Copyright challenges in AI model training under Thailand’s legal framework

Thai copyright law poses significant hurdles for AI developers because it lacks broad fair-use provisions, a common feature in other major jurisdictions. Without statutory exceptions for data mining or text analysis, using copyrighted materials to train models is presumed infringing unless explicit permission is granted. This absence of legal clarity forces developers to navigate a complex landscape where even publicly available data scraped for training purposes may violate the law, creating substantial uncertainty regarding liability and compliance. The practical implications of this regulatory gap include heightened licensing burdens and increased risks of litigation. Developers must individually secure rights for vast datasets, which is financially and operationally demanding. Furthermore, the lack of established precedent leaves companies vulnerable to infringement claims, potentially stifling local innovation and complicating international collaborations. Models trained abroad may still face legal challenges in Thailand if they utilize unlicensed content, highlighting the strict territorial reach of these copyright protections and the difficulty of managing cross-border data flows. This article is relevant to open data advocates as it illustrates the critical tension between the openness required for robust AI development and restrictive intellectual property regimes. It underscores the urgent need for legal frameworks that distinguish between unauthorized commercial exploitation and permissible technological research. By highlighting the absence of data mining exceptions, the piece argues for policy reforms that would allow open data to fuel innovation without exposing developers to undue legal risk, ensuring that the benefits of AI can be realized within a legally sustainable environment.

Source: managingip.com
Published on 2025-08-30

Copyright challenges in AI model training under Thailand’s legal framework

Related news