This online section of the University of Illinois Journal of Law, Technology & Policy contains drafts of Articles, Essays and Student Notes that have been accepted for publication and currently are undergoing the peer-review process. Although these drafts may not reflect the content or form of the final publication, they are placed in this section to elicit feedback from the site's scholarly visitors. Comments on the materials in this section may be made by emailing JLTP directly.
Volume 2017 — Issue 2 (Fall)
"The Theory of Abuse in Google Search: A Positive and Normative Assessment under EU Competition Law" by Pinar Akman
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"Imagination, Invention, and Patent Incentives: The Psychology of Patent Law" by Richard S. Gruner
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Unfortunately, individuals are prone to errors in such imagination projects due to imagination limitations present in all persons. Patentable inventions are difficult to produce for reasons embedded deep in human psychology. Special incentives are needed to promote optimal efforts to overcome psychological barriers to imagination and invention.
Several types of imagination weaknesses impede the production of patentable advances. Limitations of human psychology cause many persons to err systematically in predicting the future, resulting in inaccurate projections of future actions of others and of the actions and items that that will make persons happy in the future. In the context of inventive efforts, these systematic weaknesses in human imagination cause inventors to mistakenly project how items incorporating significant variations from present technologies will operate and serve potential users.
These errors are especially prevalent as inventors develop outlier advances potentially qualifying for patent protections. Such advances are typically based on distinctly new and untried technologies about which inventors have little experience and background knowledge. Inventors must expand on very little knowledge and imagine a great deal to produce invention designs based on these untried technologies.
Inventors’ imagination errors may undercut invention projects at many stages. Inventors may mistakenly imagine how significantly new technologies will function when incorporated in new products or processes, how the new functionality achieved through new invention designs will contribute to the practical tasks of invention users, or how new designs will translate into commercially viable products – that is, products that are at once manufacturable, marketable, and well-received by potential users. Because inventors frequently make errors in foreseeing one or more of these key factors, many attempts to produce patentable advances incorporating distinctively new technologies are systematically doomed to failure. Human psychology creates inherent barriers to these inventions through the weaknesses of human imagination.
Obviously, not all invention efforts incorporating significantly new technologies are doomed to failure. However, given the imagination barriers involved, success in producing useful advances based on new and unproven technologies will be rare. We should have a healthy respect for the difficulty of these efforts and construct patent laws accordingly.
The rarity of correctly imagined and successfully realized inventions involving significantly new technologies has three implications for patent laws. First, patent incentives should be targeted with psychological weaknesses of invention imagination in mind. This means that patent incentives should be greatest where imagination weaknesses are most likely to impair inventors’ foresight about future invention functionality and the impacts of distinctive, non-obvious technological changes. Second, patent rewards should be sized to ensure that payoffs for rare invention successes compensate inventors for their many likely failures based on imagination barriers. Inventors who overcome these barriers -- by successfully imagining both future public needs and non-obvious technology changes that will serve those needs -- deserve compensation that takes into account the probable failures of many invention attempts before one successful attempt gains a valuable patent. Third, patent rights should be enforced to promote rapid and extensive product commercialization and popularization efforts regarding patented inventions since these test and filter inventions based on their practical value. Such enforcement should help ensure that rare successes in overcoming imagination barriers and creating valuable products based on significantly new technologies will receive the public attention and access that they deserve.
Patent incentives encouraging hard-to-imagine inventions and the commercialization of such inventions serve the public in both the present and the future. The public benefits in the present because this combination of incentives tends to bring more hard to imagine, non-obvious technologies into widespread public use and potential public service. The public benefits in the future because patent disclosures of present advances enhances the design knowledge available to future inventors. Insights encouraged by patent rewards are added to the body of information constituting the useful arts. Thereafter, these insights become commonly available tools for future parties to use in formulating additional product designs and engineering analyses.
This article uses psychological insights into imagination processes to interpret patent laws and to advocate changes in light of imagination barriers. The article addresses four related topics. First, it describes recent advances in psychology research regarding systematic imagination errors. Second, the article describes how these systematic errors affect the creation of new and non-obvious inventions of the sort governed by patent laws. Third, the article considers how patent standards – particularly standards for patentable subject matter and tests for the non-obviousness of invention designs – work to offset invention weaknesses by boosting the production and popularization of inventions otherwise impaired by imagination weaknesses. Fourth, the article considers psychology-informed changes in patent laws to better offset imagination weaknesses and help to reduce the negative societal impacts of invention imagination errors hindering new technology development and progress.
"Internet, New Technologies and Value: Taking Share of Economic Surveillance" by W. Gregory Voss
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During the reading of Benabou and Rochfeld’s book, we note that an important actor in the creation of value—the consumer—does not necessarily receive his or her share of the resulting value. The law, which has a role in defending certain values, whether it be copyright law, competition law, or contract law, has difficulties in a dealing with new paradigms created by new technologies and information. In Europe, fundamental rights and consumer law are supposed to help the web user, but do they go far enough? The book’s authors propose beginnings of solutions to the law’s difficulties in this context—based on transparency, technical mastery of content by the consumers who created it, control of consent, and collective actions. Although the book leaves us hungry for more, it leaves us thought-provoked as the reviewer comments.
"Safety First: The Case for Mandatory Data Sharing as a Federal Safety Standard for Self-Driving Cars" by Jesse Krompier
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Safety requires automation data. Automation data includes detailed information about the driving infrastructure (i.e., maps, signs, and speed limits), dynamic objects (i.e., other cars, cyclists, and pedestrians), and driving events like crashes, disengagements, and lane merges. Carmakers are engaged in an arms race to collect massive volumes of automation data so that they can teach their cars to make safer driving decisions.
But there is a problem: carmakers are fiercely competitive, and they don’t want to share data. As such, carmakers who have gaps in their data sets will build self-driving cars that could make unsafe decisions and cause accidents. Because of data secrecy, however, it is virtually impossible to determine where data gaps exist and whether each carmaker’s data set is sufficiently complete to ensure safe driving. State legislatures have struggled to enact comprehensive data reporting laws because they want to encourage innovation in their states.
This Note analyzes what states have done to address the need for data sharing, why they have failed, and argues that the National Highway Traffic Safety Administration should set forth a mandatory data sharing framework as a new federal safety standard for self-driving cars.
Volume 2018 — Issue 1 (Spring)
"A Location-Based Test For Jurisdiction Over Data: The Consequences For Global Online Privacy" by Shelli Gimelstein
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This Note argues that basing government jurisdiction over data on the data’s physical location threatens user privacy. It also creates unworkable and unpredictable results for technology companies by failing to account for the significant differences in how they divide, store and transmit their users’ data around the world. In the context of digital searches, the data location test has two potential effects. First, it will create bottlenecks in the already-burdensome mutual legal assistance system, hindering intergovernmental cooperation on law enforcement investigations. Second, it may embolden foreign governments to circumvent the system by adopting similar, or even more extreme, positions on jurisdiction over data, such as data localization and mandatory encryption backdoor laws. These policies have dangerous consequences for privacy, free expression, and innovation around the world.
While some have written about the data location test in Microsoft Ireland in the abstract, this Note takes a step further and considers its role in the rulings conflicting with Microsoft Ireland that have been issued by federal magistrate judges in the past few months. It also evaluates several recent legislative and non-legislative proposals to solve the problems arising from the data location test. In particular, this Note highlights the pressing need for Congress to reform the Stored Communications Act, incorporating an alternative test for jurisdiction over user data and provisions that would clarify companies’ data disclosure obligations under conflicting legal regimes. Finally, while much of the literature on this topic focuses solely on legislative proposals rather than the real-world impact of the uncertainty creating a need for statutory reform, this Note focuses on what companies should do while they await a resolution from Congress or the Supreme Court. To that end, this Note offers some practical recommendations for how companies can navigate the issues arising from the data location test, particularly as they make decisions about their global operations and data storage architecture.
"Mechanizing Alice: Automating the Subject Matter Eligibility Test of Alice v. CLS Bank" by Ben Dugan
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This article describes a project to mechanize the subject matter eligibility test of Alice v. CLS Bank. The Alice test asks a human to determine whether or not a patent claim is directed to patent-eligible subject matter. The core research question addressed by this article is whether it is possible to automate the Alice test. Is it possible to build a machine that takes a patent claim as input and outputs an indication that the claim passes or fails the Alice test? We show that it is possible to implement just such a machine, by casting the Alice test as a classification problem that is amenable to machine learning.
This article describes the design, development, and applications of a machine classifier that approximates the Alice test. Our machine classifier is a computer program that takes the text of a patent claim as input, and indicates whether or not the claim passes the Alice test. We employ supervised machine learning to construct the classifier. Supervised machine learning is a technique for training a computer program to recognize patterns. Training comprises presenting the program with positive and negative examples, and automatically adjusting associations between particular features in those examples and the desired output.
The examples we use to train our machine classifier are obtained from the United States Patent Office. Within a few months of the Alice decision, examiners at the Patent Office began reviewing claims in patent applications for subject matter compliance under the new framework. Each decision of an examiner is publicly reported in the form of a written office action. We programmatically obtained and reviewed many thousands of these office actions to build a data set that associates patent claims with corresponding eligibility decisions. We then used this dataset to train, test, and validate our machine classifier.
“Just the Facts: Empirically Driven Impact Litigation as a Route to Copyright Reform”