As AI continues to revolutionize how we approach problem-solving, inventors and companies alike are increasingly turning to patents to protect their AI-related innovations. However, patenting AI presents unique challenges, especially when it comes to determining what constitutes a patentable AI invention.
This article explores the complexities of AI in the context of patents, offering insights into the challenges and strategies for protecting AI-related inventions in this emerging field.
The AI Patent Landscape
Artificial intelligence (AI) is not a new concept in the patent world. AI has been around for a long time; we just did not call it AI. From early automated telephone systems to today's sophisticated machine learning models, the evolution of AI has been gradual but profound.
The recent explosion in AI capabilities has brought this technology to the masses and to the forefront of patent law discussions.
From AI generated music and art to systems that assist in medical diagnoses, the scope of AI’s influence is vast and growing. As the technology advances, so do the complexities of determining what aspects of AI are eligible for patent protection.
Two primary forms of AI that often come up in patent discussions are predictive AI and generative AI:
- Predictive AI analyzes existing data to predict outcomes or fill in missing gaps. For example, AI might be used to forecast financial trends or identify patterns in medical imaging data.
- Generative AI takes data analysis a step further by creating new content based on learned patterns. This is the type of AI behind AI-generated language, art, music, and software code.
Both forms of AI present potential for innovation, but they also pose unique challenges when it comes to navigating the patent process.
Challenges in Drafting AI Patent Applications
Patenting AI inventions presents unique challenges due to the fluid nature of AI and the current legal framework. Key issues that may arise when drafting AI patents include:
- Complexity and Opacity: Many AI systems, particularly those using deep learning or neural networks, operate as "black boxes" where even the inventors may not fully understand the internal decision-making process. This opacity can make it difficult to describe the invention in the detail required for a patent application.
- Rapid Evolution: The fast-paced nature of AI development means that innovations can quickly become outdated, potentially affecting the long-term value of patents in this field.
- Patent Eligibility: AI inventions often fall under the category of computer-implemented inventions, which face intense scrutiny under patent eligibility laws. Many computer-based innovations are dismissed as abstract ideas, or mental processes or simple concepts. AI is no exception. The courts and the U.S. Patent and Trademark Office (USPTO) use a two-step framework to evaluate whether an invention is patent-eligible under this standard:
- Is the invention directed to a judicial exception, e.g., an abstract idea? If the answer is yes, the invention may or may not be patentable depending on further assessments of additional features in the claims.
- Does the invention provide a practical application that goes beyond the abstract idea? If the AI system creates a tangible improvement in a field or solves a technical problem, it has a better chance of meeting the eligibility criteria.
One important strategy to avoid the "abstract idea" rejection is to show that the AI does more than what a human mind could do manually. AI systems that generate results that would be unpredictable or infeasible for humans to achieve, like complex pattern recognition in enormous data sets, can help strengthen the case for patent eligibility.
USPTO AI Patent Guidelines and Recent Developments
Recognizing the growing importance of AI, the USPTO has introduced new guidelines to help navigate patent eligibility issues related to AI. These guidelines, issued in July 2024, provide more clarity on what constitutes patentable subject matter when it comes to AI. They reinforce the need for AI-related inventions to be framed within a practical application or tied to improving a specific technology.
For example, AI that optimizes computer processing times or enhances data analysis methods may be considered patentable if the invention goes beyond simply executing an algorithm. In contrast, inventions that rely solely on AI's ability to perform mental processes or mathematical calculations will likely face an uphill battle to secure a patent.
As this field evolves, the USPTO is likely to issue additional AI patent guidance. AI patent considerations should be discussed with an experienced AI patent attorney to ensure new developments are included in any AI-related patent applications.
Strategies for Patenting AI Inventions
Taking into account the USPTO’s recent guidance and common AI patent application challenges, there are several strategies that inventors and companies can employ when drafting patent applications to protect AI-related innovations:
- Focus on Practical Applications: Emphasize how the AI invention solves a specific problem or improves a particular technology. For example, in biomedical applications, AI that leads to better diagnosis and treatment decisions may be more likely to meet patent eligibility criteria.
- Highlight Technical Improvements: Demonstrate how the AI invention improves a computer or other technology’s function. This could include innovations that make computations faster or more efficient.
- Describe the Training Process: While the internal workings of an AI model might be opaque, the process of training the model can often be described in detail. This can be a valuable aspect to include in patent applications and may also help address evolutions or updates to the AI.
- Protect Multiple Aspects: Consider patenting various elements of the AI system, including:
- The AI model itself
- The training methodology
- Input and output processes
- Hardware implementations
- Demonstrate Real-Time and Practical Results: Emphasize capabilities that clearly surpass human cognitive abilities, such as processing vast amounts of data in real-time to produce actionable results.
- Partner with an Experienced AI Patent Attorney: Work closely with an experienced AI patent attorney to ensure your patent application is drafted to address these common AI patent concerns and overcome patenting obstacles from the onset.
Can AI Itself Be an Inventor?
Another big question in patent law today is whether AI can be considered an inventor. Current laws generally require that an invention be the product of human ingenuity. However, what happens when an AI system creates something novel?
The courts and patent offices around the world are still grappling with this question. USPTO and courts have historically focused on the human inventor, but with AI's increasing role in invention, this could change over time.
For now, AI-generated inventions remain tools to assist human inventors rather than independent inventors themselves. The boundaries between AI assistance and AI-driven innovation are still developing.
The Future of AI Patents
As AI continues to advance, we can expect further evolution in patent law and practice. The increasing use of AI in fields like biotech and data analysis presents both opportunities and challenges for patent protection.
The patent system tries to and is intended to be a completely generic system, meaning that it is a system where the rules, procedures, and ways of viewing patentability of an invention should be technology neutral to the extent possible. This principle suggests that while AI may present new challenges, the fundamental approach to patentability remains consistent, regardless of the technological advancement.
For now, AI may be best viewed as a tool that enhances human ingenuity, rather than a standalone inventor. However, with ongoing developments in the field and growing reliance on AI for innovation, we may eventually see further shifts in how the patent system treats AI-generated outcomes.
Conclusion
As the field evolves, collaboration between technologists, legal professionals, and policymakers will be key in shaping a patent system that promotes innovation while protecting intellectual property in the age of AI.
By focusing on practical applications, technical improvements, and clear descriptions of AI systems, innovators, in partnership with an AI patent attorney, can increase their chances of successfully patenting their AI-related inventions.
Questions about securing IP for an AI-related invention? Pabst Patent Group specializes in intellectual property law in the biotech, pharmaceutical, and chemical industries. Our lawyers leverage their deep scientific, legal, and business expertise to create effective IP strategies to create real impact. Contact us today to learn more.
