Description

In a subtle yet impactful way, artificial intelligence (AI) algorithms have made considerable inroads into the everyday practice of trade mark law. The appeal of this technology lies in its ability to keep pace with the ever-growing corpus of registered trade marks globally. More marks mean more registrability assessments and more conflicts. Machine learning technologies are used to assist applicants with registration requirements, support examiners who classify signs, and help established right-holders (or new applicants) identify conflicts when new marks are applied for. AI is also entering the domain of enforcement, where it is used to identify unauthorised uses of marks online, including on social media platforms.
This new technology is often presented as merely assisting with the
implementation of existing procedures, rules and doctrines of trade mark law. It appears to be business as usual, just done more efficiently. This lecture sets out to challenge this assumption, by identifying some of the more subtle implications and ripple effects of this transformation of the everyday working of trade mark law – at scale – in the registration and enforcement domains.