Artificial intelligence (AI) model training and data scraping are essential processes in the development of modern AI systems. AI model training involves using large datasets to teach machine learning algorithms to recognize patterns, make predictions, or generate new content. Data scraping refers to the automated extraction of information from websites or digital sources, often to assemble the vast datasets required for effective AI training.

As these practices become more widespread, questions about the legality of using third-party content—especially copyrighted works—have become increasingly important. In Thailand, the legal landscape for AI developers is shaped primarily by the Copyright Act, which presents unique challenges due to the absence of a fair-use exception. This article examines the copyright-related risks and legal uncertainties facing AI developers under Thailand’s current copyright law and practices, offering strategic guidance for navigating this complex environment.

Copyright Risks in AI Scraping and Training

Thailand’s Copyright Act does not provide a broad fair use or fair dealing exception, unlike some other jurisdictions, such as the United States. This absence has significant consequences for AI developers:

• No general defense for AI training: Any use of copyrighted material for AI model training is presumed to be infringing unless a specific, narrow statutory exception applies or explicit permission is obtained from the rights holder. There is no general legal basis for using copyrighted works in AI training without authorization.
• Increased rights clearance burden: Developers must identify and secure licenses for every copyrighted work included in their training datasets. Given the scale and diversity of data required for effective AI models, this process can be both impractical and costly.
• Legal ambiguity and litigation risk: The lack of clear statutory guidance or case law leaves developers in a legal gray area. There is no established precedent clarifying whether certain uses of copyrighted material for AI training might be tolerated or considered trivial. This uncertainty exposes developers to potential copyright infringement claims, which could result in injunctions, damages, or even criminal penalties.
• Chilling effect on innovation: The risk of liability and the complexity of compliance may discourage both local and foreign entities from developing or deploying AI technologies in Thailand. This could stifle innovation and limit the growth of the country’s AI sector.
• Complications in international collaboration: AI development often involves cross-border data sharing. Models trained using data in compliance with foreign laws may still be infringing under Thai law if deployed or commercialized in Thailand, complicating international partnerships and technology transfers.

Data Scraping and Copyright Infringement

Data scraping can itself constitute copyright infringement if it involves the reproduction or extraction of protected works without authorization. In Thailand, the lack of a fair use exception heightens this risk. Even the act of copying website content for the purpose of assembling training datasets may be actionable, regardless of whether the use is commercial or noncommercial. Developers must be aware that scraping publicly accessible content does not automatically make its use lawful under Thai copyright law.

Jurisdictional Factors and Model Transfer Considerations

Thai copyright law may apply to acts committed outside Thailand if the resulting AI models are deployed, commercialized, or otherwise made available within the country.In addition, AI models trained on data in compliance with foreign laws may still be infringing under Thai law if the training data included copyrighted works not cleared for use in Thailand. This creates additional due diligence requirements for international collaborations and technology transfers.

Recommendations for AI Developers

To mitigate copyright risks, AI developers operating in or targeting the Thai market should consider the following steps:

• Conduct comprehensive rights clearance: Identify and obtain licenses for all copyrighted works included in training datasets.
• Review data scraping practices: Avoid unauthorized reproduction or extraction of protected works; respect website terms of service and copyright notices.
• Implement robust record-keeping: Maintain documentation of rights clearance and compliance efforts.
• Monitor legal developments: Stay informed about changes in Thai copyright law and any emerging guidance related to AI and data use.
• Engage in risk assessments: Regularly evaluate legal risks associated with new datasets, model deployments, and international collaborations.

Outlook

Thailand is exploring possible regulatory reforms and policy initiatives to address challenges presented by AI and emerging technologies. Discussions include the potential for AI-specific regulations, consideration of copyright exceptions for technological uses, and possible updates to data protection laws. The direction and timing of these changes remain unclear, so stakeholders should stay informed and participate in public consultations as opportunities arise.

AI developers in Thailand face significant legal challenges due to the lack of a fair use exceptions in the Copyright Act. This increases the burden of rights clearance, heightens litigation risks, and creates uncertainty that can hinder innovation and international collaboration. Proactive copyright compliance and staying updated on legal developments are important for navigating these challenges and supporting responsible AI growth.

Although some countries, such as Singapore and Japan, have introduced text and data mining (TDM) exceptions for AI training, Thailand has not yet adopted similar measures. The industry continues to await legislative amendments or court decisions that will provide clearer guidance.

A version of this article appeared in Managing Intellectual Property.