Let’s start with understanding what is AI or Artificial Intelligence!
Simply put, artificial intelligence is a broad field aiming to solve problems, AI combines computer science and robust dataset. It also encompasses sub-fields of machine learning and deep learning, which are frequently mentioned in concomitance with artificial intelligence. Then there is weak AI and Strong AI, Deep learning, and Machine learning but let’s not get carried away, we’ll be discussing just an overview of them.
According to our experts, “Weak AI” A.K.A Narrow AI or Artificial Narrow Intelligence (ANI) focuses on specific tasks. You may relate to Apple's Siri, Amazon's Alexa, and even autonomous vehicles for example. Whereas “Strong AI” is made up of Artificial General Intelligence (AGI) and Artificial Super Intelligence (ASI). In this concept, a machine is supposed to have an intelligence equivalent to humans; meaning that strong AI would be self-aware/conscious and have the ability to solve problems, learn, and plan accordingly. Artificial Super Intelligence (ASI) may surpass the intellectual intelligence and ability of the human brain. Although experts say that superintelligence is still a theoretical concept for humans, what’s happening with the military progressions we’ll get to see Super intelligence soon.
Again according to experts, machine learning (ML) and deep learning (DL) are actually just sub-fields of Artificial Intelligence (AI), in fact, deep learning is actually a sub-field of machine learning. Deep learning comprises neural networks. You may understand the difference between DL and ML by the method of how each algorithm learns. Their main function is to eliminate some of the manual human intervention required.
Now let’s see what happens in the “patent searching"
“Patent searching” is a process of searching for existing patents or published patent applications worldwide or within a territorial jurisdiction to determine the novelty and non-obviousness of an invention. This search is generally conducted to assess the potential for obtaining a patent for the invention and to determine if there are any existing patents or published applications that could impact the patentability of the invention.
We see patent searching as an art. It requires an amalgamation of intellect, good keywords, a crystal clear understanding of the domain- of innovation- technology, and a little bit of imagination. When we put all these collectively into a strategy and run it, the search engine treats that as an algorithm. The researcher makes that unique algorithm with different logic every time during the search to get the desired results.
Now that we have cleared what’s what, we can now focus on the real question, can AI do a better job than humans in patent searching?
All the efforts of big and small players in the market to develop and revolutionize machine learning (ML) and artificial intelligence (AI) have rapidly grown in recent years. We can see its impact in terms of advanced robotics, self-driven cars, industrial automation, chatbots, etc. Similarly, in the area of patent search AI and machine learning are being used to automate repetitive tasks and improve the efficiency and accuracy of the search process.
Let’s analyze what the experts have to say on the matter
|S.no.||What seems to be an “advantage” of AI-based search||How much of it is “real”|
|1||AI can analyze a bulk of data way more swiftly than humans. Hence the number of results would increase with it.||Assurance of the results being relevant to the subject patent or the invention is going to be vague and cannot be certain. Also, AI can be biased if they are trained on biased data, leading to unequal or unfair
|2||AI offers improved accuracy; the AI and ML algorithms can identify patterns and relationships in data that may be difficult for humans to perceive.||AI may find a lot of results based on keywords and patterns but AI does not truly understand what those results are trying to implicate so a question could be posed about their usefulness.|
|3||No possibility of error, Since humans are not going to be involved in the frontline. With AI searching reliability and consistency improves by far.||Questionable data quality as the accuracy of AI is only as good as the quality of the data they are trained on and poor-quality data can lead to inaccurate results, which is seen in utmost cases.|
|4||AI can handle large workloads easily. Making the searches easy and doable.||AI is limited by the technology of its time; the algorithms lack creative and analytical abilities in comparison to a skilled team, meaning that AI may end up missing claims, novel points, and important details or even overlook unique solutions.|
|5||An economical and productive solution. Compared to manual searching, AI being in charge of searching can save a lot of time and money.||Needle in a haystack situation. Since the results being valid and relevant are questionable in the case of an AI search, a client/researcher might end up losing their money and time.|
The use of AI in patent searches has the potential to revolutionize the way patents are being searched and analyzed. This technology could become the pinnacle for patent search and can bring benefits such as faster processing times, improved accuracy, consistency, scalability, and cost-effectiveness. Nonetheless, it is highly crucial to address the potential disadvantages first such as technical limitations, lack of understanding, dependence on data quality, bias, and limited creativity. Only after that, we can use AI as a priority tool for Patent search.
In the end, experts say that the goal should be to use AI and human expertise together to improve the overall efficiency and accuracy of the patent search. And we at Virtue Legal Services strive to provide our clients with the necessary details and guide you through the process if any. Our experts are quick, efficient, and focused on your support.