second-order obviousness: how information and communication technologies make inventions more...

597

Second-Order Obviousness: How Informationand Communication Technologies Make

Inventions More Obvious and Why the LawShould Care

Ryan Whalen

Abstract

Non-obviousness is a key component in how patent law determines thebounds of patentability. However, there are multiple ways that a technol-ogy can be considered “obvious” and current patent doctrine does not con-sider them all. Although all inventions can lead to subsequent inventionsby providing inspiration (first-order obviousness), some have further ef-fects on future innovation by facilitating the associated activities (second-order obviousness). Because of the way they enable communication andinformation access, information and communications technologies (ICTs)like the Internet have particularly strong second-order obviousness effects,as they lower the cost of invention.

This Article introduces the concept of second-order obviousness andtheorizes the relationship between ICTs and innovation. It demonstratesthree mechanisms via which ICTs ease invention and increase obvious-ness: (1) improved access to information; (2) increased ease of collabora-tion; and (3) enhanced accuracy of market monitoring. It then empiricallysupports the presence of these effects as state-level Internet access andpatenting data are used to show that, even when controlling for impor-tant patenting predictors like research and development (R&D) spending,gross domestic product (GDP), and the number of researchers, Internet ac-cess rates are positively and significantly correlated with patenting rates.

After theorizing and supporting the presence of second-order obvious-ness effects, this Article discusses how patent examiners and the courtscurrently take them into account during non-obviousness analysis andsuggests ways to make the analysis more explicit and effective. Sugges-tions include altering the non-obviousness analysis to include a presump-tion to combine prior art references; assessing obviousness from a teamrather than an individual perspective; and paying more attention to themarket demand for inventions. To address future technologies that may

598 Second-Order Obviousness JPTOS

also have second-order obviousness effects, the final Part of this Articlesuggests minor alterations to the text of § 103 and the United State Patentand Trademark Office’s (USPTO’s) technology monitoring that would al-low our innovation system to respond more proactively to changing tech-nological capabilities.

Contents

I. Theorizing the Innovation Environment & Obviousness 600A. The Incentive Justification for Patent Law . . . . . . . . . . . . . 601B. How Patent Law Attempts to Strike a Smart Bargain . . . . . . . 601C. The Innovation Environment . . . . . . . . . . . . . . . . . . . . 602

II. ICTs and Innovation 604A. ICT’s Information-Access Effect on Innovation . . . . . . . . . . 605B. ICT’s Collaboration Effect on Innovation . . . . . . . . . . . . . . 606C. ICTs Effect on Market Transparency . . . . . . . . . . . . . . . . 607

III.Empirically Validating the Relationship between ICTs and Innova-tion 609A. Patent Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 610B. Internet Access Data . . . . . . . . . . . . . . . . . . . . . . . . . 611C. Control Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . 611

1. State GDP . . . . . . . . . . . . . . . . . . . . . . . . . . . 6112. R&D Spending . . . . . . . . . . . . . . . . . . . . . . . . 6123. Science and Engineering PhDs employed . . . . . . . . . 612

D. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 612E. Additional Tests to Support the Existence of an ICT Effect on

Innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6141. Analyzing a Technological Subset . . . . . . . . . . . . . 6152. The Internet and Collaborative Invention . . . . . . . . . 616

IV. How Should Innovation Policy React to Second-Order Obviousness?618A. How the Innovation System May Currently Account for Second-

Order Obviousness . . . . . . . . . . . . . . . . . . . . . . . . . . 6191. The Person Having Ordinary Skill in the Art . . . . . . . 6202. Long Felt but Unmet Need . . . . . . . . . . . . . . . . . 623

B. Updating Non-Obviousness Jury Instructions . . . . . . . . . . . 624C. Future Second-Order Obviousness . . . . . . . . . . . . . . . . . 625

VOL 97, NO 4 Whalen 599

Introduction

We live in arguably the most innovative period in human history.1 One canscarcely glance at the news without reading about the most recent happeningsin technological and scientific progress.2 Every year, more and more inven-tions are patented and brought to market.3 This Article argues that the in-formation and communications technology (ICT) revolution of the past thirtyyears has played a key role in facilitating this innovation explosion. By both in-creasing the amount of information available and making it easier to find andorganize that information, ICTs have made innovation an easier task than ever.In addition to these individual-level effects that make an inventor’s job easier,ICTs have networked society,4 making markets move faster and demand moretransparent.

All inventions have some potential to facilitate future inventions.5 Regard-less of the field, any invention can be improved upon or used as inspiration forfuture developments. However, ICTs remain distinct in that they facilitate fu-ture inventions not only by serving as inspiration, but also by providing func-tionality that eases the inventive process.6 Every invention has one input incommon: information.7 By facilitating work with information, ICTs facilitateall types of invention, regardless of whether they directly relate to informationtechnology.

This Article proceeds in four parts to discuss the facilitating effects thatICTs have on innovation. In Part I, I describe the innovation environment—the social and technological reality within which inventors work to create theirinventions. All inventions have some effect on the innovation environment,each in some way altering the potential for future inventions. However, be-cause of the way they alter our work with information, ICTs have especiallypronounced effects on the innovation environment.

Part II builds upon the theoretical model from Part I by exploring the mech-anisms through which ICTs affect innovation. I show that there are three gen-eral mechanisms by which this phenomenon takes place: (1) ICTs increase ac-

1See The Great Innovation Debate, ECONOMIST (Jan. 12, 2013, 4:11 PM), http://www.economist.com/news/leaders/21569393-fears-innovation-slowing-are-exaggerated-governments-need-help-it-along-great (statingthat “we tend to think of our age as the most innovative ever.”).

2See, e.g., Tech giant Intel backs schoolboy inventor, BBC NEWS (Nov. 5, 2014), http://www.bbc.com/news/technology-29920654 (discussing the invention of an affordable braille printer);Hannah Ellis-Petersen, The future has arrived: the sci-fi inventions that have become reality, THEGUARDIAN (Oct. 21, 2014, 10:30 AM), http://www.theguardian.com/science/2014/oct/21/the-future-has-arrived-the-sci-si-inventions-that-have-become-reality (discussing the invention of a hoverboard); Meghan Gambino, The Smithsonian Celebrates American Invention at This Weekend’s Innovation Fes-tival, SMITHSONIAN.COM (Oct. 30, 2014), http://www.smithsonianmag.com/smithsonian-institution/smithsonian-celebrates-american-invention-weekends-innovation-festival-180953174/?no-ist (announcing anevent where inventors share the stories of their inventions).

3See U.S. PATENT & TRADEMARK OFFICE, U.S. PATENT STATISTICS SUMMARY TABLE CALENDAR YEARS1963 TO 2014 (2014), available at http://www.uspto.gov/web/offices/ac/ ido/oeip/taf/us stat.htm.

4See generally MANUEL CASTELLS, THE RISE OF THE NETWORK SOCIETY (1996).5See infra Part I.C.6See infra Part II.7See Kenneth Arrow, Economic Welfare and the Allocation of Resources for Invention, in THE RATE & DIRECTION

OF INVENTIVE ACTIVITY: ECONOMIC & SOCIAL FACTORS 609, 616 (NBER 1962).


cess to information, enabling invention; (2) they ease the collaboration that isincreasingly central to generating successful inventions; and (3) they improveaccess to market information, allowing innovators to be more responsive andaccurately tailor their inventive activities.

Part III sets out to empirically demonstrate the relationship between ICTsand innovation. I show that, even when we control for important patent pre-dictors like research and development (R&D) funding, gross domestic product(GDP), and the number of researchers at work, higher Internet access rates arerelated to higher patenting rates. In addition, Internet access also leads to morecollaborative inventions and more geographically distant collaborations. PartIV discusses implications, including the importance of reconsidering innova-tion policy with these findings in mind. Suggestions include altering the non-obviousness analysis to include a presumption to combine prior art references,assessing obviousness from a team rather than an individual perspective, andpaying more nuanced attention to the market demand for inventions.

I. Theorizing the Innovation Environment & Obviousness

To obtain a patent, an invention must qualify as novel, useful, and non-obvious.8 While each of these requirements helps determine what qualifies aspatentable, non-obviousness represents the key doctrine that the United StatesPatent and Trademark Office (USPTO) and the courts use to police patentabil-ity boundaries.9 These patentability boundaries help ensure that our innova-tion system provides the appropriate incentives for invention, granting exclu-sive rights only when the underlying invention merits them.

In assessing obviousness, both the USPTO and the courts look to the priorart to determine whether one ordinarily skilled in the art would view the in-vention in question as obvious.10 This Article argues that while this first-orderobviousness—something obvious in relation to previous inventions—is im-portant, courts and the USPTO must also take account of how prior art affectssecond-order obviousness—the way that previous inventions affect the innova-tion process and make some inventions easier to achieve.

This Part will first briefly explain the main theoretical justification forgranting patents and show that obviousness analysis remains a central com-ponent in policing the boundaries of patentability. Next, I will demonstratethe two conceptually different ways that inventions affect the innovation envi-ronment and make future inventions easier, or more obvious: inspiration effectsand functional effects.

835 U.S.C. §§ 101–103 (2012).9Christopher A. Cotropia, Nonobviousness and the Federal Circuit: An Empirical Analysis of Recent Case Law, 82

NOTRE DAME L. REV. 911, 912 (2007) (“The nonobviousness requirement plays a critical role in United Statespatent law.”).

1035 U.S.C. § 103 (2012); MPEP § 2141 (9th ed. Rev.7, March 2014).


A. The Incentive Justification for Patent Law

Patent law is often characterized as a quid pro quo, with the public trading thegrant of exclusive rights to practice an invention for the eventual return of thatinvention to the public domain.11 This quid pro quo conception of patents hasroots in the incentive justification for patent law, which itself stems from theProgress Clause of the constitution.12 The story here goes that to “promote theprogress of science and the useful arts,”13 the exclusive rights associated withpatents are a necessary incentive.

As patent law provides incentives for innovation, it follows that provid-ing appropriate incentives is one of the most important elements of the patentsystem.14 When the public grants exclusive rights so that it can incentivizeinnovation, it ideally would like to optimize those incentives so that rightsare granted only for innovations that would not otherwise have occurred in atimely fashion. In other words, in striking a bargain with inventors, the publicshould strive to strike a savvy deal, giving up only what is required to acquirethe benefit of the bargain.

To strike a savvy deal, the public—via the USPTO and the courts—musthave some sense of the costs that the alternate party—inventors and theiremployers—incur. The bargain requires reassessment if and when those costschange.

B. How Patent Law Attempts to Strike a Smart Bargain

Utility, novelty, and non-obviousness are the three principle requirements forpatentability.15 While utility and novelty play some role in policing the boundsof the incentives granted to inventors, the non-obviousness requirement com-pletes the lion’s share of the work.16 Utility and novelty act as threshold re-quirements in that the public does not wish to grant exclusive rights over use-less or already known inventions. Non-obviousness on the other hand is morenuanced in its tailoring of when a grant of exclusive rights is appropriate.

Non-obviousness is also the most flexible of the three patentability require-ments.17 This flexibility arises because non-obviousness requires analysis via

11See generally Jacob Adam Schroeder, Written Description: Protecting the Quid Pro Quo Since 1793, 21 FORDHAMINTELL. PROP. MEDIA & ENT. L.J. 63 (2011).

12See U.S. Const. art. I, § 8, cl. 8.13Id. The incentive theory does not serve as the sole theoretical justification for patent law, but does serve as

one most commonly referred to by courts and one of the most generally familiar. See, e.g., Mayo v. Prometheus,132 S. Ct. 1289, 1305 (Sup. Ct. 2012) (stating that “the promise of exclusive rights provides monetary incentivesthat lead to creation, invention, and discovery.”); see also Roberto Mazzoleni & Richard R. Nelson, EconomicTheories about the Benefits and Costs of Patents, J. OF ECONOMIC ISSUES 1031, 1032–33 (1998) (highlighting thefamiliarity of that the “incentive motivation” theory and noting three additional justifications for patent law:disclosure, commercialization, and exploration).

14For discussion on the difficulty of designing appropriate patent incentives see Suzanne Scotchmer, Standingon the Shoulders of Giants: Cumulative Research and the Patent Law, 5 THE J. OF ECON. PERSP. 29, 37 (1991) (“Thereare no simple conclusions to draw about the optimal breadth of patents.”).

1535 U.S.C. §§ 101–103 (2012).16Cotropia, supra note 9, at 912 (discussing the central importance of non-obviousness to a functioning patent

system).17KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415 (2007) (stating that Supreme Court precedent set out an


a multi-factor test that courts can tailor to specific scenarios. The “Grahamfactors” take into account (1) the scope and content of the prior art; (2) thelevel of ordinary skill in the art; (3) the uniqueness the invention; and (4) ob-vious evidence of non-obviousness.18 Courts also take into account so-called“secondary considerations” of non-obviousness including whether there was along-felt need for the invention, commercial success, failure of others to perfectthe invention, copying of the invention by others, and whether the inventionstemmed from unexpected results.19

The state of the prior art plays a central role in the non-obviousness analy-sis. In assessing the obviousness of an invention, the USPTO asks whether “thedifferences between the claimed invention and the prior art are such that theclaimed invention as a whole would have been obvious . . . .”20 The USPTOtends to focus on prior art in the nature of previous inventions—patent grantsor applications—or publications such as journal articles.21 To determine whatprior art qualifies as relevant to the invention, the patent examiner performs asearch that covers “the claimed subject matter and . . . also cover the disclosedfeatures which might reasonably be expected to be claimed.”22 In other words,the prior art search is a sort of similarity search, where examiners look for previ-ous inventions or publications that might share similarities with the inventionin question and thus imply the obviousness of the invention. The prior artsearch does not encompass previous inventions or developments that, despitesharing no functional similarities with the invention in question, may havemade the invention easier to achieve. The following section will argue thatthe USPTO and the courts should remain cognizant of this sort of non-similarprior art because it too can affect the innovation environment and alter theincentives necessary to ensure a healthy innovation policy quid pro quo.

C. The Innovation Environment

Conceiving of the world of invention and inventors as an innovation environ-ment can help to illuminate the different types of prior art and the way theycan affect innovation.23 Inventions can alter the innovation environment andmake subsequent inventions more obvious.

There are two mechanisms by which inventions alter the innovation en-vironment in ways that beget future inventions: (1) they provide inspiration

“expansive and flexible approach” to the obviousness question).18Graham v. John Deere Co. of Kan. City, 383 U.S. 1, 17 (1966); see Allen Archery Inc., v. Browning Mfg. Co.

819 F.2d 1087, 1092 (Fed. Cir. 1987) (discussing the validity of using secondary considerations as a demonstrationof non-obviousness).

19Graham, 383 U.S. at 17–18.20MPEP § 2141 (9th ed. Rev.7, March 2014).21See id. § 904.22Id. § 2141(II)(A)(1); see id. §§ 904.02, 904.01(c) (describing the prior art search process and stating that the

search should include a search of analogous technology classes).23There is a long tradition of conceiving of the knowledge underlying science and engineering as an envi-

ronment or space. See, e.g., Richard M. Shiffrin & Katy Borner, Mapping Knowledge Domains, 101 PROC. NAT’LACAD. SCI. 5183, 5183 (2004) (describing the evolution of mapping knowledge); Lee Fleming and Olav Soren-son, Science as a Map in Technological Search, 25 STRATEGIC MGMT. J. 909, 910 (2004) (conceptualizing science asa recombinatorial search through multidimensional space).


that future inventors build upon;24 and (2) they provide functionality useful tothe inventive process.25 All inventors to one degree or another have the firstof these effects. Every invention results in information that may prove usefulto future inventors. Patent examiners look for this type of useful informationwhen they conduct a prior art search. On the other hand, not all inventionshave the second of these effects, and those that do have it to varying degrees.

For instance, the discovery of the antibacterial properties of penicillin26

eventually led to a family of new drug inventions and treatment possibilities.27

This discovery provides an example of the first type of effect, an inspirationeffect, that inventions have on the innovation environment. The similaritiesbetween these drugs and treatments would have been relevant prior art in afirst-order obviousness analysis.

On the other hand, consider the invention of something like the scanningelectron microscope (SEM).28 This groundbreaking invention undoubtedly in-spired future inventions related to microscopes.29 However, the invention alsohad a functional effect enabling previously impossible research; research thatled to many new inventions.30 However, these functionally-related inventionsenabled by the SEM would not have cited the SEM as prior art. In fact the SEMwould not have necessarily played an explicit role in any of the relevant patentapplications. After all, with no similarity between the two inventions, patentprocedures do not require examiners to explicitly take this type of functionaleffect on obviousness into account.

To extend the innovation environment analogy further, one can think of theinspiration effects that inventions have as additions to a map of the innovationenvironment. In the same way that penicillin’s discovery revealed a new fieldof research, inspiration effects show new areas to explore. As future inventorsexplore these areas, they will sometimes make significant discoveries.

On the other hand, functional effects enable exploration and movementthrough the environment. The invention of a new microscope shares simi-

24This represents the idea of “cumulative innovation” where one invention leads to subsequent related in-ventions. See generally Fiona Murray & Siobhan O’Mahony, Exploring the Foundations of Cumulative Innovation:Implications for Organization Science, 18 ORG. SCI. 1006 (2007).

25This is similar to the notion of “technology affordances,” which stand for the proposition that people per-ceive of technologies by how they allow interaction with the environment. See William W. Gaver, TechnologyAffordances, PROC. OF THE SIGCHI CONFERENCE ON HUM. FACTORS IN COMPUTING SYSTEMS 79, 79 (ACM1991).

26See generally Alexander Fleming, On the Antibacterial Action of Cultures of a Penicillium, with Special Referenceto Their Use in the Isolation of B. Influenzae, 10 BRIT. J. OF EXPERIMENTAL PATHOLOGY 226 (1929).

27See Selman A. Waksman, Antagonistic Relations of Microorganisms, 5 BACTERIOLOGICAL REVIEWS 231, 235–37(1941) (showing an early example of usage of the word antibiotic and results of research that would eventuallylead Waksman to receive the Nobel prize); see also Selman A. Waksman - Biographical, NOBLEPRIZE.ORG, http://www.nobelprize.org/nobel prizes/medicine/laureates/1952/waksman-bio.html (last visited Oct. 25, 2015).

28Electron Scanning Microscope, U.S. Patent No. 2,241,432 (filed Sept. 7, 1938) (issued May 13 1941).29See the many patents that directly or indirectly cite the Von Ardenne and Von Borries patent as prior art.

See, e.g., U.S. Patent No. 2,527,562 (filed Aug. 2, 1945) (issued Oct. 31, 1950); U.S. Patent No. 2,680,669(filed Nov.26, 1947) (issued June 8, 1954); U.S. Patent No. 2,932,549 (filed Nov. 20, 1953)(issued Apr. 12 1960); U.S. PatentNo. 7,474,730 (filed Oct. 17, 2006) (issued Jan. 6, 2009).

30See, Practical uses for the SEM, AUSTRALIAN MICROSCOPY & MICROANALYSIS RESEARCH FACILITY, http://www.ammrf.org.au/myscope/sem/background/practical/practical/#prettyPhoto (last visited Oct. 25, 2015)(describing uses for scanning electron microscopes including medical research, forensic science, materials sci-ence, biology and geology).


larities with the introduction of a new vehicle or navigation system that betterenables inventors to explore the innovation environment, regardless of whatinspired the inventors to research their specific fields.

The transportation and navigation aids that help inventors explore the in-novation environment can have important effects on the balance we try tostrike within innovation policy. New technologies that alter the ease of subse-quent invention effectively make many inventions more obvious than they hadpreviously been. This obviousness may not derive from first-order similarityeffects but rather from the technology’s second-order functionality effects.

The term “obvious” means to be “[e]asily discovered, seen, or understood;readily perceived by the eye or the intellect; plain; patent; apparent; evident;clear; [or] manifest.”31 Traditional non-obviousness analysis asks whether—given the information contained in the relevant prior art and its similarity tothe invention in question—an invention possesses easy discoverability.32 Un-like traditional first-order obviousness, second-order obviousness effects donot arise from this sort of similarity. Rather, second-order obviousness ariseswhen the functions of an invention make something easier to discover.

I argue that, to ensure the continued effectiveness of and balance withininnovation policy, policymakers and adjudicators like the USPTO need to beaware of these second-order effects and understand how they play into the ob-viousness analysis. However, before moving on to an empirical exploration ofsecond-order obviousness effects and their implications for innovation policy,the functional effects that ICTs have on the innovation environment requiresfurther examination. This will help demonstrate the mechanisms throughwhich second-order obviousness can ease invention.

II. ICTs and Innovation

No group of technologies has more changed the innovation environment overthe past few decades than ICTs. These technologies have had inspiration ef-fects that have expanded the map of the innovation environment, leading toinventions in research fields that previously did not exist.33 However, muchof the transformation has taken place via the functional effects that ICTs havehad on the way inventors engage in research and development work.34 Thesefunctional effects have reduced invention costs in many technology areas, ef-fectively making many types of invention more obvious than they would oth-erwise have been.

Information technologies reduce invention costs in at least three ways:(1) they improve access to information, increasing the odds that inventors

31BLACK’S LAW DICTIONARY 1078 (6th ed. 1990).32See MPEP § 2141 (9th ed. Rev. 7, March 2014).33See, e.g., James Bessen & Robert M. Hunt, An Empirical Look at Software Patents, 16 J. OF ECON. & MGMT.

STRATEGY 157, 157–59 (2007) (noting the rapid growth of software patents in recent years).34See Samuel Kortum & Josh Lerner, What is Behind the Recent Surge in Patenting?, 28 RES. POLICY 1, 2–4 (1999)

(showing a large scale increase in patenting activity and arguing that much of the growth has occurred due torecent changes in the innovation process).


will find relevant inspiration—an information-access effect; (2) they ease col-laboration, enabling teams to work together and build upon one another’sstrengths—a collaboration effect; and (3) they enable better measurement of mar-ket demands—a market transparency effect. This Section will discuss each ofthese in turn.

A. ICT’s Information-Access Effect on Innovation

Information is an essential component in the innovation process.35 When in-ventors create a new invention, they invariably rely on humanity’s store ofknowledge, drawing inspiration from prior art and recombining it into newcreations. Some of that knowledge will be readily available as the tacit knowl-edge within a given discipline.36 Other knowledge will be codified in refer-ences, publications, and patents37 providing inventors with guidance and in-spiration. Regardless of where the knowledge resides, few, if any, inventorsdo not rely on the knowledge of those that preceded them.38

The patent law system is structured on the premise that information playsa vitally important role in innovation. In exchange for disclosing the infor-mation necessary to replicate an invention, the law grants the inventor a tem-porary monopoly.39 This bargain that the public strikes with inventors restupon an implicit assumption: that future researchers and inventors will havethe ability to build upon the work of their predecessors to develop new andimproved inventions.40 Many courts and scholars consider this informationdisclosure function one of the patent system’s most important justifications.41

Information is not only an essential input for innovation, it is also the pri-mary output.42 When the USPTO grants a patent, it grants rights not to a phys-ical good, but to information. When an inventor obtains a patent, she does notgain rights over any particular machine, device or property, but rather gainsthe right to control the underlying know-how that constitutes her contributionto knowledge. This unique trait of the innovation process, where informationis both the primary input and the primary output, creates a feedback loop. If

35See Paul M. Romer, Endogenous Technological Change, J. OF POL. ECON. S71, S79 (1990) (explaining that theexisting stock of knowledge is a principal component in the creation of new knowledge).

36See Kaj U. Koskinen & Hannu Vanharanta, The Role of Tacit Knowledge in Innovation Processes of Small Technol-ogy Companies, 80 INT’L J. OF PRODUCTION ECON. 57, 63 (2002) (highlighting the utility of tacit knowledge inthe innovation process).

37See Dan L. Burk, The Role of Patent Law in Knowledge Codification, 23 BERKELEY TECH. L.J. 1009, 1012 (2008)(explaining the role patents play in codifying knowledge).

38See generally Scotchmer, supra note 14.39See Bonito Boats, Inc. v. Thundercraft Boats, Inc., 489 U.S. 141, 150–51 (1989) (stating that “the federal patent

system thus embodies a carefully crafted bargain for encouraging the creation and disclosure of new, useful,and nonobvious advances in technology and design in return for the exclusive right to practice the invention fora period of years.”).

40For this reason, common law has long allowed for a research-use defense to patent infringement. See Madeyv. Duke University, 307 F.3d 1351, 1361–62 (Fed. Cir. 2002) (noting the existence of the research exemption whilelimiting its scope).

41See Bonito Boats, 489 U.S. at 150–51; Kewanee Oil Co. v. Bicron Corp., 416 U.S. 470, 480–81 (1974); see alsoJeanne C. Fromer, Patient Disclosure, 94 IOWA L. REV. 539, 541 (2008). But see Alan Devlin, The MisunderstoodFunction of Disclosure in Patent Law, 23 HARV. J.L. & TECH. 401, 401–06 (2010) (arguing that the disclosurefunction does not serve as important a function as many assume).

42Arrow, supra note 7, at 616.


information begets innovation, and innovation begets information, then inno-vation begets innovation.

Information technologies compound this information–innovation feedbackloop. The invention of ICTs not only adds to the total stock of informationin the manner of any invention, but it also facilitates work with information,thereby strengthening the signal in the feedback loop. This information effect isthe first of the three principle ways that ICTs affect innovation, and ultimatelygive rise to second-order obviousness.

Because information is an essential input in the innovation process, it haslong been popular to associate changes in ICTs with changes in the innova-tive process.43 These arguments are intuitively attractive. For example, it isobvious that the invention of the printing press allowed for greater dissemi-nation of knowledge and thereby more widespread innovation.44 However,despite their intuitive appeal, these effects have long been difficult to empiri-cally demonstrate. While many would agree that the telegraph probably hadsome effect on the speed of future inventions, there is insufficient data to provethis assertion and determine the effect size. Furthermore, possibly becausethese effects have proven difficult to validate and measure, neither the courtsnor Congress have taken them into account when interpreting and designingpatent law. In Part III, this Article will empirically support the relationshipbetween ICT access and increased innovation. However, the remaining twomechanisms by which ICTs create second-order obviousness effects requirefurther analysis.

B. ICT’s Collaboration Effect on InnovationIn addition to the information effect that ICTs have on innovation, they alsoplay a related but distinct role in innovation by facilitating collaboration be-tween innovators.45 Much of the folk wisdom surrounding the way inno-vation occurs would suggest that inventors tend to do their inventing whilesequestered away in laboratories, slaving away in isolated research and de-velopment.46 Closer investigation, however, demonstrates that invention is asocial practice,47 and that inventors embed themselves in communities of col-

43See generally HAROLD A. INNIS, EMPIRE AND COMMUNICATIONS (1972); NEIL POSTMAN, TECHNOPOLY:THE SURRENDER OF CULTURE TO TECHNOLOGY (1993); Boyan Jovanovic & Rafael Rob, The Growth and Diffusionof Knowledge, 56 THE REV. OF ECON. STUD. 569, 571, n.2 (1989).

44See Jovanovic & Rob, supra note 43, at 571 (“The invention of the printing press, telephone, mathematics andso on, have all made communication easier and more precise. These inventions may well be largely responsiblefor the sustained growth the world has experience in recent times.”); see generally ELIZABETH L. EISENSTEIN,THE PRINTING PRESS AS AN AGENT OF CHANGE: COMMUNICATIONS AND CULTURAL TRANSFORMATIONS INEARLY-MODERN EUROPE (1980).

45In truth, this effect could be characterized as an information effect, because collaboration relies on the ex-change of ideas and information. However, it remains useful to distinguish the communication functions ofinformation and communication technologies because of the importance of collaboration to modern innovationpractices.

46See Jasjit Singh & Lee Fleming, Lone Inventors as Sources of Breakthroughs: Myth or Reality?, 56 MGMT. SCI. 41,41 (2010) (noting the history of famous inventors extolling the virtues of lone inventors); Mark A. Lemley, TheMyth of the Sole Inventor, 110 MICH. L. REV. 709, 710 (2012) (explaining the inherent sole-inventor bias in patentlaw.

47Lemley, supra note 46, at 710–12.


laborators and competitors.48 Moreover, not only is collaboration increasinglycommon in research and development, but it also leads to higher-quality in-ventions.49

As with other forms of organizational and interpersonal communications,ICTs have increased and accelerated the channels for the communication andcollaboration that takes place in research and development projects.50 As com-munication becomes faster and easier, collaboration will become more effi-cient, which in turn will increase the rate of innovation as ideas are sharedand improved upon more quickly.

To illustrate this phenomenon it is useful to imagine how ICTs have af-fected collaboration, resulting in faster, easier, and more efficient collabora-tive innovation. E-mail provides a useful example, showing how instant writ-ten communication has the potential to accelerate collaboration, especially forteams that are not co-located.51 By allowing collaborators to instantly com-municate with one another essentially for free and share results, images, anddocuments, e-mail demonstrates the paradigm shift that ICTs have had on col-laborative communication. Prior to e-mail’s availability, collaborators neededto share physical documents, relying on the postal service, couriers, and even-tually fax machines to communicate with one another.

This collaboration effect is the second of the three effects that ICTs have onthe innovation process. With collaboration playing the central role that it nowdoes in producing inventions,52 any technological improvements that makecollaborating easier, will also make inventing easier.

C. ICTs Effect on Market Transparency

Along with improving our ability to work with information and collaborate,ICTs also make markets more transparent. Information technology allows forfaster and more accurate access to market information.53 This improved access

48Laura G. Pedraza-Farina, Patent Law and the Sociology of Innovation, 2013 WIS. L. REV. 813, 838–39 (2013)(describing scientific “communities of practice.”).

49Stefan Wuchty et al., The Increasing Dominance of Teams in Production of Knowledge, 316 SCI. 1036, 1037–38(2007) (showing that patents by teams of inventors have greater impact than those by solo inventors); see alsoSingh & Fleming, supra note 46, at 55.

50See Jorge Schrottke & Thomas Weber, The End of the Great-Man Theory of Innova-tion, BUSINESSWEEK.COM (July 10, 2013) http://www.businessweek.com/articles/2013-07-10/the-end-of-the-great-man-theory-of-innovation (noting a shift in management styles towards increasedcollaborative research and development); see generally Samer Faraj et al., Knowledge Collaboration in OnlineCommunities, 22 ORG. SCI. 1224 (2011).

51See Donald Beaver, Reflections on Scientific Collaboration (and Its Study): Past, Present, and Future, 52 SCIEN-TOMETRICS 365, 375 (2001) (stating that “research is nearly impossible” without e-mail). E-mail is only oneexample of how ICTs have transformed work. There are many other examples of how ICTs have eased col-laboration, and there is in fact a whole field of collaborative software or “groupware” development, focusedon developing platforms to enable more effective collaborative work. See Collaborative software, WIKIPEDIA,http://en.wikipedia.org/wiki/Collaborative software (last visited Oct 25, 2015).

52See Wuchty et al., supra note 49, at 1037–38 (showing that all fields of science, social science, and patentinghave seen increasing collaboration rates in recent decades).

53See Nelson F. Granados et al., The Impact of IT on Market Information and Transparency: A Unified TheoreticalFramework, 7 J. OF THE ASS’N FOR INFO. SYSTEMS 148–49 (2006).


to market information in turn enables more successful innovation.54

Companies and inventors can now more easily probe the market to mea-sure demand for potential inventions, and get feedback on works in develop-ment.55 In addition, the rise of big data and customer tracking suggests thatthis market transparency effect will only become stronger in the near future.56

As more and more firms track consumption patterns and as methods and toolsfor analyzing these vast stores of data become more sophisticated, the demandfor potential inventions becomes more transparent.

With more transparent demand one can expect to see more efficient innova-tion. Companies will gain the ability to more accurately tailor their inventiveactivities toward successful developments with a higher potential for success.In theory this should lead to more inventions to fill these demands and morepatents to cover them.

This market transparency effect is the third of the three ICT effects on the in-novation process. The magnitude of this effect will vary based on the typeof innovation in question because ICTs will make some markets more trans-parent than others. For instance, software development firms can easily tracksoftware consumption behavior and then incorporate lessons learned from thereal-world use of their products into future developments.57 Other, less-fully-wired, products are not affected to the same degree. For instance, demand fornew drugs or medical treatments are not made more transparent by improve-ments in ICTs. Robust public health statistics have existed for a long time.58

While the rise of the Internet may have made it somewhat easier for medicalresearch and development firms to measure market demand, they have notexperienced the transformative changes that other firms have.

In addition, ICTs make markets transparent not only by allowing directtracking of consumer product use and demand, but also by producing vastrecords of human behavior and the technologies required to analyze theselarge datasets. These records of human behavior come from many sources,

54See Brian D. Ottum & William L. Moore, The Role of Market Information in New Product Success/Failure, 14 J.OF PRODUCT INNOVATION MGMT. 258, 265–66 (1997) (showing that the ability to process market informationis positively correlated with a firm’s new product success). From an innovation theory perspective, this issimilar to the role that market knowledge plays in Nelson’s model of the role of knowledge in research anddevelopment. See Richard R. Nelson, The Role of Knowledge in R&D Efficiency, 97 THE Q. J. OF ECON. 453,460 (1982) (“A stronger knowledge base not only enhances the general productivity of search. It increases thesensitivity of search to the fine structure of market situation.”).

55Robert F. Lusch et al., The Phase Transition of Markets and Organizations: The New Intelligence and EntrepreneurialFrontier, 21 IEEE INTELLIGENT SYSTEMS 5, 6 (describing modern markets as a conversation between actorsincluding firms and consumers).

56See Howard Baldwin, When Big Data Projects Go Right, FORBES (Feb. 2, 2015, 11:22 AM), http://www.forbes.com/sites/howardbaldwin/2015/02/02/when-big-data-projects-go-right/(describing the rise of bigdata driven marketing).

57Use tracking has become quite common, where nowadays much software prompts the user on installationto opt-in to tracking, while others include use tracking as a mandatory part of the terms of use in which usersmust agree. See David M. Martin et al., The Privacy Practices of Web Browser Extensions, 44 COMM. OF THE ACM45, 45 (2001) (explaining the free-to-use provided users allow tracking business model); On the enforceability ofclickwrap agreements, see Feldman v. Google, Inc., 513 F. Supp. 2d 229, 235–38 (E.D.Pa. 2007); ProCD, Inc. v.Zeidenberg, 86 F.3d 1447, 1452 (7th Cir. 1996).

58See generally CDC, NATIONAL CENTER FOR HEALTH STATISTICS, 1960-2010, CELEBRATING 50 YEARS(2010), available at http://stacks.cdc.gov/view/cdc/23174.


including Internet clickstream data,59 social media services,60 and online shop-ping records.61 Data mining uses ever-more-powerful computers62 and ever-more-sophisticated algorithms63 to analyze this data and extract useful marketinformation. This makes the market more transparent for innovators and re-duces the cost of innovation by allowing them to more accurately tailor theirresearch and development activities to meet precise market demand.

* * *

The above has theorized how inventions affect the innovation environ-ment. Arguing that any given invention can have two types of effect on theinnovation environment—inspiration effects, or functional effects—one can seethat ICTs have especially potent functional effects on the innovation environ-ment. They supplement inventors’ inventive abilities by enabling work withinformation, communication, and collaboration. By doing so, ICTs effectivelylower the cost of innovation, making many types of invention more obviousthan they were previously. A lowered cost for innovation should lead to an in-crease in inventions and patents granted. To support the above assertions, thenext section of this Article will empirically support the relationship betweenICT access and innovation.

III. Empirically Validating the Relationship between ICTsand Innovation

The above analysis has provided a variety of theoretical explanations of theways in which improvements in ICTs may lead to lower cost invention.64 Bymaking information, the primary input in the innovation process, more read-ily available, ICTs lower research costs and increase the chance that inventorswill find inspiration for their inventions.65 Similarly, by enabling more effec-tive collaboration, ICT improvements facilitate teamwork critical to modern

59Alan L. Montgomery et al., Modeling Online Browsing and Path Analysis Using Clickstream Data, 23 MKTG. SCI.579, 579 (2004) (explaining that website use monitoring provides “a new facet to predicting consumer behavior. . . .”).

60Daniel Zeng et al., Social Media Analytics and Intelligence, 25 IEEE INTELLIGENT SYSTEMS 13, 14 (2010) (“For-profit businesses are tapping into social media as both a rich source of information and a business-executionplatform for product design and innovation, consumer and stakeholder relations management, and marketing.For them, social media is an essential component of the next-generation business intelligence platform.”).

61Cesar Astudillo et al., Editorial: Data Mining in Electronic Commerce-Support vs. Confidence, 9 J. OF THEO-RETICAL & APPLIED ELECTRONIC COM. RES. I, I (2014) (“In recent years with the rapid growth of electroniccommerce and the large amounts of data collected through operational transactions, data mining techniques arebecoming more useful to discover and understand unknown customer patterns.”).

62Moore’s law, stating that computational power will double every one-to-two years, has demonstrated rela-tive accuracy over the past four decades. See Ethan Mollick, Establishing Moore’s Law, 28 IEEE ANNALS OF THEHIST. OF COMPUTING 62, 62 (2006).

63For an overview of data mining algorithms see Xindong Wu et al., Top 10 Algorithms in Data Mining, 14KNOWLEDGE & INFO. SYSTEMS 1 (2008).

64See supra Part I.65See supra Part I.A.


research66 and generate more innovation.67 In addition, ICT improvementshave allowed firms to more accurately measure, and thus more quickly re-spond to, market demand for innovation.68 However, ultimately these expla-nations of how ICTs affect the innovative process are theoretical conjecture.Without some empirical demonstration that a relationship between ICT accessand innovation exists, it will remain difficult to determine how, or even if, thelaw should respond.

Measuring both access to ICTs and the number of patents granted can helpto determine whether ICTs have a significant effect on the innovative process.If the above discussion correctly suggests that ICTs decrease the cost of inven-tion, we should see increased rates of patenting in areas where greater accessto information technology exists.

Measures of access to discrete information technologies remain difficult toprocure, but there are relatively reliable measurements of Internet access ratesacross the United States.69 By focusing on the rate of Internet access over timeand its relationship to the number of patents granted to inventors within eachstate, one can test whether a relationship between ICTs and greater innovationexists.

The below analysis uses a panel regression model to test the hypothesisthat Internet access relates to an increase in patenting behavior. The modelincludes state-level annual patent grants per 1000 people as the dependentvariable, and Internet access rates as the independent variable. The full modelalso includes a number of control variables, such as federal research and de-velopment spending per capita, private research and development spendingper capita, the per capita number of science and engineering PhDs working instate, and state GDP per capita. The regression was performed using a within-subjects fixed-effects model.70

A. Patent Data

Patent data from the year 1994 and later was used to calculate the number ofpatents granted per state per year. This data has disambiguated individualinventors and where available has included data on their home state.71 Theannual number of patents granted per 1000 individuals in the state populationis the dependent variable used in the final model. State population numbersfor this and other per capita measures were taken from population estimatesprovided by the United States Census Bureau (Census).72

66Wuchty et al., supra note 49, at 1037–38; see, e.g., Toshio Murase et al., Teams Are Changing: Time to “ThinkNetworks,” 5 INDUS. & ORGANIZATIONAL PSYCHOL. 41 (2012).

67See supra Part I.B.68See supra Part I.C.69See supra Part II.B.70For more information on panel regression and the software used see generally Yves Croissant & Giovanni

Millo, Panel Data Econometrics in R: The Plm Package, 27 J. OF STAT. SOFTWARE 1 (2008).71See Ronald Lai et al., Disambiguation and Co-Authorship Networks of the US Patent Inventor Database, 2138

HARV. INST. FOR QUANTITATIVE SOC. SCI.,941 (2011). In the referenced article, where a patent listed inventorsfrom more than one state, each state was credited with that invention.

72Population Estimates, U.S. CENSUS BUREAU, http://www.census.gov/popest/ (last visited Oct. 25, 2015).


B. Internet Access DataThe United States Census Computer and Internet Use survey was used to de-termine Internet access rates for each state.73 Unfortunately, the Census doesnot perform the Internet use survey every year. The Census started the sur-vey in 1994. Internet use questions were again asked in 1997, 1998, 2000, 2001,2003, 2007, and 2009. Respondents who answered affirmatively when askedif they had Internet access at home were counted as “yes” respondents. In1994 the survey did not explicitly ask whether respondents had Internet ac-cess at home, but rather asked a series of questions about whether the homecomputer was used for a variety of online activities, such as for sending e-mailor shopping.74 If respondents answered yes to any of these questions, theywere counted as having Internet access at home. These data were then used tocalculate a simple rate of Internet access for each state for each surveyed year.

C. Control VariablesExamining the relationship between Internet access and patenting can showwhether the two are correlated with one another.75 However, there are manypotential confounding factors that could also explain why patenting might in-crease in a jurisdiction concurrently with a growth in its Internet access rate. Toensure that the model accurately measures the relationship between Internetaccess and patenting, it must control for as many of these potential confound-ing factors as possible.

1. State GDP

Regional wealth is of the most obvious factors that might relate to both Internetaccess and patenting. As a state’s GDP rises, one would expect to see both anincrease in patenting76 and an increase in Internet access.77 Therefore, anymodel attempting to measure the effect that Internet access has on patentingmust include controls for the per capita GDP of each state.

To do so, state GDPs were taken from the Bureau of Economic AnalysisRegional Data collection,78 and per capita GDP was subsequently computedusing the census state population estimates.79 These were standardized to 2012dollars using conversion factors from the Bureau of Labor Statistics ConsumerPrice Index data.80

73Computer and Internet Use, U.S. CENSUS BUREAU, http://www.census.gov/hhes/computer/ (last visitedOct. 25, 2015).

74Id.75Indeed the two have a strong correlation. See infra Part III.D.76See Iftekhar Hasan & Christopher L. Tucci, The Innovation–Economic Growth Nexus: Global Evidence, 39 RES.

POL’Y 1264, 1267 (2010) (showing a significant and positive correlation between GDP and R&D effectiveness).77See Sampsa Kiiski & Matti Pohjola, Cross-Country Diffusion of the Internet, 14 INFO. ECON. & POL’Y 297,

308–9 (2002) (showing that GDP per capita is an important predictor of Internet usage rates).78Regional Data, BUREAU OF ECON. ANALYSIS, http://bea.gov/iTable/iTable.cfm?reqid=70&step=1&isuri=

1&acrdn=1#reqid=70&step=1&isuri=1 (last visited Oct. 25, 2015).79Population Estimates, supra note 72.80CPI Res. Series Using Current Methods, BUREAU OF LABOR STATISTICS, http://www.bls.gov/cpi/cpirsdc.

htm (last visited Oct. 25, 2015).


2. R&D Spending

Along with raw GDP counts, one can also control for direct spending on R&D.As R&D spending increases we would expect to see a concomitant increase inpatents granted.81 Thus, to accurately measure the effect that Internet accesshas on patenting, one needs to hold R&D spending constant. As such, the fullmodel includes two R&D control variables.

Both R&D spending variables rely on data from the National Center for Sci-ence and Engineering Statistics (NCSES).82 The first R&D expenditure variablerepresents federal R&D spending per capita. The second represents businessR&D expenditure per capita. Each of these is calculated for each state. TheNCSES had missing data for some years, such as in 2009 when federal R&Dfunding data was not available. In these instances, the trend from the previousyear was projected one year forward to impute the missing data.83

3. Science and Engineering PhDs employed

Along with GDP and R&D expenditure, we would expect the number of re-searchers working in in any given state to be significantly related to the num-ber of patents granted to inventors there.84 While it remains difficult to obtainexact measures of the number of inventors who work in a state, one can use theNCSES data on the number of Science and Engineering PhDs working in eachstate85 to at least partially control for the number of researchers. The assump-tion here is that an increased number of researchers in a state will presumablylead to a greater rate of patenting. Controlling for these PhD holders helpsthe model to account for this and estimate any independent effect that Internetaccess may have.

D. Results

Internet access grew remarkably quickly in the late 1990s and early 2000s. Fig-ure 1 shows the mean level of Internet access by state for the years where datawas available. At the same time, a marked increase in the rate of patent grant-ing occurred. Figure 2 graphs the mean number of patents granted per 1000people.86 Taken together, these two graphs suggest that these two phenomenaare at the least strongly collinear.

81Jinyoung Kim & Gerald Marschke, Accounting for the recent surge in U.S. patenting: changes in R&D expendi-tures, patent yields, and the high tech sector, 13 ECON. OF INNOVATION & NEW TECH. 543 (2004).

82NCSES Data, NAT’L SCI. FOUND., http://www.nsf.gov/statistics/data.cfm (last visited Oct. 25, 2015).83For example, to impute the 2009 Federal R&D spending, the rate of change from 2007 to 2008 was assumed

constant from 2008 to 2009 and values for 2009 were computed accordingly.84While a facially valid supposition, evidence exists that, at least until the recent patenting boom, growth in

the number of researchers did not lead to growth in the number of patents granted. Samuel S. Kortum, Research,Patenting, and Technological Change, 65 ECONOMETRICA 1389, 1391 (1997).

85NCSES Data, supra note 82.86The means for both Internet access rates and patents granted graphed here are the between-state means

rather than the national mean.


Figure 1

Figure 2

The regression results show a statistically significant positive relationship be-tween Internet access rates and the rate of patents granted by state. Table 1shows that even when controlling for state differences in GDP, federal R&Dfunding, private R&D funding, and the number of science and engineeringPhDs employed in each state, the relationship between Internet access ratesand patent granting rates remains highly significant.


Table 1

Estimate Std. Error t-value Pr(¿—t—)

Internet 4.25E-003 5.76E-004 7.3759 1.18E-012***GDP -2.62E-006 3.31E-006 -0.791 0.429466Fed RD 9.13E-007 1.94E-006 0.4718 0.63738Biz RD 6.38E-005 3.01E-005 2.1168 0.034974*PhDs 1.19E-001 3.84E-002 3.0953 0.002123**

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ‘ 1Total Sum of Squares: 16.182Residual Sum of Squares: 11.225R-Squared : 0.30634Adj. R-Squared : 0.26429F-statistic: 31.0902 on 5 and 352 DF, p-value: 2.22e-16

The above model uses granted patents as the dependent variable, whichcan prove problematic in that a lag period generally exists between when aninvention is made and a patent subsequently applied for and when a patent isgranted.87 This “pendency period” varies from patent to patent, but over thepast two decades has generally hovered somewhere between 2-3 years.88 Toattempt to more accurately model the Internet’s effect on patenting, one needsto take account of this pendency period. To do so, a second model was runwith the dependent variable—patents per 1000 people—lagged by two years.

Table 2 shows that, even when the patent rate lags by two years to accountfor patent pendency, Internet access rates show a significant and positive re-lationship with patents. The magnitude of the effect is somewhat diminishedin the lagged model, but it does remain statistically significant. The rest of themodel coefficients remain similar. This suggests that even when controllingfor important predictors of patentable research activity, like research and de-velopment spending and the number of researchers working in a state, whenInternet access increases, one can expect the number of patents granted to in-crease after a few years.

E. Additional Tests to Support the Existence of an ICT Effect on In-novation

While the above model supports the assertion that improvements in informa-tion and communication technology lead to increased rates of patenting, likeany statistical model, it is not immune to criticism. To shore up support for

87See generally Jason J. Chung, Patent Pendency Problems and Possible Solutions to Reducing Patent Pendency at theUnited States Patent and Trademark Office, 90 J. PAT. & TRADEMARK OFF. SOC’Y 58 (2008).

88USPTO Annual Reports, U.S. PATENT & TRADEMARK OFFICE, http://www.uspto.gov/about/stratplan/ar/(last visited Oct. 25, 2015).


Table 2

Estimate Std. Error t-value Pr(¿—t—)

Internet 2.54E-003 6.57E-004 3.8758 0.0001268***GDP -1.72E-006 3.78E-006 3.78E-006 6.49E-001Fed RD 2.96E-006 2.21E-006 1.342 0.180459Biz RD 1.41E-004 3.43E-005 4.114 4.85E-005***PhDs 1.92E-001 4.38E-002 4.3763 1.59E-005***

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ‘ 1Total Sum of Squares: 18.416Residual Sum of Squares: 14.576R-Squared : 0.20854Adj. R-Squared : 0.17992F-statistic: 18.5495 on 5 and 352 DF, p-value: 2.3198e-16

the position that ICT developments have altered the way innovation happensand that these alterations merit consideration by law and policy makers, thisArticle provides two additional tests below.

1. Analyzing a Technological Subset

The above analysis has shown that access to the Internet significantly corre-lates with increased patenting.89 Even when controlling for R&D expenditure,state GDP, and the number of researchers working within the state, we stillobserve a positive and statistically significant relationship between Internetaccess and patenting rates. One could rely on the theoretical explanations forhow ICTs affect innovation described in Part II and point to this correlation asevidence of just such an effect. Others, however, may see this evidence andconclude that the increased rate of innovation may not be due to the func-tional nature of ICTs, but rather due to the fact that states with higher ratesof Internet access also had more computers and computer-professionals dur-ing this time. During the period under examination, many technological im-provements to computers and related technologies occurred. While these im-provements would have led to increased patenting, especially of ICT-relatedtechnologies, nothing clearly indicates that the increase could be attributedto any functional attributes of ICTs. Indeed, the 1990s and early 2000s mighthave happened to be a particularly fruitful period for computer-related in-ventions, with many avenues for relatively easy inventions opened by earlypath-breaking developments in computer technology.

If this were the case, and states with higher Internet access rates experi-enced greater levels of patenting simply because more computers and com-puter professionals lived in them during the period of study, then we wouldnot be able to conclude that ICTs have the sort of functional effects on the inno-vation environment posited previously. To eliminate this alternate explanation

89See supra Part III.


one can perform an analysis similar to that in the preceding section, but insteadof using the total number of patents per capita as the dependent variable, usea subset that excludes computer-related technologies.

To do so I performed an identical analysis as that described above, usingthe same predictor and control variables, but excluding any patents from thestate patents per capita measure if they were classified in USPTO patent classesthat are closely related to computer technologies.90 Doing so demonstratesthat, when even when excluding computer-related technologies from the an-alyzed data, Internet access remains positively and statistically significantlyrelated to patenting rates.91 This rules out the alternate explanation suggestedabove and strengthens the argument that something about Internet access, andICTs more generally, that encourages invention.

2. The Internet and Collaborative Invention

If ICTs genuinely do decrease the costs of innovation by facilitating easier andlower-cost collaboration, the patenting record should show this. Patent lawrequires that when two or more individuals create an invention, they eachbe listed as inventors in the application.92 If the above assertion about therelationship between ICTs and collaboration holds true,93 one would expectthat, as a state’s Internet access rises, one would also see a rise in the proportionof patents filed in that state listing more than one inventor.

Using the same patent data as that in the above analysis, but changingthe dependent variable from patents granted to a collaborative patenting ratehelps get at this issue. The collaboration variable is defined as the proportionof patents in each state that list two-or-more authors. So, in the case of a statelike New York that was home to inventors listed on 9,772 patents in the year2000, 1,436 of which listed more than one author, the collaboration rate wouldbe 0.147.

Running similar within-subjects fixed-effects panel regression models asthose above94 shows that Internet access has a statistically significant relation-ship with a state’s collaboration rate. That is to say, as Internet rates increasein a given state, we expect to also see an increase in the proportion of patents

90All patents in the 300-level classes—encompassing many electrical technology inventions—and the 700-levelclasses—encompassing many computer and data storage and processing inventions—along with the followingspecific class numbers were excluded from the data: 136 Batteries: Thermoelectric and Photoelectric, 174 Elec-tricity: Conductors and Insulators, 200 Electricity: Circuit Makers and Breakers, 257 Active Solid-State Devices,439 Electrical Connectors, 445 Electric Lamp or Space Discharge Component or Device Manufacturing. Theseexcluded classes are likely over-inclusive and provide a conservative test as to whether the increased patentingobserved relates to computer technology activity rather than some unique trait of ICTs. For more about thepatents granted in each class by year see Patent Counts By Class By Year, JANUARY 1977 – DECEMBER 2013, U.S. PATENT & TRADEMARK OFFICE, http://www.uspto.gov/web/offices/ac/ido/oeip/taf/cbcby.htm (lastvisited Oct. 25, 2015).

91While the magnitude of the effect-size decreases with the exclusion of computer-related patents—those witha coefficient of 1.99E-003 rather than the 4.25E-003 observed above—it remains statistically significant at the p0.001 level, with comparable results for the lagged models.

9235 U.S.C. § 116(a) (2006) (“When an invention is made by two or more persons jointly, they shall apply forpatent jointly . . . .”).

93See supra Part I.B.94See Croissant & Giovanni supra note 70 and accompanying text.


Figure 3

granted to inventors in that state that include more than one inventor. Thisobservation provides additional support for the theory that ICTs have signif-icant effects on the innovation process, and that enabling collaboration is oneof those effects.95

It is possible that the collaboration effect that the Internet causes on theinnovation process might not be immediate. To address this possibility, ad-ditional models that lagged the collaboration rate by both one and two yearswere calculated. In both of these scenarios the Internet’s significant and posi-tive relationship with collaboration rates remained.

To further support the point that Internet access makes collaborative innova-tion easier, we can also look to the type of collaboration that occurs. If in-ventors use ICTs to facilitate collaborative innovation, one would expect tosee more collaborations amongst non-co-located inventors. That is to say, onewould expect to see inventors from different parts of the country working to-gether more than they previously had.

Figure 3 shows the national rate of interstate collaboration during the pe-riod of analysis, which represents the proportion of collaborative inventionsthat include authors from more than one state. As Internet access becamemore common across the country, not only did collaborative inventing become

95Contact the author for full results or for more information on the data processing and analysis applied.


more common, but collaborating with inventors from different states also be-came more common. Statistically modeling this by state though use of Internetaccess as a predictor of the rate of collaboration shows that Internet access isindeed significantly and positively related to the rate of collaboration, evenwhen taking into account all of the control variables included in the previousmodel. This remains true for same-year and lagged models.

* * *

While the between-state differential effect that the Internet may have oninventive activity has likely disappeared due to the generally high rates of In-ternet access across the country, the lessons about innovation that this modelteaches remain relevant. The above analysis shows that access to powerfulICTs like the Internet can lead to more inventions and an increase in patent-ing behavior. As Internet access spread across the country, those states thatenjoyed higher rates of access also enjoyed higher rates of patenting. Evenwhen excluding computer-related technologies from the analysis and control-ling for major predictors of patenting like R&D expenditures, state GDP, andthe number of researchers working within the state, we see that Internet accessis related to more patented inventions. This increase is due to the second-orderobviousness effects that arise from ICT functionality. As ICTs have made in-formation easier to work with, collaboration easier to engage in, and marketresearch easier to perform, they have effectively made invention easier. Thenext Part will turn to how the law should react to this important lesson.

IV. How Should Innovation Policy React to Second-Order Obviousness?

The above analysis has argued that all inventions affect the innovation envi-ronment in one of two ways: via the production of new information that canbe used as an inspiration for future inventions, and via functional effects thatchange the way research and development work is done.96 Patent law ad-dresses the first of these effects by requiring that new inventions not be toosimilar to, or simplisticly derivative of, those that came before.97 This is whatI refer to as first-order obviousness, and is generally what courts, legislators,and the USPTO have in mind when they refer to “obviousness.” The secondeffect that inventions have—that of enabling inventive behavior—leads to adifferent sort of obviousness that I refer to as second-order obviousness. Ascurrently designed, patent law does not explicitly engage with second-orderobviousness. There are ways that it may be implicitly accounted for in patentdoctrine, but these risk sweeping functional effects under the rug and not suf-ficiently taking them into account while balancing innovation incentives.

96See supra Part I.C.97See 35 U.S.C. § 102 (2012) (requiring that an invention be new to qualify for patentability); id. at § 103

(requiring that an invention be sufficiently different from existing technologies).


This Part will discuss how current patent law should deal with second-order obviousness, and improvements that could be made to ensure that theboundaries of patentability remain appropriately drawn. Suggested improve-ments include: (1) nuancing secondary non-obviousness considerations to re-spond to the funcational effects that ICTs have had on the innovation system;(2) acknowledging the rise of team research by changing the person havingordinary skill in the art standard into a team having ordinary skill in the art(THOSITA) standard; (3) altering the text of Section 103 to encourage patentexaminers to account for functional technologies that may lead to second-order obviousness; and (4) creating a USPTO innovation technology assess-ment office, charged with making discrete institutional silos aware of inven-tions outside their field of expertise that may have relevance to their field’sinnovation environment.

A. How the Innovation System May Currently Account for Second-Order Obviousness

While current innovation policy does not explicitly account for the second-order obviousness effects that inventions like ICTs can have, courts do havesome doctrinal tools that partially take these considerations into account. Asargued above, ICTs have three types of functional effects on the innovation en-vironment that increase second-order obviousness: information effects, collab-oration effects and market transparency effects.98 Through these effects, ICTsenable more efficient work with information, help inventors work together,and clarify what sorts of inventions inventors should focus on.

These effects are all to some degree related to obviousness considerationsthat courts have long taken into account when assessing patent validity. Forinstance, the information effect—wherein ICTs make it easier for inventors toaccess the information that comprises an essential component in the innova-tive process—brings to mind the way courts consider the “knowledge pos-sessed by a person having ordinary skill in the art.”99 Similarly, the mar-ket transparency effect—wherein ICTs enable inventors to better measure mar-ket demand for potential inventions and thus more efficiently focus theirenergies—brings to mind secondary considerations about pre-existing marketdemand.100 The improved ease of collaboration that ICTs allow does not fit asneatly into current non-obviousness analysis, but could be considered closely-related to the “level of ordinary skill in the . . . art”101 as collaborative teamsundoubtedly possess more collective skill than their individual members.

As such, the current innovation system already has some ability to respondto changes in the innovation environment like those brought about by ICT de-velopments. Courts and the USPTO can and should take the innovation en-vironment into consideration during the non-obviousness analysis. The chal-

98See supra Part II.99KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 418 (2007).

100Id. (stating that non-obviousness analysis requires courts to look to “the effects of demands known to thedesign community or present in the marketplace . . . .”).

101Graham v. John Deere Co. of Kan. City, 383 U.S. 1, 17 (1966).


lenge, however, lies in understanding when the innovation environment haschanged, how it has changed, and how those changes may have affected theinnovation process behind a given invention.

In the case of ICTs, certain aspects of the current non-obviousness doc-trine could be used to redraw the bounds of patentability in response to theirsecond-order obviousness effects. Current non-obviousness doctrine initiallyapplies the Graham factors to determine whether a claimed invention is un-patentable.102 In addition to the Graham factors, courts and the USPTO look tosecondary considerations of non-obviousness,103 and at times apply the teach-ing, suggestion, or motivation (TSM) test.104 The below will show that boththe Graham factors and secondary patentability considerations can be used toaddress some of the concerns raised by second-order obviousness.

1. The Person Having Ordinary Skill in the Art

The person having ordinary skill in the art (PHOSITA) is invoked frequentlyin patent doctrine.105 He represents innovation policy’s equivalent of the rea-sonable man,106 and comprises an essential aspect of the Graham inquiry intonon-obviousness.107 When assessing obviousness, courts and examiners usethe PHOSITA to determine the vantage point from which obviousness shouldbe assessed.108 If the PHOSITA would have found the invention obvious, theunderlying invention is not patentable subject matter.109 This individual is as-sumed to have both an ordinary level of skill in the relevant research area, andan ordinary level of creativity.110

102See id. (noting that the factors include the scope and content of the prior art; the differences between theclaimed invention and the prior art; and the level of ordinary skill in the art); see also Cotropia, supra note 9.

103See Iron Grip Barbell, Co. v. USA Sports, Inc., 392 F.3d 1317, 1323–24 (Fed. Cir. 2004) (analyzing secondarynon-obviousness considerations); John Paul Putney, Are Secondary Considerations Still “Secondary”?: An Exami-nation of Objective Indicia of Nonobviousness Five Years After KSR, 4 AM U. INTELL. PROP. BRIEF 45–46 (2013);Natalie A. Thomas, Secondary Considerations in Nonobviousness Analysis: The Use of Objective Indicia Following KSRv. Teleflex, 86 NYU L. REV. 2070, 2071–74 (2011).

104The Supreme Court disavowed the mechanical application of the TSM test in KSR v. Teleflex, 550 U.S. 398(2007), but courts, including the Federal Circuit, still use it to inform non-obviousness analysis. See, e.g., PregisCorp. v. Kappos, 700 F.3d 1348, 1354–55 (Fed. Cir. 2013) (looking for suggestions to combine and teaching awayin the prior art and examining motivations to invent); see Emer Simic, The TSM Test is Dead: Long Live the TSMTest! The Aftermath of KSR, What Was All the Fuss About?, 37 AIPLA Q.J. 227, 230–38 (2009).

105In addition to non-obviousness analysis, the PHOSITA also has importance to claim construction. SeePhillips v. AWH Corp., 415 F.3d 1303, 1313 (Fed. Cir. 2005) (“[T]he ordinary and customary meaning of aclaim term is the meaning that the term would have to a person of ordinary skill in the art in question at thetime of the invention . . .”). For more on the PHOSITA standard see generally Joseph P. Meara, Just Who is thePerson Having Ordinary Skill in the Art? Patent Law’s Mysterious Personage, 77 WASH. L. REV. 267 (2002); John O.Tresansky, PHOSITA - The Ubiquitous and Enigmatic Person in Patent Law, 73 J. PAT. & TRADEMARK OFF. SOC’Y37 (1991).

106See Panduit Corp. v. Dennison Mfg. Co., 810 F.2d 1561, 1566 (Fed. Cir. 1987) (“With the involved factsdetermined, the decisionmaker confronts a ghost, i.e., ‘a person having ordinary skill in the art,’ not unlike the‘reasonable man’ and other ghosts in the law.”).

107Graham v. John Deere Co. of Kan. City, 383 U.S. 1, 18 (1966).10835 U.S.C. § 103 (2012) (“A patent for a claimed invention may not be obtained . . . if the differences between

the claimed invention and the prior art are such that the claimed invention as a whole would have been obviousbefore the effective filing date of the claimed invention to a person having ordinary skill in the art . . . .”).

109Id.110KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 420 (2007) (“A person of ordinary skill is also a person of ordinary

creativity, not an automaton.”).


The PHOSITA standard may implicitly account for some of the concernsraised by second-order obviousness. In the case of ICTs, two of the mecha-nisms through which they induce second-order obviousness, specifically in-formation effects and collaboration effects, could each be mitigated by the ob-vious to a PHOSITA inquiry. However, some minor alterations to the analysiswould make treatment of second-order obviousness concerns more explicitand would help ensure consistency and clarity in patent doctrine.

The PHOSITA and the Information Effect. Courts could use the PHOSITA’spresumed knowledge of the prior art to mitigate some of the concern raised bythe information effect that ICTs have on the innovation environment. Courtsoften assume the ordinary person is actually a sort of “superperson”111 with“knowledge of all pertinent prior art.”112 The assumption that the PHOSITAknows all the relevant prior art could partially mitigate the second-order ob-viousness that arises from ICTs’ information effect on the innovation environ-ment. However, current non-obvious doctrine hampers any potential mitiga-tion because not all prior art is considered “analogous” and because courts willnot only look for knowledge of the prior art, but also evidence of a motivationto combine or modify them in the manner claimed.113

Given how much easier it is to navigate the innovation environment nowthan when the obviousness doctrine was originally developed, courts shouldalter the boundaries of what they consider analogous art, and not require amotivation to combine for an obviousness finding. Under current doctrine,before considering prior art in an obviousness analysis, courts and the USPTOfirst ask whether it is “analogous art to the claimed invention.”114 To makethis determination the examiner asks: (1) whether the prior art is from thesame field as the claimed invention; or (2) whether the prior art is reasonablypertinent to the inventor’s problem.115 If the answer to either of these ques-tions is “yes” then the reference in question is analogous prior art and may beconsidered in a non-obviousness analysis.116

However, the analysis does not end there. Once the examiner determinesthe universe of analogous prior art, she then engages in the next steps of thenon-obviousness inquiry. This involves comparing the prior art to the claimedinvention, and determining the level of ordinary skill in the art.117 Once com-pleted, the examiner looks for some evidence that would suggest that one or-

111See Michael Ebert, Superperson and the Prior Art, 67 J. PAT. & TRADEMARK OFF. SOC’Y 657, 657 (1985)(describing the PHOSITA as a superperson rather than an ordinary person because of the expectation that hehave such wide-ranging memory capacity and mental abilities).

112Bristol-Myers Squibb Co. v. Teva Pharms. USA, Inc., 769 F.3d 1339, 1357 (Fed. Cir. 2014) (Newman, J.,dissenting) (emphasis added).

113Innogenetics, N.V. v. Abbott Laboratories, 512 F.3d 1363, 1374 (Fed. Cir. 2008) (“[S]ome kind of motiva-tion must be shown from some source, so that the jury can understand why a person of ordinary skill wouldhave thought of either combining two or more references or modifying one to achieve the patented method.”)(citation omitted).

114MPEP § 2141.01(a) (9th ed. Rev. 7, March 2014).115Id. (citing In re Bigio,381 F.3d 1320, 1325 (Fed. Cir. 2004)).116Id.117See MPEP § 2141 II(A).


dinarily skilled in the art would be motivated to create the invention.118 Thismotivation could come from prior art that provided a “teaching, suggestion,or motivation” for the claimed invention119 or alternately from “any need orproblem known in the field of endeavor.”120

While the motivation-to-combine requirement was perhaps a sensible pol-icy in an era when information had a much greater cost to access andorganize—and thus innovation more costly to achieve—it is too forgiving inthe current era of low-cost and ubiquitous information access. The motiva-tion requirement places the obviousness bar too high, and should be altered inresponse to the changes that ICTs have brought to the world of research anddevelopment. Courts could easily make this adjustment by altering the non-obviousness analysis to presume the PHOSITA has a motivation to combine theprior art as combined in the claimed invention. This presumption would be re-buttable if prior art “teaches away” from making such a combination.121 Thistype of minor alteration to the obviousness analysis would help re-balance theinnovation incentives that have been upset by the widespread second-orderobviousness effects arising from decades of ICT development.

To demonstrate how this alteration might affect patentability deliberations,consider Circuit Check, Inc. v. QXQ Inc., a recent case decided by the FederalCircuit.122 QXQ—which had been sued for infringement by Circuit Check—argued that Circuit Check’s circuit board interface plate patent should beconsidered non-patentable because of obviousness, similarities between thepatented technique and those used in a variety of prior art including rock carv-ing techniques, and machining and engraving techniques.123 Although thelower court had sided with QXQ, granting a motion for judgment as a matterof law and finding the disputed claims invalid for obviousness,124 the FederalCircuit disagreed.125 At appeal, the Federal Circuit relied on the analogous artdoctrine, stating that “[a]lthough ‘familiar items may have obvious uses be-yond their primary purposes,’ . . . a reference is only reasonably pertinentwhen it ‘logically would have commended itself to an inventor’s attention inconsidering his problem.”’126 Taking greater notice of second-order obvious-ness would weaken the analogous art doctrine. Instead of requiring prior artto logically commend itself to the inventor, courts should instead presume therelevance of all prior art, while allowing a patentee to rebut that presump-tion by showing how their invention was truly non-obvious. Altering the non-obviousness analysis in this way would help it reflect more appropriately the

118Innogenetics, 512 F.3d, at 1374.119See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 399, 418–420 (2007) (rejecting the rigid application of the TSM

test but admitting it does provide “helpful insight . . . .”).120Id. at 420.121In re Gurley, 27 F.3d 551, 553 (Fed. Cir. 1994) (“A reference may be said to teach away when a person

of ordinary skill, upon reading the reference, would be discouraged from following the path set out in thereference, or would be led in a direction divergent from the path that was taken by the applicant.”).

122Circuit Check Inc. v. QXQ Inc., No. 2015–1155 (Fed. Cir. 2015).123Id. at 3.124Id. at 4.125Id. at 2.126Id. at 6–7 (citations omitted).


demands of the current innovation system.

The PHOSITA and the Collaboration Effect. It is less clear how currentpatent doctrine addresses the collaboration effect that ICTs have on the in-novation process. While collaboration has steadily increased across almostall research disciplines127—effectively increasing society’s collective technicalabilities—patentability standards have done little to react to these changes.The PHOSITA standard could prove useful here as well.

To respond to the rise of team science and ensure that patentability stan-dards appropriately reflect the difficulty of inventing, courts and the USPTOshould alter the PHOSITA analysis to focus not on a person having ordinaryskill in the art, but a team having ordinary skill in the art (THOSITA). There aresome instances on the record of courts taking the availability of teammates intoaccount when assessing a PHOSITA’s abilities.128 That said, these instances arethe exception to the overly individualistic rule that the current PHOSITA stan-dard presents.129

A THOSITA standard would work similarly to the current PHOSITA stan-dard, but it would first inquire as to the typical size and makeup of a teamin the field. Once it had determined how large an ordinary team is in therelevant art, and what sort of researchers are likely to be members, the courtcould then proceed with the traditional PHOSITA factor analysis, looking to:“(1) the educational level of the [team]; (2) type of problems encountered inthe art; (3) prior art solutions to those problems; (4) rapidity with which in-novations are made; (5) sophistication of the technology; and (6) educationallevel of active workers in the field.”130 Assessing this from a team standardwould help the non-obviousness analysis more accurately reflect the actualityof modern day innovation. It would remind courts that, instead of consideringobviousness from the perspective of the mythical sole inventor,131 they shouldconsider how obvious the invention would seem to an average team in therelevant discipline.

2. Long Felt but Unmet Need

The “long-felt but unmet need” secondary obviousness consideration couldbe used to challenge the obviousness of patents enabled by the improved mar-ket transparency type effect that inventions like ICTs have on the innovation

127See Wuchty et al., supra note 49, at 1036–38.128See, e.g., Takeda Pharm. Co. v. Mylan Inc., [2014] WL 5862134, *14 (N.D. Cal. 2014) (stating in a patent claim

construction PHOSITA analysis that a PHOSITA “would likely have been part of, or had access to, a team ofindividuals with various skills spanning the chemical arts.”); Andis Clipper Co. v. Oster Corp., 481 F. Supp.1360, 1375 (E.D. Wis. 1979) (stating in an obvious to a PHOSITA analysis that the PHOSITA would have been “apart of a ‘unit’ or ‘team’ dealing with new concepts and new projects on a continuous basis . . . .”).

129Bristol-Myers Squibb Co. v. Teva Pharms. USA, Inc., 769 F.3d 1339, 1357–58 (Fed. Cir. 2014) (Newman, J.,dissenting)..

130Id. This alteration to the PHOSITA standard may require a small alteration to §103 that requires an inventionnot be obvious “to a person having ordinary skill in the art.” 35 U.S.C. § 103 (2012) (emphasis added). This appar-ently singular approach to the non-obviousness assessment might preclude courts from altering the PHOSITAinto a THOSITA without minor statutory alterations.

131For more on the mythical sole inventor see Lemley, supra note 46.


environment. This consideration traditionally weighs against finding an in-vention obvious if there was pre-existing demand for the technology that hadlong gone unmet.132 A long-felt but unmet need demonstrates that an inven-tion was not obvious because had it been obvious, the need would not havegone unmet.133 Using the motivation to invent provided by improved markettransparency as evidence of obviousness would analyze market demand in amore nuanced way, with the demand potentially cutting either for or againstan obviousness finding depending on how long demand remained unmet.

The analysis here would turn on how high demand was for the invention,how transparent that demand was, and how long it had been unmet for. Along felt but unmet demand would remain unchanged as evidence of non-obviousness for the same reason it is so now. On the other hand, a newfoundand sufficiently evident demand for a given technology would cut in the op-posite direction in favor of finding an invention obvious. All else being equal,it is less likely that we need to provide patent rights for an invention newly inhigh demand. It is very possible that the market may fulfill this demand onits own, making a patent in the area ultimately inefficient. If a market failureoccurs and the demand remains unmet, then the original interpretation of thelong felt but unmet demand consideration will encourage innovation and helpa related invention survive an obviousness challenge.

These minor alterations to current non-obviousness analysis—a presump-tion of motivation to combine, applying a THOSITA rather than PHOSITAstandard, and paying more attention to the length that demand for an inven-tion has existed—would help respond to the changes that ICTs have broughtto our innovation environment. However, the ICT revolution has alreadywrought much of its change. Future technologies will surely transform the in-novation processes in new and as-yet unimagined ways, and innovation policyneeds to be designed in a manner that will allow it to respond to these changes.

B. Updating Non-Obviousness Jury InstructionsAltering jury instructions to explicitly refer to the capabilities that the currentlyavailable technology affords inventors could help courts ensure that secondaryobviousness concerns are adequately considered. Take for instance the FederalCircuit Bar Association’s Model Patent Jury Instructions.134 These instructionscurrently direct the jury to “consider the level of ordinary skill in the field [ofthe invention] that someone would have had at the time the [invention wasmade] or [patent was filed], the scope and content of the prior art, and any dif-ferences between the prior art and the claimed invention.”135 The instructionsdefining the PHOSITA in turn read:

132See, e.g., Procter & Gamble Co. v. Teva Pharm. USA, Inc., 566 F.3d 989 (Fed. Cir. 2009); Monarch KnittingMach. Corp. v. Sulzer Morat GmbH, 139 F.3d 877 (Fed. Cir. 1998).

133Timothy J. Le Duc, The Role of Market Incentives in KSR’s Obviousness Inquiry, 11 WAKE FOREST J. BUS. &INTELL. PROP. L. 33, 47–48 (2010).

134See, generally, FED. CIRCUIT BAR ASS’N, MODEL PATENT JURY INSTRUCTIONS 2 (2014), avail-able at http://memberconnections.com/olc/filelib/LVFC/cpages/9004/Library/2012%20Updated%20FCBA%20Model%20Patent%20Jury%20Instructions.pdf.

135Id. at 46.


In deciding what the level of ordinary skill in the field of [invention] is, youshould consider all the evidence introduced at trial, including but not limitedto: (1) the levels of education and experience of the inventor and other personsactively working in the field; (2) the types of problems encountered in the field;(3) prior art solutions to those problems; (4) rapidity with which innovationsare made; and (5) the sophistication of the technology.136

The final instruction here, urging jurors to consider “the sophistication ofthe technology” is the most suitable area to incorporate explicit reference tothe technological affordances that ease invention. As the instructions cur-rently read, the “sophistication of the technology” consideration speaks mostdirectly to the complexity of the invented technology, with jurors perhaps un-derstanding that more sophisticated technological developments are less obvi-ous than their less sophisticated counterparts. However, this instruction couldbe adapted somewhat so as to account not only for the sophistication of thetechnology in question, but for the availability of all technologies and the abil-ities they afford inventors who work in the area.

To do so the final clause in the jury instruction PHOSITA definition couldbe altered to flag the effect that general technological affordances may haveon the invention process. Doing so would make the jury instructions read asfollows, with emphasis added:

In deciding what the level of ordinary skill in the field of [inven-tion] is, you should consider all the evidence introduced at trial,including but not limited to: (1) the levels of education and expe-rience of the inventor and other persons actively working in thefield; (2) the types of problems encountered in the field; (3) priorart solutions to those problems; (4) rapidity with which innova-tions are made; and (5) the sophistication of the technology at issue,and the capabilities of all available technologies that affect the research,development and invention process.

The italicized phrase adds very little complexity to the jury instructions, butensures that the jury is asked to consider not only the technology at issue inthe contested patent, but also the general technological environment and howit might affect obviousness.

C. Future Second-Order ObviousnessThis Article has focused on ICTs as an example of how technologies can havesecond-order obviousness effects and has argued that inventions have two po-tential types of effect on the innovation environment: inspirational and func-tional. Inspirational effects are those most familiar in patent non-obviousnessanalysis and lead to first-order obviousness. On the other hand, functionaleffects are less often appreciated as they lead to second-order obviousness.

In the case of ICTs, these functional effects include increased access to in-formation, eased collaboration, and improved market transparency. Part III

136Id. at 48.


provided support for this contention by demonstrating that as the Internet—today’s ICT non pareil—spread across America, the rate of invention also in-creased. However, the Internet is not unique in its ability to facilitate invention.Future technologies, perhaps ones that we cannot now even imagine, will al-most certainly have their own functional effects that will threaten to upset thebalance struck by federal innovation policy.

By more fully theorizing second-order obviousness effects, this Articlehopes to put policymakers on notice to prepare them for when new technolo-gies emerge that further alter the innovation environment. Society saw rapidincreases in the rates of patenting as the Internet became widely used acrossthe United States.137 To the extent that this growth in patenting reflects the in-creased ease of invention that innovation policy had yet to take into account,it demonstrates the danger posed by not appropriately responding to the de-velopment of new technologies that ease invention.

Inadequately adjusting innovation policy to account for changes in diffi-cultly in creating new inventions risks upsetting the patent incentive systemand thereby allowing for a proliferation of exclusive rights that risk slowingfuture innovation. As discussed above, patent grants are intended to cre-ate incentives that will lead to inventions that either would not have other-wise occurred or would have occurred more slowly absent the incentive.138

If those incentives are improperly tailored, the USPTO will grant patents toinventions that would have been created regardless of the incentives offered,which ultimately leads to inefficiencies. Granting bad patents unnecessarilyforecloses competition by allowing a single firm to control the use of an inven-tion that, even without the potential for a patent, would have been developedanyway.139

A proliferation of exclusive rights to inventions also risks upsetting theinnovation system more generally. The more patents there are, the more likelyany invention is to potentially infringe upon another patent.140 This raisestransaction costs as innovators must search more prior art and negotiate formore licenses to bring their products to market.141 This gives rise to a potentialinnovation chilling effect as patent thickets may prove such a disincentive thatinnovators do not bring their potential innovations to market because theybelieve the risk of infringement liability is too high.142

137See U.S. PATENT & TRADEMARK OFFICE, supra note 3.138Supra Part I.A.139See EXEC. OFFICE OF THE PRESIDENT, PATENT ASSERTION AND U.S. INNOVATION 2 (2013), available at

https://www.whitehouse.gov/sites/default/files/docs/patent report.pdf. But see F. Scott Kieff, Property Rightsand Property Rules for Commercializing Inventions, 85 MINN. L. REV. 697, 702–04 (2001) (arguing that the patentsystem functions not only to incentivize creation, but more importantly to incentivize development and com-mercialization).

140Carl Shapiro, Navigating the Patent Thicket: Cross Licenses, Patent Pools, and Standard Setting, in INNOVATIONPOLICY & THE ECONOMY, VOLUME 1 119, 121 (Adam B Jaffe et al. eds., 2001) (“The vast number of patentscurrently being issued creates a very real danger that a single product or service will infringe on many patents.”).

141Id. at 119 (“Cross licenses and patent pools are two natural and effective methods used by market partici-pants to cut through the patent thicket, but each involves some transaction costs.”).

142Id. at 144 (“Our current patent system is causing a potentially dangerous situation in several fields . . . inwhich a would-be entrepreneur or innovator may face a barrage of infringement actions that it must overcometo bring its product or service to market.”).


While the risk that future inventions may upset carefully crafted innova-tion policy will remain ever-present, we can prepare for this eventuality inways that will help the patent system become more responsive to these sortsof changes. Congress could signal to the USPTO and courts that they shouldtake full account of the innovation environment when assessing patentabil-ity. To do so, a minor alteration to § 103 would help clarify that examinersshould take into account not only the inspirational effects that prior art has onthe likelihood that a given invention would have been created, but also thesecond-order obviousness effects that more general-use technologies have onthe innovation environment. This could be done by altering § 103 to precludepatentability “if the differences between the claimed invention and the priorart are such that the claimed invention as a whole would have been obviousbefore the effective filing date of the claimed invention to a person or team hav-ing access to technologies commonly used in the relevant field and having ordinaryskill in the art to which the claimed invention pertains.” This is the existing textfrom § 103, with the addition of the italicized clause that would serve to makesecond-order obviousness concerns more prominent to courts and patent ex-aminers. While, as mentioned above, the current PHOSITA analysis could beconstrued to include consideration of the PHOSITA’s team situation and ac-cess to technologies, making these considerations explicit will help mitigateconcerns about granting bad patents.

In addition to alterations of § 103, the USPTO should consider establishingan innovation technology assessment office. This office would monitor technolo-gies that promise to have functional effects on the innovation system. TheUSPTO’s current structure potentially discourages examiners from appreci-ating the effects that inventions outside their area of expertise may have oninventions within their field. The USPTO is organized into a series of “tech-nology centers,” each of which contains a number of art units that are respon-sible for examining patent applications in some set of classes and subclasses.143

While this structure promotes specialization and encourages examiners to be-come familiar with their field’s prior art, it also risks overspecialization.

This overspecialization may cause examiners to be less aware of techno-logical developments in other fields that may have functional effects on the in-novation processes relevant to their own art units. An innovation technologyassessment office would track new technologies that alter the way innovationoccurs and create reports for examiners in affected art units. For instance, ifsoftware developers created a new program capable of modeling flavor com-pounds in a manner that was an order of magnitude more efficient than cur-rent flavor compound research occurs, it may make some inventions that pre-viously would have been patentable, unpatentable for non-obviousness rea-sons.144 However, specialization at the USPTO may lead to lag before relevant

143See Patent Technology Centers Management, U.S. PATENT & TRADEMARK OFFICE, http://www.uspto.gov/patent/contact-patents/patent-technology-centers-management (last visted Oct. 25).. See also MPEP §§903.08(b)–(d) (9th ed. Rev. 7, March 2014).

144It is true that this flavor compound may ultimately be held unpatentable if the patent were ultimately chal-lenged. In this situation the lag between the patent application and any ensuing trial would allow the functionaleffects of the new hypothetical computer program to become more widely known. Regardless, proactively deal-


examiners become aware of the new computer technology, and bad patentsmay be granted in the interim. An office of innovation technology assessmentwould help address this lag by proactively seeking out inventions that exam-iners should be aware of.

* * *

These alterations to patentability standards would help to re-balance thedeal struck by the public with inventors. As noted above in Figure 2, thenumber of patents granted has exploded in recent years. With more patentsgranted, society stands to face increased problems with patent thicketing,145

and potentially slower innovation than would otherwise occur. To correctfor this the public needs to be more discerning as to when it grants exclusiverights. Altering the text of § 103 to foreground second-order obviousness con-cerns, and charging an office with monitoring how new technologies may havemore general effects on the innovation process, will help ensure that the patentsystem is able to respond to future changes to the innovation environment.

Conclusion

Technology changes the way people innovate. In addition to providing inspi-ration for future inventions (first-order obviousness), it also changes the waypeople work and research, making even seemingly unrelated inventions eas-ier to create (second-order obviousness). This Article has theorized differentways that technology affects the innovation policy system. ICTs have pro-vided a recent and dramatic example of how some technologies can have bothinspirational and functional effects on the innovation system. ICTs ease workwith information, facilitate collaboration, and make markets more transparent,which leads to lower cost inventions and more patent grants. This occurred re-cently as Internet access spread across the country, raising local patent rates asit did so.

To ensure appropriate incentives, policymakers must engage with second-order obviousness. Altering the non-obviousness analysis so that it explic-itly engages not only with the inspirational effects of prior technologies butalso their functional effects can satisfy this imperative. Additionally, increasedmonitoring of new technologies and training at the USPTO will help ensurethat technological developments with generalized effects on the innovationsystem do not go unnoticed by potentially affected art units..

Technology can have innovation feedback loops, accelerating innovationand transforming people’s lives in an ever-faster fashion. Making sure that thepublic stays aware of these effects and that innovation incentives are designedto account for them is essential to ensuring that maximum benefits accrue to

ing with these sorts of situations is preferable because it does not require litigation—an expensive and relativelyunlikely occurrence—and it reduces the number of bad patents granted.

145Shapiro, supra note 140, at 119–122.


the public in future years. Otherwise society risks unnecessarily enclosing un-told amounts of intellectual property that would not have survived a second-order obviousness challenge.

second-order obviousness: how information and communication technologies make inventions more...

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