Data Producer's Right and the Protection of Machine-Generated Data

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Data Producer's Right and the Protection of Machine-Generated Data Texas A&M University School of Law Texas A&M Law Scholarship Faculty Scholarship 4-2019 Data Producer's Right and the Protection of Machine-Generated Data Peter K. Yu Texas A&M University School of Law, [email protected] Follow this and additional works at: https://scholarship.law.tamu.edu/facscholar Part of the Intellectual Property Law Commons, and the International Law Commons Recommended Citation Peter K. Yu, Data Producer's Right and the Protection of Machine-Generated Data, 93 Tul. L. Rev. 859 (2019). Available at: https://scholarship.law.tamu.edu/facscholar/1318 This Article is brought to you for free and open access by Texas A&M Law Scholarship. It has been accepted for inclusion in Faculty Scholarship by an authorized administrator of Texas A&M Law Scholarship. For more information, please contact [email protected]. Data Producer's Right and the Protection of Machine-Generated Data Peter K. Yu* I. INTRODUCTION.............................................................................860 II. PAST LESSONS..............................................................................867 A. HistoricalInsights ..................................873 B. CounterfactualInsights ............... ...... 879 II. PRESENTN EEDS ........................................................................... 884 A. TechnologicalNeeds. ................ ........ 888 B. Business Needs. .................. .......... 889 C. Scientific Needs . ....................... .... 892 D. PersonalNeeds ...................... ..... 893 E. Summary. .......................... ...... 895 IV. FUTURE DEVELOPMENTS............................................................. 896 A. Endogenous Complications......... ............. 896 1. Modality of Protection............................................... 898 2. Allocation of Rights...................................................901 3. Duration of Protection...............................................908 4. Scope of Protection....................................................910 5. Limitations and Exceptions.......................................913 B. Exogenous Complications..................... 917 1. Intellectual Property...................................................918 2. Privacy........................................................................920 3. Trade...........................................................................921 4. Investm ent..................................................................923 * 02019 Peter K. Yu. Professor of Law, Professorof Communication, and Director, Center for Law and Intellectual Property, Texas A&M University. Earlier versions of this Article were presented at the 18th Intellectual Property Scholars Conference at the U.C. Berkeley School of Law; the 10th Annual Conference on Innovation and Communications Law at the School of Law, Bocconi University in Milan, Italy; the 7th International Intellectual Property Scholars Roundtable at Duke University School ofLaw*, and the Workshop on 'Legal Implications of the Platform Economy" at the Institute for Civil and Business Law, Vienna University of Economics and Business in Vienna, Austria. The Author would like to thank the participants of these events, in particular Frederick Abbott, Margaret Chon, Brett Frischmann, Justin Hughes, Katja Lindroos Weekstrom, Peter Jaszi, Nicholson Price, Jerome Reichman, and Joshua Sarnoff for valuable comments and suggestions. He is also grateful to Clemens Appl and Philipp Homar for their kind invitation to the Vienna University of Economics and Business and to Bent Hugenholtz for providing a very timely critique that inspired this Article. 859 860 TULANE LA WREVIEW [Vol. 93:859 C. Summary .......... 926 V. PRELMINARY POLICY RECOMMENDATIONS...............................926 V I. CONCLUSION ................................................................................ 929 I. INTRODUCTION Data is the new oil of today's economy--so claim policy makers, commentators, and industry analysts.' In a data-driven economy, there is enormous value in the data generated and collected by humans and machines-both consciously and subconsciously.2 As the European Commission estimated, the value of the European data economy will more than double from E257 billion in 2014 to 6643 billion by 2020. Both the McKinsey Global Institute and the Organisation for Economic Co-Operation and Development have released pioneering studies documenting the many opportunities provided by big data analytics and the emerging data-driven economy.4 The increase in data value, 1. "'Data is the new oil', a phrase that is common currency among leaders in industry, commerce, and politics, is usually attributed to Clive Humby in 2006, the originator of Tesco's customer loyalty card." DAwN E. HOLMEs, BIG DATA: A VERY SHORT INTRoDUCTION 20 (2017); see also VIKTOR MAYER-SCHONBERGER & KENNETH CUKIER, BIG DATA: A REVOLUION THAT WILL TRANSFORM How WE LivE, WORK, AND THINK 16 (2013) (describing data as "the oil of the information economy"); Teresa Scassa, Data Ownership 1 (Ctr. for Int'l Governance Innovation, CIGI Paper No. 187, 2018), https://www.cigionline.org/sites/default/ files/documents/Paper%20no.187_2.pdf ('he commercial value and importance of data is such that they have been referred to as the 'new oil' ... ."); The World's Most Valuable Resource Is No Longer Oil, but Data, EcoNOMIST (May 6, 2017), https://www.economist. com/news/leaders/21721656-data-economy-demands-new-approach-antitrust-rules-worlds- most-valuable-resource (stating that data have "spawn[ed] a lucrative, fast-growing industry [the same way as oil], prompting antitrust regulators to step in to restrain those who control its flow'). See generally ROB KrICHIN, THE DATA REVOLUTION: BIG DATA, OPEN DATA, DATA INFRASTRUCTURES & THEIR CONSEQUENCES (2014) (providing a comprehensive discussion of the data revolution). 2. See Commission Communicationon "Buik ing a EuropeanData Economy," at 4, COM (2017) 9 final (Oct. 1, 2017) [hereinafter Commission Communication]("[Als the data- driven transformation reaches into the economy and society, ever-increasing amounts of data are generated by machines or processes based on emerging technologies, such as the Internet of Things ... ,the factories of the future and autonomous connected systems."). 3. Id at 2. 4. JAMES MANYucA ET AL., McKINSEY GLOB. INST., BIG DATA: THE NEXr FRONTIER FOR INNOVATION, COMPETION, AND PRODUCTIVITY (2011); ORG. FOR EcoN. Co-OPERATION & DEv., DATA-DRIVEN INNOVATION: BIG DATA FOR GROwifH AND WELL-BEING 403-38 (2015). As the report from the McKinsey Global Institute observed. [I]f US health care could use big data creatively and effectively to drive efficiency and quality, we estimate that the potential value from data in the sector could be more than $300 billion in value every year, two-thirds of which would be in the form of reducing national health care expenditures by about 8 percent In the private 2019] DATA PRODUCER'SRIGHT 861 and the attendant explosion of data,s was the result of a confluence of factors-most notably "the rise of 'smart manufacturing', . the economic potential of 'mining' Big Data[,] ... and the promise of the Internet of Things." With the arrival of big data analytics, data have also become highly valuable for uses other than what data producers or collectors initially intended.! Because data can be used alone or in combination with previously nonexistent or inaccessible data,' a considerable part of the value of the generated data now lies in their "option value," not intended value.' In an environment with ubiquitous communication, the prolifeation of Intemet-of-Things devices,'0 and the drastic reduction sector, we estimate, for example, that a retailer using big data to the full has the potential to increase its operating margin by more than 60 percent. MANYIKA E AL., supra, at 2. 5. See HOLMEs, supra note 1, at 1-13'(discussing the data explosion); MAYER- SCHONBERGER & CUKIER, supra note 1, at 70-72 (discussing the transformation brought about by the "data deluge"); Wolfgang Kerber, A New (Intellectual) Property Right for Non- PersonalData?An Economic Analyis, 65 GEwERBaCHERREcKIscHuIzuNDURHEmERREcrT, INTERNATIONALER TEIL [GRURINT] 989, 992 (2016) (Ger.) ('The amount of collected data is increasing exponentially, and it is widely expected that through the spreading of sensor technology and the 'internet of things' this trend will continue for the foreseeable future.'). 6. P. Bernt Hugenholtz, Against 'Data Property,' in 3 KRTrKA: ESSAYS ON INTELLECTUAL PROPERTY 48, 51-52 (Hanns Ullrich et al. eds., 2018). 7. See MAYER-SCHONBERGER & CUIGER, supra note 1, at 153 ("[In a big-data age, most innovative secondary uses haven't been imagined when the data is first collected."); Mark Burdon &Mark Andrejevic, Big Data in the Sensor Society, in BIG DATA Is NOT A MONoLITH 61, 69 (Cassidy R. Sugimoto et al. eds., 2016) (noting that the value in data "is provided by the fact that personal data can be aggregated with that of countless other users (and things) in order to unearth unanticipated but actionable research findings"); Margaret Foster Riley, Big Data, HlIPAA, and the Common Rule: 7me for Big Change?, in BIG DATA, HEALTH LAW, AND BioEDIIcs 251, 251 (L Glenn Cohen et al. eds., 2018) ("The analysis of Big Data related to healthcare is often for a different purpose than the purpose for which the data were originally collected."). 8. See MAYER-SCHONBERGER & CUKIER, supra note 1, at 107 ("Sometimes the dormant value can only be unleashed by combining
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