The future of intellectual property in the era of AI

April 26, 2023

The role of IP in promoting innovation

April 26th marks the World Intellectual Property Day, a day dedicated to recognizing the crucial role that intellectual property (IP) plays in fostering innovation by providing support and incentives to creators worldwide. The progress of our society is largely determined by our ability to generate new ideas and introduce groundbreaking inventions to the market. However, with the rapid rise of artificial intelligence (AI) systems, especially Generative AI, a new wave of opportunities and challenges has emerged.

Generative AI has brought about transformative changes, with text generators like Chat GPT capable of producing essays, poems, and even passing complex medical and legal exams faster than humans. These systems can also create astonishing artwork within seconds, often imitating renowned artists and their styles with remarkable precision, surpassing the quality and speed of human counterparts. 

How do generative AI systems do it?

In order to train systems like Chat GPT, vast amounts of data including texts, images, and parameters, are required. During the training process, AI platforms identify patterns to create rules, make judgments, and predictions which then allow them to respond to user prompts. However, this training process may involve intellectual property infringement as it often uses data scraped from the web, including potentially copyrighted content.

Recent lawsuits, such as those initiated by Getty Images and a group of artists against AI art generators, have highlighted the IP issues associated with AI. Getty Images has accused Stability AI of copying over 12 million images from its database without permission or compensation, including distorted versions of the Getty watermark, potentially leading to trademark infringement claims.

However, the open questions regarding IP in the context of AI extend beyond protected data and images used in training, but also to the creative outputs generated by AI platforms. Questions such as copyright, patent, and trademark infringement in relation to AI creations, as well as ownership of AI-generated content, need to be addressed as individuals and businesses continue to embrace the benefits of generative AI.

The key issue with copyright is that it requires originality, which is often attributed to human authors. Without human involvement in the creative process of AI-generated works, copyright protection may not be possible.  In 2019, the Beijing court in China held that human production or creation is a prerequisite for copyright protection, which may exclude AI software as an author. More recently, the German artist who won the prestigious Sony World Photography Awards refused to accept the award, revealing the photo was in fact generated by AI. 

As AI does not have legal personhood, it is currently not recognized as a holder of any (intellectual property) rights. If no inventor or creator can be identified, the work may, in principle, fall into the public domain, which raises the question of whether there could be alternative solutions to protect AI-generated works under copyright law. 

Is artificial intelligence (AI) all that problematic?

On March 2, 2022, the European Union Intellectual Property Office (EUIPO) released a “Study on the Impact of Artificial Intelligence on the Infringement and Enforcement of Copyright and Designs”. The authors of the study believe that emerging technologies, such as AI and machine learning, represent a “double-edged sword,” and can be used effectively to enforce as well as to infringe on IP rights.  

For example, machine learning tools can be deployed to remove the digital dots and watermarks used to track the distribution of unauthorized copies of copyright works online, as well as to generate “deep fakes”—developed through a specific type of machine learning, known as “generative adversarial networks”. 

On the other hand, authorities can harness that same technology in a positive way. Once the deep fakes have been identified, the authorities can use AI bots to identify on social media those components of the deep fake that constitute copyright and design infringement. Similarly, computer vision applications can be implemented in the field of IP. For instance, computer vision applications can determine if videos are original or artificially generated.

Moving Forward

Effectively addressing these intellectual property issues requires a collective effort from all stakeholders, including policy makers, service providers, developers, content creators, and business owners. 

AI developers must make sure they comply with laws related to the acquisition of data used for training their models. This could include obtaining licenses for or compensating those who own the intellectual property being used, or sharing revenue generated by the AI tool.

On the other hand, customers of AI tools should also be cautious and ask questions about the source of the training data, carefully review the terms of service and privacy policies, and avoid using AI tools that cannot confirm proper licensing from content creators or adherence to open-source licenses. 

It is also important for businesses to give their employees basic training on how to use new AI tools without violating their privacy and trade secrets.  In a recent incident, Samsung employees accidentally leaked company secret data (trade secret) by including a source code in its prompt. As ChatGPT retains the data for training purposes, these trade secrets from Samsung are now in the hands of Open AI.

While we embrace these innovations, it is important to learn how to use them responsibly in order to safeguard our sensitive data as well as to recognize the rights of those who have contributed to the creation of AI, as they may be impacted by its use. As AI is becoming increasingly integrated into our lives, it is crucial to find a balance between its development and adoption, and IP rights. Below is what Chat GPT thinks about the issue:

“The relationship between artificial intelligence (AI) and intellectual property (IP) can be complex, but there are a few ways to balance the two:

  • Protecting AI with IP: Just like any other invention, AI can be protected by intellectual property rights such as patents, copyrights, and trade secrets. This can encourage innovation and investment in AI research and development.
  • Addressing ownership and licensing: When AI is developed by a team or in collaboration with others, ownership and licensing agreements need to be established. This can ensure that the creators and contributors receive appropriate credit and compensation for their work.
  • Managing data and privacy: AI often relies on large amounts of data, which can include sensitive personal information. It’s important to manage this data responsibly and protect privacy, while also allowing for innovation and development of AI.
  • Considering ethical implications: AI can have significant social and ethical implications, such as bias, discrimination, and automation of jobs. It’s important to consider these implications and ensure that AI is developed and used in an ethical and responsible manner.

Overall, balancing AI and intellectual property requires careful consideration of legal, ethical, and practical issues. By addressing these issues and promoting responsible innovation, we can create a balanced and sustainable approach to AI development and intellectual property protection.

Mariam Chaduneli is a Senior Policy Associate who has worked extensively on research and policy analysis in the area of technology policy, emerging threats and digital rights.

Mariam is in charge of monitoring relevant national and international policy developments and producing research relating to digital policy, innovation readiness, and digital transformation. She is also responsible for coordinating long-term research projects, communications, and administrative work across key focus areas for PI. She is the lead project manager for the Network Readiness Index (NRI) published in partnership with Saïd Business School, University of Oxford and coordinates the publication of the Global Innovation Index (GII) in partnership with the World Intellectual Property Organization (WIPO).

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