Guangyu Zou et al.

Patent Trials and Appeals Board

Dec 26, 2019

14190205 - (D) (P.T.A.B. Dec. 26, 2019)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
14/190,205 02/26/2014 Guangyu Zou 20130880US01 2406
144328 7590 12/26/2019
JONES ROBB, PLLC (CONDUENT)
1420 Spring Hill Road
Suite 325
McLean, VA 22102
EXAMINER
KONERU, SUJAY
ART UNIT PAPER NUMBER
3624
NOTIFICATION DATE DELIVERY MODE
12/26/2019 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
Conduent.PatentDocketing@conduent.com
docketing@jonesrobb.com
kevin.robb@jonesrobb.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte GUANGYU ZOU, MARINA L. THARAYIL, ALVARO E. GIL,
DEEPTHI CHANDRA, and LAURA ELISA CELIS
Appeal 2018-006935
Application 14/190,205
Technology Center 3600
Before MAHSHID D. SAADAT, JAMES R. HUGHES, and
SCOTT E. BAIN, Administrative Patent Judges.
HUGHES, Administrative Patent Judge.
DECISION ON APPEAL
STATEMENT OF THE CASE
Pursuant to 35 U.S.C. § 134(a), Appellant1 appeals from the
Examiner’s decision rejecting claims 1, 3–15, 17–20, and 22–24. Claims 2,
16, and 21 have been canceled. See Final Act. 1–2.2 We have jurisdiction
under 35 U.S.C. § 6(b).

1 We use the word Appellant to refer to “applicant” as defined in 37 C.F.R.
§ 1.42(a). Appellant identifies the real party in interest as Conduent
Business Service, LLC. See Appeal Br. 2.
2 We refer to Appellant’s Specification (“Spec.”), filed Feb. 26, 2014;
Appeal Brief (“Appeal Br.”), filed Mar. 16, 2018; and Reply Brief (“Reply
Br.”), filed June 19, 2018. We also refer to the Examiner’s Final Office
Action (“Final Act.”), mailed Oct. 16, 2017; and Answer (“Ans.”) mailed
April 19, 2018.
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We AFFIRM.
CLAIMED SUBJECT MATTER
The claims in this patent application generally relate to
“crowdsourcing” and, “[m]ore particularly, the presently disclosed
embodiments are related to methods and systems for creating a simulator for
a crowdsourcing platform.” Spec. ¶ 1; see Spec. ¶¶ 4–7 and Abstract.
Claims 1, 13, 15, and 22 are independent. Claim 1, reproduced below, is
illustrative of the claimed subject matter:
1. A method for creating a simulator for a
crowdsourcing platform, the method comprising:
receiving, by one or more processors through a transceiver
over a communication network, parameters comprising
statistical data about one or more entities associated with the
crowdsourcing platform, wherein the statistical data is
determined based on historical data associated with the one or
more entities, and the one or more entities comprise requestors,
tasks, and workers;
calculating a first statistical distribution of a set of the
parameters associated with the requestors, wherein the first
statistical distribution is calculated using one or more curve
fitting techniques based on values of the set of parameters
associated the requestors;
calculating a second statistical distribution of a set of the
parameters associated with the workers, wherein the second
statistical distribution is calculated using one or more curve
fitting techniques based on values of the set of parameters
associated the workers;
generating, by the one or more processors, a plurality of
rules indicative of interactions between the one or more entities
associated with the crowdsourcing platform, wherein generating
the plurality of rules comprises:
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generating a non-deterministic set of rules based on
at least one of the first statistical distribution and the
second statistical distribution;
estimating, by the one or more processors, a first level of
service of the crowdsourcing platform based on the plurality of
rules over a predefined time period;
receiving an observed level of service of the
crowdsourcing platform based on processing of one or more
tasks by the crowdsourcing platform during the predefined time-
period;
modifying, by the one or more processors, the plurality of
rules based on a comparison between the first level of service and
the observed level of service of the crowd sourcing platform,
wherein the modified plurality of rules are used to simulate task
processing by the crowdsourcing platform for potential tasks,
and wherein modifying the plurality of rules further comprises:
varying one or more characteristics of at least one
of the first statistical distribution and the second statistical
distribution based on a comparison between the first level
of service and the observed level of service of the
crowdsourcing platform, and
modifying the non-deterministic set of rules based
on the variation in the one or more characteristics of at
least one of the first statistical distribution and the second
statistical distribution; and
simulating a processing time for the crowdsourcing
platform to complete the potential tasks based on current
conditions of the crowdsourcing platform and the modified
plurality of rules, wherein the simulated processing time is
presented to a provider of the potential tasks.
Appeal Br. 34–35 (Claims App.).
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REJECTION
The Examiner rejects claims 1, 3–15, 17–20, and 22–24 under
35 U.S.C. § 101 as being directed to patent-ineligible subject matter. See
Final Act. 4–8.
ANALYSIS
Subject Matter Eligibility—35 U.S.C. § 101
Under 35 U.S.C. § 101, a patent may be obtained for “any new and
useful process, machine, manufacture, or composition of matter, or any new
and useful improvement thereof.” The Supreme Court has “long held that
this provision contains an important implicit exception: [l]aws of nature,
natural phenomena, and abstract ideas are not patentable.” Alice Corp. v.
CLS Bank Int’l, 573 U.S. 208, 216 (2014) (quoting Ass’n for Molecular
Pathology v. Myriad Genetics, Inc., 569 U.S. 576, 589 (2013)).
The Supreme Court, in Alice, reiterated the two-step framework
previously set forth in Mayo Collaborative Servs. v. Prometheus Labs., Inc.,
566 U.S. 66, 77–80 (2012), “for distinguishing patents that claim laws of
nature, natural phenomena, and abstract ideas from those that claim patent-
eligible applications of those concepts.” Alice, 573 U.S. at 217. The
framework requires us first to consider “whether the claims at issue are
directed to one of those patent-ineligible concepts.” Alice, 573 U.S. at 217.
If so, we then examine “the elements of [the] claim both individually and ‘as
an ordered combination’ to determine whether the additional elements
‘transform the nature of the claim’ into a patent-eligible application.” Alice,
573 U.S. at 217 (quoting Mayo, 566 U.S. at 78, 79). That is, we examine the
claim for an “inventive concept,” “an element or combination of elements
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that is ‘sufficient to ensure that the patent in practice amounts to
significantly more than a patent upon the [ineligible concept] itself.’” Alice,
573 U.S. at 217–18 (alteration in original) (quoting Mayo, 566 U.S. at 72–
73).
The Patent Office recently published revised guidance concerning this
framework and the application of § 101. USPTO’s 2019 Revised Patent
Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019)
(hereinafter “2019 Revised Guidance”). Under that guidance, we first look
to whether the claim recites:
(1) any judicial exceptions, including certain groupings of
abstract ideas (i.e., mathematical concepts, mental processes, or
certain methods of organizing human activity such as a
fundamental economic practice or managing personal behavior
or relationships or interactions between people) (hereinafter
“Step 2A, prong 1”); and
(2) additional elements that integrate the judicial exception into
a practical application (see MPEP § 2106.05(a)–(c), (e)–(h))
(hereinafter “Step 2A, prong 2”).3
See 2019 Revised Guidance, 84 Fed. Reg. at 51–52, 55.
A claim that integrates a judicial exception into a practical application
applies, relies on, or uses the judicial exception in a manner that imposes a
meaningful limit on the judicial exception, such that the claim is more than a
drafting effort designed to monopolize the judicial exception. See 2019
Revised Guidance, 84 Fed. Reg. at 54. When the judicial exception is so
integrated, then the claim is not directed to a judicial exception and is patent
eligible under 35 U.S.C. § 101. Id.

3 All references to the MPEP are to the Ninth Edition, Revision 08–2017
(rev. Jan. 2018).
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Only if a claim (1) recites a judicial exception and (2) does not
integrate that exception into a practical application, do we then evaluate
whether the claim provides an inventive concept. See 2019 Revised
Guidance 84 Fed. Reg. at 56; Alice, 573 U.S. at 217–18.
For example, we look to whether the claim:
(3) adds a specific limitation beyond the judicial exception that
is not “well-understood, routine, conventional” in the field (see
MPEP § 2106.05(d)); or
(4) simply appends well-understood, routine, conventional
activities previously known to the industry, specified at a high
level of generality, to the judicial exception.4
See 2019 Revised Guidance, 84 Fed. Reg. at 56. With these principles in
mind, we turn to the merits of the § 101 rejection. The Examiner rejects
Appellant’s claims 1, 3–15, 17–20, and 22–24 as being directed to patent
ineligible subject matter. See Final Act. 4–8. Appellant does not separately
argue the claims with specificity and, instead, argues claims 1, 3–15, 17–20,
and 22–24 together for this rejection. See Appeal Br. 16–32. Accordingly,
we address the Examiner’s rejection of independent claim 1 and the claims
not separately argued by Appellant as a group based on claim 1, as permitted
by 37 C.F.R. § 41.37(c)(1)(iv).

4 Items (3) and (4) are collectively referred to as “Step 2B” hereinafter and
in the 2019 Revised Guidance.
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Statutory Subject Matter
We find that claim 1 recites a “method” (infra). A “method” is a
process, which is a statutory category of invention (subject matter)
(USPTO’s Step 1).
Abstract Idea
The Examiner rejects Appellant’s claim 1 as being directed to patent
ineligible subject matter. See Final Act. 4–6; Ans. 3–6. Specifically, the
Examiner concludes claim 1 (and the other pending claims) “is directed to a
judicial exception (i.e., . . . an abstract idea) without significantly more”
(Final Act. 4), in particular, the “abstract idea of . . . receiving parameters
comprising statistical data about entities associated with crowdsourcing.”
Final Act. 4. The Examiner also concludes the abstract idea includes:
calculating statistical distributions from the parameters; generating rules
indicative of interactions between entities, where the rules are non-
deterministic and generated based on the statistical distributions; estimating
a level of service based on the rules; and simulating a processing time to
complete the potential tasks based in part on the rules. See Final Act. 4–6.
The Examiner further concludes claim 1 (and the other pending claims) “are
abstract because the claims are an idea itself” “similar to how collecting and
analyzing information to detect misuse and notifying a user when misuse is
detected was an abstract idea in FairWarning and how organizing and
manipulating information through mathematical correlations was an abstract
idea in Digitech.” Final Act. 6 (citing FairWarning IP, LLC v. Iatric Sys.,
Inc., 839 F.3d 1089 (Fed. Cir. 2016) and Digitech Image Techs., LLC v.
Elecs. for Imaging, Inc., 758 F.3d 1344 (Fed. Cir. 2014)).
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Appellant contends the Examiner erred in rejecting the claims as
being directed to patent-ineligible subject matter. See Appeal Br. 16–32;
Reply Br. 2–6. Specifically, Appellant contends, with respect to the first
step of the Alice analysis, that the Examiner erred in rejecting claim 1 (and
the other pending claims) because: (1) claim 1 is not directed to an abstract
idea, “the Office overgeneralized the claims” (Appeal Br. 17; see Appeal Br.
16–22; Reply Br. 4–6); (2) “the Office erred in finding” claim 1 is “not
analogous to the patent eligible claims in McRO” (Appeal Br. 16; see
Appeal Br. 16–18, 22–26; Reply Br. 2–4 (citing McRO, Inc. v. Bandai
Namco Games Am. Inc., 837 F.3d 1299 (Fed. Cir. 2016)); (3) “the Office
erred in finding” claim 1 recites “subject matter similar to the patent
ineligible claims” in FairWarning and Digitech (Appeal Br. 16; see Appeal
Br. 16–19, 27–29; Reply Br. 4–6); (4) the limitations of claim 1 could not be
accomplished mentally or using a pen and paper, the limitations of claim 1
are not conventional or well-known, and the Examiner’s allegations
(concerning concepts that are conventional or well-known) “are not
supported by evidence made of record” (Appeal Br. 21; see Appeal Br. 20–
22; Reply Br. 2–4); and (5) “the claims recite a technological improvement”
(Appeal Br. 21) and “the Office failed to consider technological problems
identified by the Specification and the solutions to those problems, which
are appropriately claimed” (Appeal Br. 19) (see Appeal Br. 16–26; Reply
Br. 2–4).
For the reasons discussed below, we conclude Appellant’s claim 1
(and the other pending claims) recites abstract ideas, these abstract ideas are
not integrated into a practical application, nor do they include an inventive
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concept. In view of the 2019 Revised Guidance, we clarify and expand the
Examiner’s reasoning as follows.
We begin our analysis by broadly but reasonably construing
Appellant’s claim 1 (see Appeal Br. 34–35 (Claims App.)). Claim 1 recites
a “method for creating a simulator for a crowdsourcing platform,” i.e., a
process for simulating (creating a simulation for) a crowdsourcing
platform—an online portal that acts as a mediator between requestors (task
providers) and the workers, where tasks are posted on the online portal by
requestors and workers select the tasks and post responses for the tasks. See
Spec. ¶¶ 2, 21. The method comprises “receiving . . . parameters comprising
statistical data about one or more entities associated with the crowdsourcing
platform, wherein the statistical data is determined based on historical data
associated with the one or more entities, and the one or more entities
comprise requestors, tasks, and workers.” The “receiving” (receipt of
parameters) is performed by “one or more processors through a transceiver
over a communication network.” That is, receiving statistical data
(parameters comprising statistical data) derived from historical data
associated with the crowdsourcing platform entities utilizing a processor,
transceiver, and network. See Spec. ¶¶ 56–57; see also Spec. ¶¶ 58–65.
Hereinafter we refer to this step (sub-process or function) as “Step A.” The
“method” recited in claim 1 includes non-abstract elements (physical
structure) performing the functionality of Step A. These additional (non-
abstract) elements, include at least one processor, a transceiver, and a
communication network. See Spec. ¶¶ 49–53; Fig. 2; see also Spec. ¶¶ 35–
48; Fig. 1.
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Claim 1 further recites “calculating a first statistical distribution of a
set of the parameters associated with the requestors . . . using one or more
curve fitting techniques based on values of the set of parameters associated
the requestors.” In other words, the process includes calculating a statistical
distribution from collected, received statistical data associated with requestor
entities using one or more curve fitting techniques, i.e., constructing a curve
or mathematical function. See Spec ¶¶ 40, 74–77; Fig. 4A. Hereinafter we
refer to this step as “Step B.”
Claim 1 also recites “calculating a second statistical distribution of a
set of the parameters associated with the workers . . . using one or more
curve fitting techniques based on values of the set of parameters associated
the workers.” Similar to Step B, the process includes calculating a statistical
distribution from collected, received statistical data associated with worker
entities using curve fitting techniques, i.e., constructing a curve. See Spec ¶¶
40, 74–77; Fig. 4B. Hereinafter we refer to this step as “Step C.”
Claim 1 additionally recites “generating . . . a plurality of rules
indicative of interactions between the one or more entities associated with
the crowdsourcing platform” “by the one or more processors.” That is,
generating entity interaction rules utilizing the processor (see Step A
(supra)). See Spec. ¶¶ 77–78. Further, claim 1 recites “generating a non-
deterministic set of rules based on at least one of the first statistical
distribution and the second statistical distribution”; i.e., generating the entity
interaction rules includes generating a non-deterministic set of rules from the
statistical distributions. The non-deterministic rules are statistical models
generated based on statistical data as opposed to deterministic rules that are
mathematical equations. In other words, the non-deterministic rules are
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probabilistic (rely on and probabilities), not certain. See Spec. ¶¶ 78, 82–84.
Hereinafter we refer to these steps as “Step D” and “Step D1,” respectively.
Claim 1 also recites “estimating . . . a first level of service of the
crowdsourcing platform based on the plurality of rules over a predefined
time period” “by the one or more processors.” In other words, the process
includes estimates a first level of service (of the crowdsourcing platform)
over a predefined time period based on the rules. The estimation is
performed by the processor(s) (see Step A (supra)). See Spec. ¶ 91.
Hereinafter we refer to this step as “Step E.”
Claim 1 further recites “receiving an observed level of service of the
crowdsourcing platform based on processing of one or more tasks by the
crowdsourcing platform during the predefined time-period.” That is, the
process receives data (observations or measurements) concerning the level
of service provided by the crowdsourcing platform while performing one or
more tasks during the predefined time-period, i.e., receiving data collected
from observing the crowdsourcing platform’s performance. See Spec. ¶¶ 93,
99–101. Hereinafter we refer to this step as “Step F.”
Claim 1 modifies the rules (see Step D) in order to more accurately
estimate a level of service (see Step E) that corresponds to an observed level
of service (see Step F). Claim 1 recites “modifying . . . the plurality of rules
based on a comparison between the first level of service and the observed
level of service . . . wherein the modified plurality of rules are used to
simulate task processing by the crowdsourcing platform for potential tasks.”
In other words, the process includes modifying the entity interaction rules
based on a comparison between the estimated first level of service and the
observed level of service. The estimation is performed by the processor(s)
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(see Step A (supra)). See Spec. ¶¶ 94, 98–105. Hereinafter we refer to this
step as “Step G.”
Claim 1 also recites “varying one or more characteristics of at least
one of the first statistical distribution and the second statistical distribution
based on a comparison between the first level of service and the observed
level of service of the crowdsourcing platform.” In other words, the
modification sub-process further includes varying characteristics of the
statistical distributions (see Step B and Step C) based on the comparison (see
Step G). Hereinafter we refer to this step as “Step G1.”
Claim 1 also recites “modifying the non-deterministic set of rules
based on the variation in the one or more characteristics of at least one of the
first statistical distribution and the second statistical distribution.” That is,
the modification sub-process further includes modifying the generated non-
deterministic entity interaction rules (see Step D1) based on the variation in
the characteristics (on the modification) of the statistical distributions.
Hereinafter we refer to this step as “Step G2.”
Finally, Claim 1 recites “simulating a processing time for the
crowdsourcing platform to complete the potential tasks based on current
conditions of the crowdsourcing platform and the modified plurality of rules,
wherein the simulated processing time is presented to a provider of the
potential tasks.” In other words, the process includes simulating
(performing a simulation of) a processing time for the crowd sourcing
platform (to complete a potential task or tasks) based on the modified entity
interaction rules (see Step G) and presenting the results (simulated
processing time) to task provider (the provider of the potential tasks)—i.e.,
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re-estimating the level of service using the modified rules. See Spec ¶¶ 107,
110. Hereinafter we refer to this step as “Step H.”
In summary, claim 1 recites a process for simulating a crowdsourcing
platform by receiving statistical data, calculating statistical distributions,
generating entity interaction rules, including non-deterministic entity
interaction rules, based on the statistical distributions, and simulating a
processing time for the crowd sourcing platform. Hereinafter, we refer to
this process as the “crowdsourcing simulation process.” This is consistent
with how Appellant describes the claimed invention—“the process of [claim
1] leads to ‘a generation of an efficient simulation model for simulating a
crowdsourcing platform.’” Appeal Br. 20 quoting (Spec. ¶ 119).
Appellant’s contentions (supra) focus on the Examiner’s purported
failure to properly characterize claim 1. See, e.g., Appeal Br. 16–26. Here,
in rejecting the claims (in particular claim 1) under 35 U.S.C. § 101, the
Examiner analyzed the claims using the Mayo/Alice two-step framework,
consistent with the guidance set forth in the USPTO’s “2014 Interim
Guidance on Patent Subject Matter Eligibility,” 79 Fed. Reg. 74618 (Dec.
16, 2014), in effect at the time the rejection was made, i.e., on October 16,
2017. The Examiner notified Appellant of the reasons for the rejection
“together with such information and references as may be useful in judging
of the propriety of continuing the prosecution of . . . [the] application.” 35
U.S.C. § 132. See Final Act. 4–6. In doing so, the Examiner set forth a
prima facie case of unpatentability such that the burden of production shifted
to Appellant to demonstrate that the claims are patent-eligible.
Appellant also contends (supra) claim 1 is not a purely mental process
and could not be accomplished using a pen and paper (see Appeal Br. 20–
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22; Reply Br. 2–4), and that the Examiner failed to glean from claim 1 (and
the other pending claims) that the claims recite a technological improvement
(see, e.g., Appeal Br. 16–26). Claim 1, however, recites no substantive
limitations on how the crowdsourcing simulation process calculates
statistical distributions, generates entity interaction rules based on the
statistical distributions, or simulates a processing time for the crowd
sourcing platform. The limitations are entirely functional in nature, or
characterize various data utilized in Steps A, B, C, D, D1, E, F, G, G1, G2,
and H (supra). A person can perform the functions of limitations A–H
(delineated above) mentally, or by using pen and paper. See, e.g.,
Appellant’s Figs. 3, 4A, 4B, 5. Nowhere does Appellant point to specific
claim limitations that distinguish over a human process.
Although Appellant contends the claims describe purported
technological improvements or advances provided by the recited
crowdsourcing simulation process, claim 1 (and the other pending claims)
does not explicitly recite any specific improvements to technology, i.e.,
performing any improved processing or analysis. Claim 1, instead, simply
recites receiving data, analyzing data (performing statistical analysis) and
calculating statistical distributions, calculating entity interaction rules from
the distributions, and estimating a level of service (e.g., a completion time)
from the rules. In each instance, the particular means of accomplishing the
functionality is not recited in the claim. The processors, transceiver, and
communication network (recited in Step A) are additional elements that are
not part of the abstract idea analysis.
Performing data analysis, as well as the collection and provision
(outputting) of information related to such analysis, has been determined by
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our reviewing court to be an abstract concept (a mental process) that is not
patent eligible. Indeed, even if such analysis requires one to access and
gather data from a database or utilize a pen and paper in the analysis (such as
to graphically represent a data set), such analysis may still be an abstract
mental process. See CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d
1366, 1372 (Fed. Cir. 2011) (“[E]ven if some physical steps are required to
obtain information from the database . . . such data-gathering steps cannot
alone confer patentability.” A claim focused on verifying credit card
transaction information is directed to “unpatentable mental processes”
because the claim’s steps “can be performed in the human mind, or by a
human using a pen and paper.”); see also SAP Am., Inc. v. InvestPic, LLC,
898 F.3d 1161, 1165, 1167–68 (Fed. Cir. 2018) (Claims reciting “[a] method
for providing statistical analysis” (id. at 1165), were determined to be
“directed to an abstract idea” (id. at 1168). “As many cases make clear,
even if a process of collecting and analyzing information is limited to
particular content or a particular source, that limitation does not make the
collection and analysis other than abstract” (id. (citation and quotation marks
omitted)); Intellectual Ventures I LLC v. Capital One Fin. Corp., 850 F.3d
1332, 1340 (Fed. Cir. 2017) (identifying the abstract idea of collecting,
displaying, and manipulating data); Elec. Power Grp., LLC v. Alstom S.A.,
830 F.3d 1350, 1354 (Fed. Cir. 2016) (characterizing collecting information,
analyzing information by steps people go through in their minds, or by
mathematical algorithms, and presenting the results of collecting and
analyzing information, without more, as matters within the realm of abstract
ideas); Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat’l
Ass’n, 776 F.3d 1343, 1345, 1347 (Fed. Cir. 2014) (finding the “claims
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generally recite . . . extracting data . . . [and] recognizing specific
information from the extracted data” and that the “claims are drawn to the
basic concept of data recognition”); Bancorp Servs., L.L.C. v. Sun Life
Assurance Co. of Can. (U.S.), 687 F.3d 1266, 1278 (Fed. Cir. 2012) (“[T]he
fact that the required calculations could be performed more efficiently via a
computer does not materially alter the patent eligibility of the claimed
subject matter.”).
Further, the exchange of information to simulate a crowdsourcing
platform, which is the focus of Appellant’s claims may be categorized as
certain methods of organizing human activity. Appellant’s Specification
describes crowdsourcing as “distributing tasks by soliciting the participation
of loosely defined groups of individual crowdworkers” (Spec. ¶ 20; see
Spec. ¶¶ 2, 117) and a crowdsourcing platform as “a business application,
wherein a broad, loosely defined external group of people, communities, or
organizations provide solutions as outputs for any specific business
processes received by the application as inputs” (Spec. ¶ 21; see Spec. ¶¶ 2,
117). The Supreme Court additionally guides that contractual relations, like
crowdsourcing, constitute “a fundamental economic practice long prevalent
in our system of commerce.” Bilski v. Kappos, 561 U.S. 593, 611 (2010);
see also Alice, 573 U.S. at 221–22. Although Appellant contends claim 1
recites technical solutions to technical problems (see Appeal Br. 19) and
“the simulation and modeling can be utilized to improve the performance of
the crowdsource environments, such as selecting crowdworkers and routing
work tasks in the computer network” (Appeal Br. 20), Appellant’s
Specification shows that the focus of Appellant’s claims is a process of
organizing human activity. Thus, claim 1 is directed to a combination of
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abstract ideas, including methods of organizing human activity and mental
processes.
In summary, we conclude Appellant’s claim 1 recites a judicial
exception (USPTO’s Step 2A, Prong 1; see 2019 Revised Guidance).
Specifically, claim 1 recites a process for simulating a crowdsourcing
platform by receiving statistical data, calculating statistical distributions,
generating entity interaction rules, and simulating a processing time (level of
service) for the crowd sourcing platform. The crowdsourcing simulation
process consists of mental processes performed in the human mind (or
utilizing pen and paper) including observation, evaluation, or judgment. See
2019 Revised Guidance, 84 Fed. Reg. at 52, 53 (listing “[m]ental
processes—concepts performed in the human mind (including an
observation, evaluation, judgment, opinion)” as one of the “enumerated
groupings of abstract ideas” (footnote omitted)). The revised guidance
explains that “mental processes” include acts that people can perform in
their minds or using pen and paper, even if the claim recites that a generic
computer component performs the acts. See 2019 Revised Guidance, 84
Fed. Reg. at 52 n.14 (“If a claim, under its broadest reasonable
interpretation, covers performance in the mind but for the recitation of
generic computer components, then it is still in the mental processes
category unless the claim cannot practically be performed in the mind.”).
Because each of the limitations discussed above encompasses an act that
people can practically perform in their minds or using pen and paper, claim
1 recites mental processes. Appellant’s arguments have not persuaded us
otherwise.

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Practical Application
We next consider whether claim 1 integrates the abstract idea into a
practical application (USPTO’s Step 2A, Prong 2). See Revised Guidance,
84 Fed. Reg. at 51. In doing so, we consider whether there are any
additional elements beyond the abstract idea that, individually or in
combination, “integrate the [abstract idea] into a practical application, using
one or more of the considerations laid out by the Supreme Court and the
Federal Circuit.” Revised Guidance, 84 Fed. Reg. at 54–55.
Appellant’s claim 1 recites additional elements beyond the abstract
crowdsourcing simulation process (the judicial exception) (supra). The
additional elements in claim 1 include the recited “processors,”
“transceiver,” and “communication network”—in particular the processor(s),
which perform the functionality of Steps A, D, E, and G. The written
description indicates that each of these elements encompass commonplace
generic components. See Spec. ¶¶ 49–53; Fig. 2; see also Spec. ¶¶ 35–48;
Fig. 1. Appellant does not describe the “processors,” “transceiver,” and
“communication network” with any specificity. For example, Appellant’s
Specification describes the “processor 202” as including “suitable logic,
circuitry, and/or interfaces that are operable to execute one or more
instructions stored in the memory . . . to perform predetermined operations”
and that the “processor 202 may be implemented using one or more
processor technologies known in the art.” Spec. ¶ 51.
Other than disclosing these additional elements performing their
accustomed functions utilizing standard techniques—the processor receiving
(statistical) data, and the processor performing data analysis and
manipulation (generating entity interaction rules and estimating a level of
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service (processing completion time) using undisclosed and unclaimed
algorithms)—the written description describes these components in
functional, result-oriented terms with no technical details. See, e.g., Spec.
¶¶ 49–53 (describing operations performed by the processor, transceiver,
and network). These descriptions show that additional elements are generic.
See Hybritech Inc. v. Monoclonal Antibodies, Inc., 802 F.2d 1367, 1384
(Fed. Cir. 1986) (“[A] patent need not teach, and preferably omits, what is
well known in the art.”); Intellectual Ventures I LLC v. Erie Indem. Co., 850
F.3d 1315, 1331 (Fed. Cir. 2017) (“The claimed mobile interface is so
lacking in implementation details that it amounts to merely a generic
component (software, hardware, or firmware) that permits the performance
of the abstract idea, i.e., to retrieve the user-specific resources.”).
Appellant contends claim 1 (as well as other pending claims)
“improve[s] a technological process” (Appeal Br. 17), “improve[s] the
performance of the crowdsource environments” (Appeal Br. 20), “recite[s] a
technological improvement” (Appeal Br. 21). See Appeal Br. 17–22; Reply
Br. 2–3. Specifically, Appellant contends “the Office failed to consider
technological problems identified by the Specification and the solutions to
those problems, which are appropriately claimed” (Appeal Br. 19), in that
the Specification describes “simulation and modeling can be utilized to
improve the performance of the crowdsource environments, such as
selecting crowdworkers and routing work tasks in the computer network”
and claim 1 “specifically recite[s] this solution” (Appeal Br. 20). Appellant
also contends (at length) that claim 1 and the other pending claims) are
analogous to the claims found patent-eligible in McRO. See Appeal Br. 16–
26; Reply Br. 2–4. In other words, the claims recite a technological
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improvement that amounts to more than simply utilizing a computer as a
tool to accomplish the crowdsourcing simulation process.
Appellant’s contentions correspond to the reasoning in MPEP
§§ 2106.05(a)–(c), where additional elements integrate the judicial exception
into a practical application. We, however, disagree with Appellant’s
contentions. Appellant’s additional elements, in particular the processor, do
not apply or use the crowdsourcing simulation process (the judicial
exception) in a manner that imposes a meaningful limit on the judicial
exception, such that it is more than a drafting effort designed to monopolize
the exception. See Alice, 573 U.S. at 221–24 (citing Mayo, 566 U.S. at 78–
85). Rather, Appellant’s claim recites a generic computer element (a
processor or processors) that is utilized as a tool to carry out the functions
recited in the crowdsourcing simulation process—receiving statistical data,
performing statistical analysis and calculating statistical distributions,
calculating entity interaction rules from the distributions, and estimating a
level of service (e.g., a task completion time) from the rules. Utilizing a
computer as a tool to perform common data processing functions that are
part of a mental process (an abstract idea) does not impose a meaningful
limit on the abstract idea. See MPEP § 2106.05(f); see also Alice, 573 U.S.
at 223 (finding “if [the] recitation of a computer amounts to a mere
instruction to implement an abstract idea on a computer that addition cannot
impart patent eligibility” (quotations and internal citations omitted)).
Appellant’s claim 1 can be distinguished from patent-eligible claims
such as those in Enfish that are directed to “a specific improvement to the
way computers operate.” Enfish, 822 F.3d at 1336. Appellant’s claims can
also be distinguished from patent-eligible claims such as those that solve a
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technology-based problem (see BASCOM Glob. Internet Servs., Inc. v.
AT&T Mobility LLC, 827 F.3d 1341, 1349–52 (Fed. Cir. 2016)), or a method
“rooted in computer technology in order to overcome a problem specifically
arising in the realm of computer [technology]” (DDR Holdings, LLC v.
Hotels.com, L.P., 773 F.3d 1245, 1257 (Fed. Cir. 2014)). Contrary to
Appellant’s arguments (see supra and Appeal Br. 29–32 (contending the
claims recite an “inventive concept” that is “significantly more” than the
abstract idea), claim 1 is not a technological improvement or an
improvement in a technology. Appellant’s claim 1 does not “improve the
functioning of the computer itself” or “any other technology or technical
field.” Alice, 573 U.S. at 225. Nor does it provide a technological solution
to a technological problem. See DDR Holdings, 773 F.3d at 1257; MPEP
§ 2106.05(a). Appellant fails to sufficiently and persuasively explain how
the instant claims are directed to an improvement in the way computers
operate, nor has Appellant identified any technical advance or improvement
or specialized computer components. See Appeal Br. 16–26; Reply Br. 2–4.
As discussed supra, nothing in claim 1 precludes a human from
performing the crowdsourcing simulation process. Performing such data
analysis functionality is the reason computers exist. The mere automation of
a process that can be performed by a human is not sufficient to show an
improvement in computer functionality, and the fact that a computer may
increase efficiency—by modeling and simulating the crowdsource
environment (see Appeal Br. 19–21, 24–25 (citing Spec. ¶¶ 3, 119))—does
not change the abstract-idea analysis. See Intellectual Ventures I LLC v.
Capital One Bank (USA), 792 F.3d 1363, 1370 (Fed. Cir. 2015) (holding
that “merely adding computer functionality to increase the speed or
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efficiency of the process does not confer patent eligibility on an otherwise
abstract idea”); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363
(Fed. Cir. 2015) (“[R]elying on a computer to perform routine tasks more
quickly or more accurately is insufficient to render a claim patent eligible.”);
see also FairWarning, 839 F.3d at 1095.
Appellant misconstrues the relevant precedent, particularly McRO.
Even if, arguendo, Appellant’s claimed process includes an (undisclosed)
improved algorithm for modeling (generating rules) and simulating a
processing completion time (estimating a level of service)—which we did
not find (supra)—claim 1 does not specify any improvement in how a
computer (the processor) performs the underlying data processing and
analysis necessary to perform the algorithm. In other words, only the
abstract ideas in claim 1 are potentially new (although we make no
determination as to novelty or obviousness), not the way a computer (the
processor) operates.
In summary, “the focus of the claims is not on such an improvement
in computers as tools, but on certain independently abstract ideas that use
computers as tools.” Elec. Power Grp., 830 F.3d at 1354; see also MPEP
§ 2106.05(f) (emphasis omitted) (instructing Examiners to consider
“[w]hether the claim invokes computers or other machinery merely as a tool
to perform an existing process” in determining whether the claim recites
mere instructions to apply the exception), cited in 2019 Revised Guidance,
84 Fed. Reg. at 55, n.30. Thus, we conclude the claims are directed to an
abstract idea that is not integrated into a practical application.
Inventive Concept
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Having concluded Appellant’s claims are directed to an abstract idea
under the 2019 Revised Guidance (Step 2A analysis), we consider whether
claim 1 has an inventive concept, that is, whether the claim has additional
elements that “‘transform the nature of the claim’ into a patent-eligible
application.” Alice, 573 U.S. at 217 (quoting Mayo, 566 U.S. at 78, 79). As
discussed above, this requires us to evaluate whether the additional claim
elements add “a specific limitation or combination of limitations that are not
well-understood, routine, conventional activity in the field” or “simply
append[] well-understood, routine, conventional activities previously known
to the industry, specified at a high level of generality.” Revised Guidance,
84 Fed. Reg. at 56. We evaluate the elements of the claims “individually
and ‘as an ordered combination.’” Alice, 573 U.S. at 217 (quoting Mayo,
566 U.S. at 78, 79). See also, BASCOM, 827 F.3d at 1350 (“an inventive
concept can be found in the non-conventional and non-generic arrangement
of known, conventional pieces.”).
The Examiner determined that all the limitations of Appellant’s claim
1 were “directed to a judicial exception . . . without significantly more”
(Final Act. 4), and the process steps of claim 1 and the other pending claims
“require nothing more than a generic computer to perform routine and
conventional computer functions.” (Final Act. 6). See Final Act. 4–6; Ans.
4–5.
Appellant, on the other hand, reiterates portions of the Specification
(see Appeal Br. 30 (citing Spec. ¶ 119)) and the limitations of claim 1 and
contends claim 1 and the other pending claims “recite a specific, discrete
implementation of improving crowdsource processes,” which is
“‘significantly more’ than an abstract idea” (Appeal Br. 31) similar to
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BASCOM and DDR Holdings. See Appeal. Br. 29–32. Appellant also
contends “the Office’s allegations about concepts that are conventional or
well-known are not supported by evidence made of record” (Appeal Br. 21)
and did not provide sufficient evidence that the claim limitations recite well
understood, routine, or conventional activities. See Appeal Br. 20–22.5
Appellant fails to persuade us of error in the Examiner’s rejection
with respect to the second Alice step (USPTO’s Step 2B). We agree with the
Examiner that Appellant’s claim 1 (and the other pending claims) does not
evince an “inventive concept” that is significantly more than the abstract
idea itself. In particular, Appellant fails to explain how the additional
elements (above) add specific limitations beyond the judicial exception that
are not well-understood, routine, and conventional in the field.
As previously discussed, claim 1 (and the other pending claims)
merely recites additional non-abstract elements (above)—specifically the
processor(s), transceiver, and communication network—generic computer
elements, in particular the processor, that carry out common data processing
functions recited in the crowdsourcing simulation process (the abstract idea).
Specifically, Appellant’s Specification describes a computer system (not
recited in the claims) as a collection of conventional (generic) computer
components performing traditional computer functions—these components

5 Appellant’s Reply Brief was filed after the publication of the Berkheimer
decision (Berkheimer v. HP Inc., 881 F.3d 1360 (Fed. Cir. 2018)) and the
USPTO’s Berkheimer Memorandum (Changes in Examination Procedure
Pertaining to Subject Matter Eligibility, Recent Subject Matter Eligibility
Decision (Berkheimer v. HP, Inc.) (April 19, 2018) available at
https://www.uspto.gov/sites/default/files/documents/memo-berkheimer-
20180419.PDF. Appellant makes no explicit arguments with respect to
Berkheimer.
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include the above-discussed processor. See, e.g., Spec. ¶¶ 49–53; Fig. 2; see
also Spec. ¶¶ 35–48; Fig. 1. Also, to the extent that the written description
describes the functions performed by these elements, Appellant’s
Specification describes the functions at a high level of generality and largely
does not describe the particulars of how the claimed invention implements
these functions. See, e.g., Spec. ¶¶ 55–103 (describing the functions in the
crowdsourcing simulation process). Such conventional computer processes
operating on conventional computer hardware “do not alone transform an
otherwise abstract idea into patent-eligible subject matter.” FairWarning,
839 F.3d at 1096 (citing DDR Holdings, 773 F.3d at 1256); see also
Berkheimer Memorandum at 3 (explaining that a specification that describes
additional elements “in a manner that indicates that the additional elements
are sufficiently well-known that the specification does not need to describe
the particulars of such additional elements to satisfy 35 U.S.C. § 112(a)” can
show that the elements are well understood, routine, and conventional).
Appellant does not direct us to any disclosure in the Specification that
indicates the additional elements, either individually or as an ordered
combination, perform anything other than well-understood, routine, and
conventional processing functions, such as generating and manipulating
data. See Inventor Holdings, LLC v. Bed Bath & Beyond, Inc., 876 F.3d
1372, 1378 (Fed. Cir. 2017) (holding that considering claims reciting data
retrieval, analysis, modification, generation, display, and transmission as an
“‘ordered combination”’ reveals that they “amount to ‘nothing significantly
more’ than an instruction to apply [an] abstract idea” using generic computer
technology) (internal citation omitted). In short, as previously discussed,
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claim 1 (and the other pending claims) does no more than use generic
hardware to implement the claimed abstract idea.
To the extent Appellant contends the Examiner failed to comply with
the requirements of the Berkheimer decision (supra), we disagree. The
Examiner generally cited to Appellant’s Specification as well as case
precedent to support the Examiner’s determinations that the claims recite
well-understood, routine, and conventional components and activities. See
Final Act. 6 (citing FairWarning and Digitech); Ans. 4–5.
For at least the reasons above, we are not persuaded of Examiner error
in the rejection of claim 1 under 35 U.S.C. § 101. Thus, we sustain the
Examiner’s rejection under § 101 of independent claim 1, independent
claims 13, 15, and 22, and dependent claims 3–12, 14, 17–20, 23, and 24,
which depend from claims 1, 13, and 15, respectively, and which were not
separately argued with specificity.
CONCLUSION
For the reasons discussed above, we determine that claims 1, 3–15,
17–20, and 22–24 are directed to an abstract idea and do not demonstrate an
inventive concept.
Appellant has not shown that the Examiner erred in rejecting claims 1,
3–15, 17–20, and 22–24 under 35 U.S.C. § 101. We therefore sustain the
Examiner’s rejection of claims 1, 3–15, 17–20, and 22–24 under § 101.
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CONCLUSION SUMMARY
In summary:
Claims
Rejected
35 U.S.C. § Basis  Affirmed Reversed
1, 3–15, 17–
20, 22–24
§ 101 Eligibility 1, 3–15, 17–
20, 22–24

Overall
Outcome
1, 3–15, 17–
20, 22–24

TIME PERIOD FOR RESPONSE
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a). See 37 C.F.R.
§ 1.136(a)(1)(iv).
AFFIRMED