Imagine you're an artist who has worked hard to create a beautiful painting, and some AI system has used your work to generate a new image without your permission. That sounds pretty unfair, right? This situation is not uncommon in the AI industry.

Take Stability AI, for example, a company that develops image generation models (such as Stable Diffusion) that are trained using a large number of images from the Internet, many of which are copyrighted works. This sparked a legal controversy when Getty Images, a well-known image rights company, filed a lawsuit against Stability AI for the unauthorized use of a large amounts of its copyrighted works, arguing that this not only infringed on its copyrights but could also lead to a decrease in the market value of its works.

This case reveals the complex challenges and opportunities for IP rights in the context of the rapid development of AI technology and triggers an in-depth discussion on the balance between technological innovation and legal compliance. The Court has now ruled that the case can proceed, and the first round of trials is scheduled to begin in June 2025.

What is AI and IP?

Artificial Intelligence (AI) is a technology that mimics human intelligence processes and is designed to enable computer systems to perform tasks that would normally require human intelligence.

Intellectual property (IP) refers to the legal protection of creations, inventions and other intellectual achievements. It covers a wide range of aspects such as patents, copyrights, trademarks and trade secrets, and aims to protect the rights and interests of innovators and encourage creativity and invention.

Challenges to IP Rights in the Age of AI

‍

As AI technology continues to advance, IP rights face several challenges:

1. Patent Protection

Inventor Issue: Who should be legally attributed as the inventor of an AI-generated technology or product? For example, if an AI system develops a new algorithm, can the AI be legally considered the inventor? Currently, the patent laws of most countries only recognize natural persons as inventors, e.g., the laws of the U.S., the EU, and Japan all require that the inventor must be a natural person.

Complexity of Patent Applications: Due to the rapid iteration of AI technologies, it becomes complicated to accurately describe these technologies when applying for a patent, which may result in the application being rejected or the scope of protection being too narrow. Applicants need to clearly articulate the innovation and its advancement over prior art, but the complexity of AI algorithms makes this process difficult. In addition, applicants need to conduct exhaustive patent searches to avoid the risk of infringement.

2. Copyright Issues

Attribution of Copyright: The attribution of copyright to AI-generated artistic works, such as music and images, still lacks clear legal provisions in many countries. Existing copyright laws usually only protect works created by humans, which puts AI-generated works at legal risk.

Use of pre-existing works: The use of pre-existing works in training AI systems raises several copyright issues. First, these works are typically protected by copyright law, and unauthorized use may lead to infringement, so developers need to understand the relevant copyright status. Second, the lack of transparency in datasets makes it hard for copyright holders to track how their works are used, complicating rights enforcement. Additionally, the ambiguity of the fair use principle makes it challenging for developers to know if their usage is lawful, as legal use usually requires authorization, which can be time-consuming and costly. Finally, differences in copyright laws across countries mean that developers must be well-informed about regulations in various regions to avoid legal liabilities. Therefore, developers should be cautious when using existing works to ensure the legality and sustainability of AI technologies.

3. Trade Secret Protection

Technical Transparency: In the AI field, many companies regard their algorithms and data as trade secrets to maintain a competitive edge. However, technical transparency poses a risk of leakage that could lead to competitors gaining access to key information, which could affect a company's market position and customer trust. To protect trade secrets, companies should implement strict internal controls, such as restricting access, employee training, signing confidentiality agreements, and utilizing encryption technology and monitoring tools.

Impact of IP Issues in AI Industry on Investors

‍

In almost every industry, IP issues are an important consideration in investment decisions. However, we will focus on the AI sector to explore the risk implications of IP issues for potential investors.

1. Challenges of IP Infringement

In the age of AI, IP infringement issues pose significant risk challenges for investors. Although there are currently no clear legal provisions finalized in national laws for determining IP infringement issues related to AI, some existing cases show that there is indeed a risk of infringement. Due to the complexity of AI technology, it is often difficult to define infringement, which can expose investors to potential legal liability and financial loss.

If a target company is accused of infringing on the IP rights of others, it may not only lead to legal action, but may also trigger high damages and injunctions, forcing the company to stop the production and sale of relevant products, thus affecting its revenue stream. Therefore, when conducting due diligence, investors should pay special attention to the target company's IP rights compliance, past infringement records, and the company's measures in preventing such risks, to minimize the risk of a potential investment.

2. Impact of IP Policies and Regulation

The AI industry is facing increasingly stringent IP policies and regulation, particularly with respect to data privacy and algorithmic transparency. For example, the EU's GDPR, which requires companies to obtain user consent, has impacted the data acquisition strategies of many companies, and Facebook and Google are under significant compliance pressure to respond to these regulations.

Meanwhile, algorithmic transparency requirements force companies to ensure their decision-making processes are explainable, impacting the ability to innovate. Investors should focus on the compliance frameworks and flexibilities of target companies, such as IBM's investment in data governance, that allow it to remain competitive in the marketplace. Companies that fail to adapt to policy changes in a timely manner may face lawsuits and fines, impacting financial health and reputation. Thus, a comprehensive understanding of these policy developments is critical for investors to make informed decisions.

3. Reliance on the Industry Trends and Market Adaptation

In the rapidly evolving AI industry, investors must pay attention to the rate of technology updates, industry trends, and changes in market demand to ensure the effectiveness of their investment decisions. As new algorithms and applications continue to emerge, target companies that fail to maintain patent protection for key technologies may be at a competitive disadvantage.

Rapid changes in market demand require the company to have good technology and market adaptability to adjust product strategies in a timely manner to meet customer needs. Understanding the overall industry conditions, including policies, regulations and technology trends, is critical to assessing the risk and return on investment. Only companies that continue to innovate and adapt to changes in the industry can achieve sustainable growth, so as to better identify investment opportunities and risks.

Conclusion

The intersection of AI and IP rights poses significant challenges and opportunities, especially for investors. The legal dispute between Getty Images and Stability AI highlights the complexities surrounding copyright and patent issues in the AI industry.

As AI technology continues to evolve, the complexities surrounding patent protection, copyright issues, and trade secret management necessitate a thorough understanding of IP rights. Investors should remain vigilant regarding potential IP infringements, the impact of regulatory changes, and the need for companies to adapt to shifting market demands.

‍