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AI

UAE National Library and Archives Calls for Ethical AI Frameworks as Conference Closes

The archive showed in-house visual search tools it says identify people, buildings, vehicles and landmarks within seconds, and a paper examined storing data in DNA.

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The National Library and Archives held its conference on large language models in the public sector with Sorbonne University Abu Dhabi.
The National Library and Archives held its conference on large language models in the public sector with Sorbonne University Abu Dhabi.Photo: وكالة أنباء الإمارات / Handout

The UAE's National Library and Archives closed a three-day conference on large language models in government with a call from its acting executive director, Dr Hamad Abdullah Al Mutairi, for ethical frameworks to keep AI tools reliable and sustainable, the Emirates News Agency (WAM) reported on Sunday. Details were first published by wam.ae.

Al Mutairi, who is also vice-president for programmes at the International Council on Archives, said large language models represent a step change for government work and the production of knowledge. He pointed to uses in writing, translation and knowledge management. The conference, titled Application of Large Language Models in the Public Sector, was organised with Sorbonne University Abu Dhabi.

He said the technology strengthens the archive's role, which reaches beyond preserving historical documents to producing knowledge, consolidating national identity and giving the public access to authentic, reliable information.

Experts and academics at the conference discussed the use of AI in service efficiency, ethical governance and sustainability. Mohammed Adel Al Ash of the National Library and Archives presented in-house systems for automating archival work, analysing data and supporting decisions. They include text extraction tools, a smart platform called Al Thakira, Arabic for memory, and visual search systems that the archive says can identify people, buildings, vehicles and landmarks within seconds.

Rachid Al Tayeb Hamdache, also of the archive, looked further ahead in a paper titled Artificial Intelligence and the Future of Genetic Archiving. He examined storing large volumes of data for long periods in very small spaces using DNA molecules, and said AI could improve the accuracy of encoding and retrieving such data and cut energy use. Cost, retrieval speed and technical complexity remain obstacles, he said.

A second session covered the role of language models in preserving cultural heritage and the archive's work to safeguard cultural memory and open its sources to researchers and the public.

The report did not say which models the archive's tools run on or what governance rules apply to them. Al Mutairi said he hoped to continue working with the university through an International Conference on Digital Archives scheduled for January 2027.

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