenous heritage and contributes to Indigenous wellbeing.”
A rock art photo taken by Andrea Jalandoni is an example of artificial intelligence’s ability to extract figures.
AI can extract figures from a rock art photo, as demonstrated by Andrea Jalandoni’s picture.
The researchers tested a machine learning model to detect painted rock art images with a high accuracy rate of 89% among hundreds of photos. Their study suggested that this system could prove invaluable for analyzing large volumes of photographs from sites of cultural importance across the globe.
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Image detection is only the initial part of the process. Automating various phases of rock art research through advanced analysis is possible, resulting in faster discoveries. This is according to Jalandoni, who adds that the potential of using this technology is vast.
Trained systems are hoped to unlock deep knowledge of the past by classifying images, extracting motifs, and discovering relationships among elements. These abilities should enable people to understand stories and traditions from history better.
In the future, AI could be used for much more sophisticated tasks than currently; for instance, recognizing which artist created a particular piece of art or even skillfully restoring damaged works.
Rocking art, a form of ancient storytelling and creativity, is rapidly declining due to a lack of timely documentation and research. This makes time an essential factor for its survival, according to Jalandoni. Many sites remain unidentified and unrecorded, making preservation even more difficult.
This rare and fragile form of art and culture is in danger of becoming increasingly scarce due to climate change and its related effects, such as extreme weather events, natural disasters, urbanization, and bad management by humans.
According to Jannie Loubser, a specialist in rock art and cultural resource management archaeologist with Stratum Unlimited, AI technology can benefit conservation and preservation efforts. She believes AI tools have the potential to aid both the conservation and preservation of vital resources. Ves AI tools have the potential to aid both the conservation and preservation of vital resources.
“Ground truthing”—facing the work—will always be necessary for understanding a site. Despite this, trained systems help to monitor unseen changes in rock art conditions by providing useful surveillance.
Jalandoni agrees that nothing compares to the value of being onsite to study ancient artworks to interpret and recognize the narrative they depict. Although, she is excited at the potential benefits of combining digital and traditional approaches in her research and documentation of sites that are difficult to access.
AI, the most contemporary of tools, has a poetic resonance for Martin Puchner, author of Culture: The Story of Us, From Cave Art to K-Pop (2023), who uses it to uncover the mysteries of the past.
Puchner says:
“Even as we are moving into the future we are also discovering more about the past, sometimes through accidents when someone discovers the cave, but also, of course, through new technologies.”
The use of AI in art research represents a significant breakthrough in our ability to understand and appreciate the history of human creativity. Using technology to uncover new insights and enhance our understanding of ancient art, we can connect with the past in new and meaningful ways.
We expect to see even more exciting developments as AI continues evolving and becoming more sophisticated. By harnessing the power of machine learning and other cutting-edge technologies, we are opening up new possibilities for research and discovery and bringing us closer to the art and culture of our ancestors.
Source: The Art Newspaper – International art news and events
