T 1358/09 - Technical considerations in text classification (AI, ML)
This blog post is a first one of a series of blog posts in which we discuss past and recent decisions which are relevant to the field of artificial intelligence (AI) and machine learning (ML). We start with discussing older decisions which form the basis for the EPO's current approach to assessing the patentability of artificial intelligence and machine learning-based inventions.
While the revised GL G-II, 3.3.1 generally refers for guidance for the patentability of AI/ML-based inventions to mathematical models, a few areas are explicitly identified in which AI/ML is considered to make a technical contribution, such as using a neural network to identify irregular heartbeats, and classification of digital images, videos, audio or speech signals based on low-level features.
The following decision, however, is cited as an example of where machine learning does not serve a technical purpose, namely in the classification of text documents in respect of their textual content.
In particular, the Board considers the following not to make a technical contribution per se:
While the revised GL G-II, 3.3.1 generally refers for guidance for the patentability of AI/ML-based inventions to mathematical models, a few areas are explicitly identified in which AI/ML is considered to make a technical contribution, such as using a neural network to identify irregular heartbeats, and classification of digital images, videos, audio or speech signals based on low-level features.
The following decision, however, is cited as an example of where machine learning does not serve a technical purpose, namely in the classification of text documents in respect of their textual content.
In particular, the Board considers the following not to make a technical contribution per se:
- Determining whether text documents belong to the same class of documents in respect of their textual content, as the Board considers this a cognitive rather than technical consideration.
- Providing an improved textual classification over manual classification by using precise computation steps which no human being would ever perform when classifying documents; the Board considers a comparison with what a human being would do not to be a suitable basis for distinguishing between technical and non-technical steps.
- Providing a faster classification than prior art classification methods; the Board considers the algorithm not to go beyond a particular mathematical formulation of the task of classifying documents, and in particular, the design of the algorithm not to be motivated by technical considerations of the internal functioning of the computer to make it 'faster'.
- Providing a reliable and objective result, as the Board considers this an inherent property of deterministic algorithms and not to make a technical contribution on its own.
SHARE:
