Russian Trade Union Has Trained Neural Network to Defend Workers’ Rights
The Federation of Trade Unions of the Sverdlovsk Region has trained AI for legal advocacy, aiming to strengthen workers’ positions in labor disputes.
Lawyers at the Federation of Trade Unions of the Sverdlovsk Region have completed specialized training on using artificial intelligence tools in legal practice. The training was delivered as a webinar, where instructors explained in detail how neural networks can help analyze court precedents, identify errors in contracts, and prepare legal claims.
Using neural networks in legal work allows teams to process large volumes of court rulings in a short time. Tasks that previously took days for a lawyer can now be completed much faster.
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Andrey Vetluzhskikh, chairman of the federation, said AI could be useful not only during document preparation, but also directly in the courtroom.
According to Vetluzhskikh, with proper configuration, neural networks could also help workers without legal training better understand their rights and defend them with trade union support. That, in turn, would free up lawyers’ time for more complex and individualized cases.
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The use of AI in the legal field is expanding well beyond Russia. Globally, neural networks are already being used to search for relevant case law, analyze contracts, and assess legal risks. Major legal platforms rely on machine learning to speed up legal research and reduce technical errors in documents.
A federation representative believes this experience can be adapted to trade union work. In the near term, the organization plans to discuss expanding the use of neural networks across other areas of its activity. Previously, it said it intends to develop its own legal AI system to advise workers as early as 2026.
