Redefining Trademark Clearance

  • anna-ronkainen
  • By Anna Ronkainen

Redefining trademark clearance with intelligent legal technology. Intelligent technologies have the potential to profoundly transform the market for legal services. The intelligent trademark analysis solutions from the Finnish startup TrademarkNow are one example of this -(Published in IPRinfo 1/2013 )Intelligent technologies have made inroads to many aspects of our daily lives. From smartphones to smart homes, the changes have often been so gradual that it is easy to lose sight of all the advances made over the last decade or two.

On the other hand, in the legal workplace, many of the technologies we would take for granted elsewhere are noticeably missing. Instead we rely on information retrieval solutions designed for the 1970s and are satisfied as long as it is easier than using printed books, together with the occasional cosmetic update. This is about to change.

What is intelligent legal technology?

Research into computational models of law, or the research field currently best known as artificial intelligence and the law (AI & law) is even older than the term artificial intelligence itself (1956). Still, unlike many AI subfields, the AI & law community has struggled to recover from the so-called AI winter of the 1980s. The research communityconsists of a few hundred researchers, particularly in the US, UK, Netherlands, and Italy, and it has focused mainly on abstract questions of legal theory with scarce attention given to their applicability to practical systems.

Prompted by technological developments in the society at large as well as the economy drive of the financial crisis, the market for legal services seems ripe for disruption. For example, the highly influential Scottish lawyer/scholar Richard Susskind has just published his fourth book on the future of legal services and he has received a more and more attentive audience with each new iteration.

To mark the changed paradigm and to avoid the unfortunate connotations of the term AI, I prefer to call the application-oriented field by the name of (intelligent) legal technology. Events such as Legal Hackathons and LawTechCamp/ReInvent Law show great promise, and the ongoing startup boom seems quite contagious and not only limited to the household names in the games business. In the US there are already dozens of tech startups in the legal field, and yes, there might already be one or two of them here in Finland as well...

Legal technology for trademark management

Onomatics, Inc. is a legal technology startup specializing in trademark law, founded in 2012 and based in Helsinki, Finland.

Onomatics provides a comprehensive web-based system for trademark management. At its core is an artificial intelligence model of trademark similarity (likelihood of confusion) based on the author’s doctoral research in computational legal theory on computational modelling of vagueness and uncertainty in law at the University of Helsinki, currently at its final stages. The system utilizes a carefully designed blend of both rule-based and statistical techniques to deliver results while managing real-world complexity in the trademark domain. After all, in principle a trademark information system has to be able to represent the entire world of commerce in all existing and fantasy languages in one way or another.

The system currently covers US federal trademarks and EU CTMs with data from USPTO and OHIM, but many more jurisdictions will be added in the near future, starting with international trademark registrations with data from WIPO during Q1/2013.

An intelligent search engine for TMs

Onomatics Quick Search is an intelligent search engine for trademarks, demonstrating the versatility of models of legal decision-making by using one as the foundation for a relevancy ranking of trademarks. It takes into account the role of thegoods and services in the assessment of trademark similarity and hence the ranking of the search results.

For IP professionals the system offers an expert user interface, which allows for comparative evaluation and prioritization of so called long lists of trademark candidates in relation to prior rights. This process has traditionally been seen as cost-intensive and has rarely been done comprehensively.

The system is designed to make sense for both non-experts and IP professionals. For example, in the results summary, the goods and services are represented by immediately understandable icons in addition to the traditional class numbers of the Nice Classification.

This is just the tip of the iceberg, and multiple additional product launches aimed at covering the full trademark lifecycle as well as not directly trademark-related aspects of the corporate and product naming processes are to be expected already later this year.

More information:

by Anna Ronkainen.