Patents on Artificial Intelligence Invention
Patents on Artificial Intelligence (AI) Inventions
Introduction
Artificial Intelligence (AI) inventions include software, algorithms, models, or systems designed to perform tasks typically requiring human intelligence. As AI technologies evolve rapidly, patenting these inventions raises unique challenges.
What Constitutes an AI Invention?
AI inventions often involve computer programs, machine learning models, neural networks, or automated decision-making systems.
These inventions may relate to:
The methodology or process of AI functioning,
The system architecture enabling AI,
Specific applications of AI in industries such as healthcare, finance, or autonomous vehicles.
Patentability of AI Inventions
To qualify for a patent, an AI invention must satisfy the fundamental criteria:
Novelty — The AI invention must be new.
Inventive Step — It should not be obvious to a person skilled in the art.
Industrial Applicability — The invention must be useful in industry.
Patentable Subject Matter — The invention must be more than just an abstract idea or mathematical algorithm.
Challenges Specific to AI Inventions
Abstract Nature of Algorithms: AI inventions often involve algorithms or software, which may be treated as abstract ideas and traditionally considered non-patentable.
Determining Inventorship: AI systems can generate inventions autonomously, raising questions about whether a machine or human should be recognized as the inventor.
Disclosure Requirements: Fully explaining AI inventions can be difficult due to complexity and “black-box” nature.
Rapid Evolution: Fast pace of AI technology may render patents obsolete quickly.
Key Legal Issues
Patent Eligibility: Courts examine whether the AI invention is a patentable process or simply an unpatentable abstract algorithm.
Inventorship: Can AI itself be named as an inventor? Traditionally, only natural persons are recognized as inventors.
Scope of Protection: Defining what aspects of AI technology (e.g., data processing methods, hardware integration) can be protected.
Relevant Case Law
1. Thaler v. Commissioner of Patents (Australia, 2022)
Facts: Stephen Thaler applied for patents naming an AI system called “DABUS” as the inventor.
Issue: Whether an AI machine can be recognized as an inventor under patent law.
Outcome: Australian courts rejected the application because only natural persons could be inventors.
Significance: This case highlights that AI cannot currently be recognized as an inventor, impacting how AI inventions are patented.
2. Alice Corp. v. CLS Bank (US, 2014)
Although a U.S. case, it is influential in AI patent eligibility discussions.
Held that abstract ideas implemented on a computer are not patentable unless they contain an inventive concept.
Applied to AI, many software-based AI inventions must demonstrate more than just an abstract algorithm to be patentable.
Approach in India
AI inventions are treated like any other invention and must meet patentability criteria.
Mere algorithmic steps or software per se are not patentable.
If the AI invention produces a technical effect or solves a technical problem, it may be patentable.
The human inventor must be named; AI cannot currently be recognized as an inventor.
Practical Tips for Patenting AI Inventions
Focus on technical application and practical implementation of AI.
Demonstrate a technical solution to a problem, not just the AI algorithm.
Clearly describe the working of the system and its industrial applicability.
Identify the human inventor(s) involved in the creation process.
Summary Table
| Aspect | Explanation |
|---|---|
| What is patentable | AI inventions with technical effect and industrial use |
| Challenges | Abstract nature, inventorship, disclosure, pace of tech |
| Inventorship | Must be a human, AI cannot be inventor |
| Key Case | Thaler v. Commissioner (AI inventor rejected) |
| Patentability Criterion | Novelty, inventive step, industrial applicability |
Conclusion
Patents on AI inventions are possible but come with significant challenges. The invention must demonstrate technical innovation beyond abstract algorithms, and human inventorship is essential. Courts are cautious to balance encouraging innovation and avoiding monopolization of abstract ideas.
RELATED Blog
0 comments