ABSI - AI Debate on Copyright Infringement Heating Up

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Time flies when you’re having fun. It’s been two years now since the initial release of OpenAI’s ChatGPT large language model that went viral and opened up the possibility of AI to the mainstream. While the technology has been a game changer for the productivity of many, it has not come without its criticisms. Specifically, the training of AI models on copyrighted material scraped from the internet. This issue will now test the legal system with a joint lawsuit filed in Canada against OpenAI for copyright infringement. ABSI this week will cover the issue and what it may mean for AI moving forward. 

Artificial intelligence (AI) is a fairly broad term in today’s society but it generally refers to software capable of performing tasks usually completed by human intelligence. In simple terms, an AI model can be trained by feeding lots of examples from real-world data—like text, images, or videos—so they can learn patterns and relationships. Think of it like teaching a child: you show them many pictures of cats and dogs, and over time, they learn to tell them apart. The data comes from various sources like websites, books, or publicly shared information. It’s cleaned and organised so the AI can learn effectively. Once trained, the model can use what it learned to answer questions or solve problems.

Estimated training cost of large models   

Source: Stanford

One issue that has plagued AI software since its viral rise has been the issue of copyright. Copyright issues can arise when training AI models, especially if copyrighted material is used without proper permissions. If this data is used without authorisation or outside the bounds of "fair use" (which varies by country), it could infringe on the rights of the original creators.

Unsurprisingly, debates have ensued about whether using copyrighted material for training is allowed, particularly when the AI’s outputs compete with or replicate the original works. Some argue that using such data for "training" is transformative and falls under fair use, while others contend it devalues the original content. To address these concerns, AI companies increasingly seek licenses, use public domain data, or allow creators to opt in or out of having their works included. A well-known licensing example is OpenAI's agreement with Shutterstock signed in 2023, which provided access to its library of images, videos, and music for training AI models. This deal ensured that Shutterstock's content contributors were compensated for the use of their work, addressing potential copyright concerns.

However, not all sources are being compensated, and arguably it isn’t feasible, which has resulted in a joint copyright lawsuit, from Canadian journalists, being filed last Friday in the Ontario Superior Court of Justice. The plaintiffs are seeking billions of dollars in damages, C$20,000 for each article illegally scraped, and are also seeking a share of OpenAI’s future profits. This follows on from a similar lawsuit filed by the New York Times in 2023 which is still in discovery. 

Uptick in AI Controvery

Source: Stanford

The issue with these lawsuits are that they’re technically very difficult to prove. Additionally, there is the argument of “fair use”. AI is a transformative use of data, it doesn’t replicate the original work but learns patterns, structures, and relationships to generate new outputs. This is akin to how humans learn by reading copyrighted material to create original content. 

The issue of AI model training on copyright data is a complicated issue that will not be solved anytime soon. Both sides hold valid arguments but I do feel that content creators do need some sort of compensation. Devaluing human content can ultimately result in a world dominated by AI-created content which may be homogenous, biased, and devoid of unique perspective.


 

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