PHILIPPINES Trends and Developments Contributed by: Katrina Doble, Danielle Francesca San Pedro and Edward King Chua, Villaraza & Angangco
this technology can redefine traditional artistic processes. The mainstream adoption of generative AI, how - ever, has as many detractors as proponents, even in the local creative industry. Animator Janina Malinis argues that AI undermines artists who spend years mastering their craft, allow - ing anyone to produce comparable results with minimal effort. Similarly, creative director Emil Mercado warns that AI’s efficiency could exac - erbate the exploitation in an already undervalued industry, where creative work is often uncredited or stolen. He highlights how AI enables clients to bypass hiring artists, cutting costs and eliminat - ing the need for in-house talent, further devalu - ing artistic professions. Filipino artists have expressed concerns about AI platforms scraping their original works to train machine-learning models without consent. Crit - ics argue that such practices dilute the value of human creativity and raise ethical concerns regarding the unauthorised use of copyrighted material. These issues highlight the need for clearer policies and regulations as generative AI continues to influence and transform the Philip - pine creative ecosystem. Controversies in the use of AI in the creative industries Despite its immense potential, generative AI has sparked significant controversy, particularly in relation to copyright protection. Generative AI models use techniques like Gen - erative Adversarial Networks (GANs) or Trans - former architectures to ensure outputs are not mere reproductions, but entirely new creations inspired by the input data. They rely on vast datasets – often composed of publicly available images, music, text and other creative works –
to “learn” and produce new content. For exam - ple, a language model like ChatGPT is trained on diverse textual data to understand grammar, context and nuances, while an image generator like DALL-E uses vast image-text pair datasets to understand visual elements and their descrip - tions. However, the inclusion of copyrighted material in these datasets has sparked disputes, particu - larly among artists and copyright holders who claim their works are being used without consent or compensation. Proponents of generative AI argue that AI train - ing qualifies as transformative because the process does not directly reproduce or exploit the original works but rather analyses them to generate entirely new outputs. This transforma - tive purpose, they contend, aligns with fair use principles as it serves to advance innovation and the development of creative tools. In addition, supporters emphasise that AI systems operate within a technological framework that extracts general patterns, rather than recreating exact copies of the works they analyse. On the other hand, critics argue that unauthor - ised scraping of copyrighted material under - mines the rights of creators. They point out that AI systems may inadvertently replicate stylistic elements, themes or recognisable portions of the original content, blurring the line between inspiration and infringement. Ethical concerns also arise when artists and creators – many of whom rely on the value of their intellectual prop - erty – are excluded from the process and offered no acknowledgment or compensation. These debates reflect a growing need for regula - tory clarity. While some jurisdictions are begin - ning to explore legal frameworks for AI training,
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