Trade Union Congress Collaborates to Draft AI Regulation and Employment Bill

Artificial intelligence (AI) is a rapidly evolving technology that is increasingly being integrated into various aspects of our lives, including the workplace. In response to the growing use of AI systems by employers, the Trade Union Congress (TUC) has taken a proactive step by collaborating with the AI Law Consultancy at Cloisters Chambers and the Cambridge University Minderoo Centre for Technology and Democracy to draft the Artificial Intelligence (Regulation and Employment) Bill.

The Bill, spearheaded by Robin Allen KC and Dee Masters of the AI Law Consultancy at Cloisters Chambers, aims to regulate the use of AI systems in the workplace to protect the rights and interests of workers, employees, and jobseekers. It also seeks to uphold trade union rights in the context of AI deployment by employers, address risks associated with the value chain of AI systems, and promote the development of safe, secure, and fair AI systems within employment settings.

The collaborative effort involved a Special Advisory Committee comprising representatives from various organizations and political parties, including the Ada Lovelace Institute, the Alan Turing Institute, and TechUK, among others. The policy outlined in the Bill reflects the stance of the TUC and is distinct from the positions of the organizations represented on the committee.

Divided into thirteen parts with complementary schedules and explanatory notes, the AI Bill covers a wide range of topics related to AI and employment. Part 1 serves as an introduction to the Bill’s structure, while Part 2 delves into core concepts such as ‘artificial intelligence system,’ ‘high-risk decision-making,’ ‘data,’ and ’emotion recognition technology,’ among others.

By establishing enforceable rights and obligations in the Employment Tribunal, the Bill aims to provide a mechanism for addressing AI-related disputes in the workplace. This jurisdiction, known for its ‘no cost’ nature, ensures that parties are accountable for their own costs regardless of the case outcome.


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