Recent advancements in AI have sparked debate over its role in innovation, particularly with the controversial DABUS cases that questioned whether an AI machine can be named as an inventor on patents worldwide. DABUS, created by Dr. Stephen Thaler, allegedly generated inventions autonomously, leading to patent applications worldwide listing it as the sole inventor. However, courts in major jurisdictions ultimately ruled that under current patent laws, only a natural person can be recognized as an inventor. As AI becomes more sophisticated, a question remains: can it ever become an inventor?
This blog is written by Helen McFadzean, a seasoned attorney with a particular focus on artificial intelligence. She currently focuses on obtaining patents, trademarks, and designs for businesses in Australia and overseas.
Imagine a groundbreaking invention - something that could disrupt industries, save lives, or redefine the future. Now, picture the inventor. Is it a team of engineers and scientists? A lone genius in a garage? Or could it be… a machine?
In recent years, rapid advancements in AI technology have fuelled widespread debate about the role of AI in innovation. In and around 2022, the controversial DABUS cases challenged patent systems around the world by asking a fundamental question: can an AI machine be named as an inventor on a patent application? DABUS (Device for the Autonomous Bootstrapping of Unified Sentience) is an AI machine created by Dr. Stephen Thaler, which allegedly generated a number of inventions autonomously. Patent applications were filed around the world naming DABUS as the sole inventor. Ultimately, many of those applications were rejected as the Courts in major jurisdictions such as the US, UK, EU and Australia determined that an AI machine cannot be named as an inventor under current patent legislation, which require a natural person to be the inventor. The articles analysing the Australian patent office and Court decisions can be found here, here and here.
The DABUS cases primarily served to test the limits of patent law, raising the question of whether the term ‘inventor’ in patent legislation could be construed to include a non-human entity. In most jurisdictions, the answer was no. At the time, this aligned with the prevailing understanding that AI machines and algorithms were seen as powerful tools that could identify patterns in data, but they required human intervention to define problems, interpret results, and ultimately drive the inventive process. Many legal and technical experts largely agreed that when AI-assisted inventions emerged, it was the human, rather than the machine, who ultimately carried out the act of inventing.
But much has changed since those initial debates in 2022. AI technology has advanced rapidly in this short time, demonstrating capabilities that go beyond pattern recognition and predictive analysis. In this talk - How AI Will Step Off the Screen and into the Real World | Daniela Rus | TED - Dr. Daniela Rus, director of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), discusses liquid neural networks, a new class of adaptive AI models inspired by neurons of a worm, which can dynamically adjust their internal equations to handle complex real world data more flexibly and efficiently. She also discusses generative AI (GAI) systems that can transform textual descriptions into functional robots (‘text to robot’) and convert images into robotic designs (‘image to robot’). The combination of liquid networks and such ‘text/image to robot’ GAI systems could lead to a transformative leap in the field of robotics, enabling more adaptive, creative, and efficient systems, faster prototyping and innovation cycles.
Is AI still just a tool, or has it evolved into something more? Can AI systems invent today, and will it be capable of inventing in the future? If the answers are yes, will our current patent laws be sufficient to protect inventions driven by generative AI, such as the "text/image to robot" systems discussed above, and encourage the growth of future innovative industries?
These questions do not have easy answers. Today, many AI systems still rely on human direction and interpretation to define their purpose and meaning. However, as GAI continues to advance, we may find that AI could play a more autonomous role in driving innovation in the not-so-distant future.
While the current patent systems do not accommodate AI as an inventor, it remains uncertain whether this will necessarily stifle innovation. As long as a human is involved and makes a material contribution to the inventive process, the human can be named as an inventor to satisfy the administrative requirements for naming an inventor in a patent application. One thing is certain though, advanced AI systems will accelerate innovation, potentially raising the bar for granting new patents, as inventions must also meet the non-obviousness requirement. History shows that the law is often playing catch-up with rapidly evolving technologies, and patent law is no exception. This is certainly an area worth watching closely.
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