Dragon Age writer condemns generative AI as virulent plague

David Gaider, co-creator of the Dragon Age series, has strongly criticized the use of generative AI in game development. He described the technology as a “virulent plague” during an interview with GamesRadar. Gaider highlighted concerns over plagiarism, efficiency, and training for new developers.

Gaider, who served as lead writer on Dragon Age: Origins, Dragon Age II and Dragon Age: Inquisition, spoke out against generative AI in comments published by the site. He pointed to its training on data without creator consent as a source of legal and moral problems.

The writer questioned whether the technology improves efficiency or quality. He stated that editing inferior AI-generated work often takes more time than starting over, based on his experience as a narrative designer.

Gaider also warned that AI could hinder junior developer training by removing entry-level tasks. He argued that the technology performs poorly at iteration and that teams should avoid relying on it until proper regulations and legal data sourcing are ensured.

관련 기사

Illustration of PR staff stopping AI question at Tomb Raider event
AI에 의해 생성된 이미지

Crystal Dynamics PR halts Tomb Raider AI question

AI에 의해 보고됨 AI에 의해 생성된 이미지

A video from Game Informer captured an awkward moment at Summer Game Fest where Crystal Dynamics public relations staff stopped a follow-up question about generative AI use in Tomb Raider: Legacy of Atlantis.

Dr Luke Dicken, the former head of AI at Take-Two, has said that excessive hype around generative AI risks turning people against all forms of artificial intelligence in game development.

AI에 의해 보고됨

Joris De Man, composer for Horizon Forbidden West, has voiced strong concerns over generative AI in creative work.

Workers paid to train advanced AI models are increasingly relying on chatbots like ChatGPT to generate the required conversations and tests. This shortcut, described as widespread by multiple sources, risks degrading the quality of future models through recursive training on synthetic data.

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