Narrowing the Universe: A Machine Learning Approach to Patent Clearance

Companies cannot reliably predict which patents are likely to be asserted against them. If they could, they would be better able to quantify and mitigate their own patent infringement risk. We used machine learning methods, informed by legal scholars’ understanding of relevant patent traits, to improve on prior attempts to predict litigation. We built primarily on Colleen Chien’s Predicting Patent Litigation. Chien used traits from a patent’s legal history and developed a method of prediction based on the traits acquired before litigation, but not after. She demonstrated that the traits acquired before litigation are useful predictors. Evaluating Chien’s approach, we determined that her logistic regression model was generalizable—that is, not overfit to her training sample—though it does not perform as well on real datasets as her matched-pairs evaluation suggested. We found that year-over-year changes in patenting and litigation will hinder real-world prediction with this approach, but only modestly. Building a much larger dataset of newer patents, and selecting machine learning models tailored to the task, we improved on Chien’s results. Our random forest model had a 7.8% greater area under the precision-recall curve, and it could allow a company to narrow its patent clearance search to a set of patents up to 34% smaller, compared to Chien’s logistic regression approach. We report our results on a random sample of patents using standardized metrics, providing a baseline for future work predicting patent litigation

Trading and Enforcing Patent Rights

We study how the market for innovation affects enforcement of patent rights. Conventional wisdom associates the gains from trade with comparative advantage in manufacturing or marketing. We show that these gains imply that patent transactions should increase litigation risk. We identify a new source of gains from trade, comparative advantage in patent enforcement, and show that transactions driven by this motive should reduce litigation. Using data on trade and litigation of individually-owned patents in the U.S., we exploit variation in capital gains tax rates as an instrument to identify the causal effect of trade on litigation. We find that taxes strongly affect patent transactions, and that reallocation of patent rights reduces litigation risk on average, but the impact is heterogeneous. We show that patents with larger potential gains from trade are more likely to change ownership, suggesting that the market for innovation is efficient, and the impact of trade on litigation depends on characteristics of the transactions.

Predicting Patent Litigation

Patent lawsuits are disruptive, unpredictable, and costly. The inability to anticipate patent litigation makes it practically uninsurable, exposes companies to late-stage suits, and drives companies to rapidly accumulate patents in order to ward off litigation. This article confronts this systemic problem, by examining the factors that lead a particular patent to be litigated – only around 1% of patents ever is. It relates the eventual litigation of a patent to earlier events in the patent’s life, including changes in ownership of the patent (assignments, transfers, and changes in owner size), continued investment in the patent (reexamination, maintenance fees), securitization of the patent, and citations to the patent. To date these “acquired” characteristics, developed after a patent has issued in contrast to the intrinsic qualities a patent is “born” with, have been the subject of limited academic study. The results are dramatic: along all the dimensions studied, patents that end up in litigation have markedly different characteristics than patents that don’t. Importantly for predictive purposes, these differences develop prior to the time of litigation, suggesting that the riskiest patents can be identified ahead of time. The results are also surprising, showing that the likelihood of litigation depends on not only how valuable the patent is but also its owner and transaction history. They draw attention to a policy area that has been long overlooked – ensuring that the public has notice not only of what a patent covers, but also of who owns it and what happens to it. The ease with which patent owners can hide who they are and what they are doing with their patents raise cause for concern, and potential reform, of the patent system

Improving (Software) Patent Quality Through the Administrative Process

The available evidence indicates that patent quality, particularly in the area of software, needs improvement. This Article argues that even an agency as institutionally constrained as the U.S. Patent and Trademark Office (“PTO”) could implement a portfolio of pragmatic, cost-effective quality improvement strategies. The argument in favor of these strategies draws upon not only legal theory and doctrine but also new data from a PTO software examination unit with relatively strict practices. Strategies that resolve around Section 112 of the patent statute could usefully be deployed at the initial examination stage. Other strategies could be deployed within the new post-issuance procedures available to the agency under the America Invents Act. Notably, although the strategies the Article discusses have the virtue of being neutral as to technology, they are likely to have a very significant practical impact in the area of software

Financial Patenting in Europe

We take a first look at financial patents at the European Patent Office (EPO). As is the case at the US Patent and Trademark Office (USPTO), the number of financial patents in Europe has increased significantly in parallel with significant changes in payment and financial systems. Scholars have argued that financial patents, like other business methods patents, have low value and are owned for strategic reasons rather than for protecting real inventions. We find that established firms in non-financial sectors with diversified patent portfolios own a large share of financial patents at the EPO. However, new specialized technology providers in the financial area also hold a number of such patents. Decisions on the financial patent applications take longer and they are more likely to be refused by the patent office, suggesting greater uncertainty over validity than for other patents. They are also more likely to be opposed, which is consistent with the fact that their other economic value indicators are higher.market valuation, intangible assets, patents, software, Europe

The Quality of Ideas: Measuring Innovation with Multiple Indicators

We model early expectations about the value and technological importance ('quality') of a patented innovation as a latent variable common to a set of four indicators: the number of patent claims, forward citations, backward citations and family size. The model is estimated for four technology areas using a sample of about 8000 U.S. patents applied for during 1960-91. We measure how much noise' each individual indicator contains and construct a more informative, composite measure of quality. The variance in quality', conditional on the four indicators, is just one-third of the unconditional variance. We show the variance reduction generated by subsets of indicators, and find forward citations to be particularly important. Our measure of quality is significantly related to subsequent decisions to renew a patent and to litigate infringements. Using patent and R&D data for 100 U.S. manufacturing firms, we find that adjusting for quality removes much of the apparent decline in research productivity (patent counts per R&D) observed at the aggregate level.

Patent Thickets and the Market for Innovation: Evidence from Settlement of Patent Disputes

We study how fragmentation of patent rights ('patent thickets') and the formation of the Court of Appeal for the Federal Circuit (CAFC) affected the duration of patent disputes, and thus the speed of technology diffusion through licensing. We develop a model of patent litigation which predicts faster settlement agreements when patent rights are fragmented and when there is less uncertainty about court outcomes, as was associated with the 'pro-patent shift' of CAFC. The model also predicts that the impact of fragmentation on settlement duration should be smaller under CAFC. We confirm these predictions empirically using a dataset that covers nearly all patent suits in U.S. federal district courts during the period 1975-2000. Finally, we analyze how fragmentation affects total settlement delay, taking into account both reduction in duration per dispute and the increase in the number of required patent negotiations associated with patent thickets.patents, anti-commons, patent thickets, litigation, settlement