Standards, AI & the Data Transparency Imperative

 This week on IPWatchdog Unleashed we take a look at the importance of data transparency and standards for artificial intelligence (AI) and standard essential patents (SEPs). Our guest is Tim Pohlmann, who is the Managing Director for the Americas at LexisNexis Intellectual Property Solutions. And before he joined LexisNexis, Tim was the founder and CEO of IPLytics. Tim has worked at the intersection of data and standard essential patents for a long time, and the themes of data integrity, data transparency and how data can be used to influence and inform decision-making was the focus of our conversation. 

We being our conversation talking about entrepreneurship and leadership from the perspective of a founder and owner of a company that has been acquired, which is a welcome and happy occurrence, but not without challenges. 

As we pivoted the conversation to begin discussing data, standard essential patents and artificial intelligence, we transitioned by discussing first how the industry continues to evolve and never stays the same for very long, how there is so much innovation in the industry, and how there are economic and national security implications with China understandably wanting Chinese companies to dominate the technology future and the United States understandably wanting American companies to dominate. This can lead to tensions, and China, the U.S. and Europe all seem to be jockeying to set the technology standards of the future.

We proceed to talk about the United States and China competing on technology lead us into a conversation about AI and the role standards will play, which was front of mind probably because we recorded this conversation right as news of DeepSeek, China’s allegedly new super-advanced AI, was breaking. 

As we pivoted away from AI and into more traditional standard essential patents, particularly focusing on telecommunications (i.e., 5G and 6G), I acknowledge that while there will be need for AI standardization, and there will be a lot of unique questions arise in that context, we still don’t have a lot of answers in a number of critical areas for well-known and well-established technologies. This paved the way for us to discuss FRAND and to tackle the question about whether a FRAND rate really exists in the first place.

Our conversation goes on to discuss implementers understandably wanting to pay only to license patents that cover technologies that are actually included in the adopted standard, the potential that the Federal Circuit will rule that lump sum license payments are not relevant to determining a fair and reasonable licensing rate, what considerations go into converging on a rate that is FRAND, bulk discounting, and the role data plays in lifting the curtain so implementers who are themselves competitors with other implementers can determine whether they are getting a rate that will make them uncompetitive, and much more.  

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