The United States Patent and Trademark Office (USPTO) has recently issued guidance that seeks to clarify the murky waters of AI contributions in the realm of patents, a move that holds significant implications not just for American innovators but also for Indian stakeholders who are deeply entrenched in the global innovation ecosystem.As AI continues to challenge the traditional notions of creativity and inventorship, the USPTO's directions may serve as a beacon for navigating these uncharted territories. Let's see.
For Indian researchers, startups, and multinational corporations, understanding and adapting to these guidelines is not just a matter of legal compliance but a strategic imperative that could define their competitive edge in the international market.
In this insight, we will delve into the nuances of the USPTO's guidance on AI patentability, exploring its potential impact on the Indian landscape of innovation. We will examine how these directions might shape the future of AI development in India and what it means for Indian entities to align with global standards while fostering an environment that encourages human ingenuity and protects intellectual property rights. Through this lens, we aim to offer a comprehensive analysis that resonates with the ethos of Indian constitutionalism and the broader aspirations of India's technological advancement.
The Inventorship Guidance for AI-Assisted Inventions
This guidance, which went into effect on February 13, 2024, aims to strike a balance between promoting human ingenuity and investment in AI-assisted inventions while not stifling future innovation. We must remember that the Guidance did refer the DABUS cases in which Stephen Thaler's petitions on declaring an AI to be an inventor were denied.
The USPTO's guidance emphasises that AI-assisted inventions are not categorically unpatentable, but rather, the human contribution to an innovation must be significant enough to qualify for a patent when AI also contributed. The guidance provides instructions to examiners and stakeholders on determining the correct inventor(s) to be named in a patent or patent application for inventions created by humans with the assistance of one or more AI systems.The issue of inventorship in patent law for AI-created inventions remains of particular importance to companies that develop and use AI technology. While AI has unquestionably created novel and nonobvious results, the question of whether AI can be an "inventor" under U.S. patent law remains unanswered.
The USPTO's guidance reiterates that only a natural person can be an inventor, so AI cannot be listed as an inventor. However, the guidance does not provide a bright-line test for determining whether a person's contribution to an AI-assisted invention is significant enough to qualify as an inventor.
The ability to obtain a patent on an invention is a critical means for businesses to protect their intellectual property and maintain a competitive edge. Also, the requirement that an "inventor" be a natural person might not be at odds with the reality of AI-generated inventions. As the conversation around AI inventorship unfolds, companies should be aware of alternative ways to protect their AI-generated inventions, such as using trade secrets. The USPTO's guidance on AI patentability is a significant step towards providing clarity to the public and USPTO employees on the patentability of AI-assisted inventions.
The USPTO has provided examples in their guidance to illustrate the application of the guidance. Let's understand the examples provided by them:
AI-generated drug discovery: In this example, a researcher uses an AI system to analyze a large dataset of chemical compounds and identify potential drug candidates. The AI system suggests a novel compound that the researcher synthesizes and tests, confirming its efficacy. The guidance indicates that the researcher would be considered the inventor, as they made a significant contribution to the conception of the invention by selecting the dataset, designing the AI system, and interpreting the results.
AI-generated materials design: In this example, a materials scientist uses an AI system to design a new material with specific properties. The AI system suggests a novel material composition, which the scientist then fabricates and tests, confirming its properties. The guidance indicates that the scientist would be considered the inventor, as they made a significant contribution to the conception of the invention by defining the problem, selecting the AI system, and interpreting the results.
AI-generated image recognition: In this example, a software engineer uses an AI system to develop an image recognition algorithm. The AI system suggests a novel neural network architecture, which the engineer then implements and tests, confirming its performance. The guidance indicates that the engineer would be considered the inventor, as they made a significant contribution to the conception of the invention by defining the problem, selecting the AI system, and implementing the suggested architecture.
The guidance is open to comments until May 13, 2024, and may change, but in the meantime, inventors seeking patent protection for their AI-assisted inventions should consider carefully documenting the human contribution on a claim-by-claim basis, including the technology used, the nature and details of the AI system's design, build, and training, and the steps taken to refine the AI system's outputs.
Implications for Indian Research Institutions
The USPTO's guidance on AI patentability could have significant implications for Indian research institutions, which are at the forefront of AI innovation. The recent memorandum of understanding between the USPTO and the Indian Patent Office at Kolkata to cooperate on IP examination and protection could facilitate collaboration and intellectual property sharing between Indian researchers and global partners.
This agreement could pave the way for joint research projects, knowledge exchange, and capacity building in the field of AI.Moreover, the growing partnership between the US and India in scientific research could further strengthen collaboration in AI. The US National Science Foundation and Indian science agencies have agreed to launch 35 jointly funded projects in space, defense, and new technologies, including AI.
This initiative could encourage higher-education institutions in both countries to collaborate on AI research and development, leading to new discoveries and innovations.However, regulatory bureaucracy and visa processing delays could pose challenges to scientific collaboration between India and the US.
To overcome these obstacles, Indian research institutions could assign a designated individual to manage joint programs and projects with US partners, as suggested by Heidi Arola, assistant vice-president for global partnerships and programmes at Purdue University. Choosing the right institutional partner with compatible goals is also crucial for successful collaboration.
Impact on Indian Startups and Entrepreneurs
The USPTO's guidance on AI patentability presents both challenges and opportunities for Indian startups and entrepreneurs seeking international patents. The guidance emphasises the need for a significant human contribution to the conception or reduction to practice of the invention, which could make it more difficult for AI-focused startups to secure patents.
However, the guidance also provides clarity on the patentability of AI-assisted inventions, which could help startups navigate the patent application process more effectively.Clarity in AI patentability could also affect investment and growth in the Indian startup ecosystem. Investors may be more likely to fund startups with a clear path to patent protection, leading to increased innovation and economic growth. Moreover, the USPTO's initiatives to increase participation in invention, entrepreneurship, and creativity, such as the Patent Pro Bono Program and the Law School Clinic Certification Program, could provide valuable resources and support to Indian startups and entrepreneurs.
Relevance for Indian Industry and Multinational Corporations
Indian industries and multinational corporations operating in India must navigate patent filings in light of the USPTO's guidance on AI patentability. The guidance emphasizes that AI cannot be an inventor, coinventor, or joint inventor, and that only natural persons can be named as inventors in a patent application.
This could have significant implications for companies developing AI-based inventions, as they must ensure that human contributors are properly identified and credited.Moreover, the potential need for harmonization of patent laws to facilitate cross-border innovation and protect intellectual property could affect Indian industries and multinational corporations.
The USPTO's Intellectual Property Attaché Program, which has offices and IP experts located full-time in New Delhi, could provide valuable assistance to U.S. inventors, businesses, and rights holders in resolving IP issues in the region.
However, Indian companies may also need to engage with local IP offices and legal counsel to develop an overall IPR protection strategy and secure and register patents, trademarks, and copyrights in key foreign markets.
Understanding Readiness on AI Patentability for India
As the world continues to focus on AI's potential, Indian regulators may not require to respond to the USPTO's guidance and the broader global discourse on AI inventorship by clarifying the patent eligibility framework for AI-related inventions in India, for now. The reason is obvious.
In a recent response in the Rajya Sabha, a Minister of State (MoS) of the Ministry of Commerce and Industry reiterated that AI-generated works, including patents and copyrights, can be protected under the current IPR regime. This statement, while seemingly obvious, holds significance for India's position in the global AI landscape.
Under international copyright law, only individuals, groups of individuals, and companies can own the intellectual properties associated with AI. The MoS's statement aligns with this principle, indicating that India is open to nurturing AI innovations within the existing legal framework. This position could be interpreted as an invitation for investment and economic opportunities in the AI sector, potentially positioning India as a safe and reasonable hub for AI development.
However, it is crucial for governments to carefully observe and address attempts by big companies to promote anti-competitive AI regulations. Creating a separate category of rights for AI-generated works could lead to challenges in compensating for and justifying contributions to the intellectual property, as well as the associated economic ramifications.
Andrew Ng, a prominent figure in the AI community, has expressed concerns about big companies pushing for anti-competitive AI regulations. He notes that while the conversation around AI has become more sensible, with fears of AI extinction risk fading, some large corporations are still advocating for regulations that could stifle innovation and competition in the AI sector.
One of the specific points made by Ng is the ongoing fight to protect open-source AI. Open-source AI refers to the practice of making AI software, algorithms, and models freely available for anyone to use, modify, and distribute. This approach fosters collaboration, accelerates innovation, and democratises access to AI technology. However, some big companies may seek to impose restrictions on open-source AI through regulations, potentially limiting its growth and impact.
An example of the importance of open-source AI can be seen in the development of popular AI frameworks like TensorFlow and PyTorch, which have become essential tools for AI researchers and developers worldwide. These open-source projects have enabled rapid progress in AI by allowing researchers to build upon each other's work and share new ideas more easily.
Furthermore, recent research from the University of Copenhagen suggests that achieving Artificial General Intelligence (AGI) may not be as imminent as some believe.
The study argues that current AI advancements are not directly leading to the development of AGI, which is the hypothetical ability of an AI system to understand, learn, and apply knowledge across a wide range of tasks at a level comparable to a human being.
This research underscores the importance of maintaining a competitive and innovative AI landscape, as the path to AGI remains uncertain and may require ongoing collaboration and breakthroughs.
There is another perspective for the Indian ecosystem to consider: R&D and innovation appetite.
The insight shared by Amit Sethi, a Professor at the Indian Institute of Technology, Bombay, highlights a significant issue in India's AI landscape. Despite the ongoing AI funding summer in India, the best AI talent in the country is still primarily focused on fine-tuning existing AI models rather than developing cutting-edge AI technologies. This situation poses several challenges for India's AI aspirations.
India's AI funding summer, which has seen significant investments in AI startups like Krutrim AI and RagaAI, is yet to produce credible AI use cases. The demand for generative AI services is rising, but the Indian AI ecosystem needs to mature to deliver on this potential.
Nandan Nilekani, the visionary behind India's Aadhaar, emphasizes the importance of developing micro-level or smaller AI use cases instead of attempting to create large models like OpenAI. However, the challenge lies in identifying and standardizing AI model weights for smaller, limited-application use cases that can work effectively over the long term.
India's tech policy on AI, including the IndiaAI initiative, cannot succeed without prioritizing local capabilities. The Indian tech ecosystem must focus on nurturing homegrown companies to create wealth and intellectual property. An American semiconductor company CEO also emphasized that India needs to capitalize on the AI revolution through homegrown companies rather than relying on multinational corporations.
Some major Indian companies are developing AI use cases that are becoming knock-offs or heavily reliant on models built by OpenAI, Anthropic, and others. This dependence on external AI models should be avoided to foster genuine innovation in the Indian AI landscape.
Suggestions for Indian Stakeholders
Indian stakeholders, including research institutions, startups, and industries, should prepare for possible changes in patent law and international intellectual property norms by:
Staying informed about the latest developments in AI patentability, both in India and globally.
Ensuring that AI-related inventions meet the fundamental legal requirements of novelty, inventive step, and industrial application.
Focusing on integrating AI features into practical applications to demonstrate a technical contribution or technical effect.
Providing clear and definitive empirical determinations of technical contributions and technical effects in patent applications.
Engaging with policymakers and patent offices to advocate for a balanced approach to AI patentability that protects the rights of inventors while fostering innovation.
Conclusion
Understanding the USPTO's AI patentability guidance is crucial for Indian stakeholders, as it could significantly impact the growth of AI-related inventions in the country. By proactively engaging with global patentability standards and adapting to changes in patent law, Indian stakeholders can support innovation in India's research, startup, and industry sectors. As the world continues to grapple with the challenges and opportunities presented by AI inventorship, India has the potential to emerge as a leader in AI-related patent filings and contribute to the global discourse on AI patentability.