DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim(s) 7-10, 14, and 16-31 are pending for examination. Claim(s) 1, 7, 9, 10, 14, and 19 have amended. Claim(s) 1-6, 11-13, and 15 have been cancelled. Claims 21-31 have been added. This action is Final.
Response to Arguments
Applicant's arguments filed 7/27/2026 have been fully considered but they are not persuasive.
Applicant Argues: Applicant respectfully traverses this rejection. Independent claim 7 is not directed to an abstract idea under Step 2A of the USPTO eligibility framework. Even assuming arguendo that some abstract concept were implicated, the claims integrate any alleged abstract idea into a practical application and further recite significantly more than any alleged judicial exception.
Examiner’s Response: The examiner respectfully disagrees for the reasons set forth below.
The § 101 rejection does not establish a prima facie case because it neither identifies nor analyzes the claim's additional elements.
Applicant Argues: The rejection is internally inconsistent and, for that reason, does not satisfy the
requirement of MPEP § 2106.07(a) that the Office articulate the basis for an eligibility rejection. At Step 2A, Prong Two, the Office states that claim 7 "does not recite any additional elements," and concludes on that basis that there is no integration of the alleged abstract idea into a practical application. See OA page 5, lines 17-19. At Step 2B, however, the Office states that "[t]he recitation of the additional elements is acknowledged, as identified above with respect to Prong 2 of Step 2A." See OA page 6, lines 4-6. These two statements are irreconcilable: the claim either recites additional elements that must be identified and analyzed, or it does not.
In fact, claim 7 recites additional elements beyond any alleged abstract idea, including at least (i) the work simulation through which a digital work sample is obtained, (ii) the qualitative scoring service that generates the qualitative data set, and (iii) the operation of mapping the quantitative and qualitative data sets into a multi-dimensional space to form a unique capabilities geometric object. By declaring that there are "no additional elements," the Office swept the entire claim into the asserted abstract idea and then performed no Prong Two analysis of the elements it subsequently acknowledged. That is precisely the methodology MPEP § 2106.04(d) prohibits: after identifying an exception at Prong One, the Office must identify the claim's additional elements and evaluate whether, individually and in combination, they integrate the exception into a practical application. Because that analysis was not performed, the Office has not made out a prima facie case, and withdrawal of the rejection is warranted on this basis alone.
Examiner’s Response: The examiner respectfully disagrees. The examiner has performed the additional analysis and as previously shown before amended the claim contained no additional elements. The digital work as argued above is now presented via amendment. As noted previously Claim 7 recited : A method for comparing a candidate's capability profile to a work profile, comprising: receiving a quantitative data set representing a quantitative scoring of a candidate's abilities based on a candidate's responses to problems presented in a work simulation; receiving a qualitative data set representing a qualitative scoring of the candidate's abilities as scored by a qualitative scoring service; mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object; comparing the unique capabilities geometric object to an ideal geometric object representing capabilities of an ideal candidate; and determining whether the unique capabilities geometric object deviates from the ideal geometric object in a plurality of capability areas in a positive, negative or neural amount. The examiner notes there are no additional elements presented in the previous claim set.
The examiner respectfully notes the claims have been amended now to recite for claim(s) 31, and similar representative claim(s) 7 and 30 use of a work simulation application and EEG readings from an EEG reader device and further use of machine learning that includes deep neural networks and a tree classifier. These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The rejection below again shows the abstract idea in Step 2A-Prong 1 and then how the additional elements in Step 2A-Prong does not impose any meaningful limits on practicing the abstract idea. Therefore the examiner finds this argument not persuasive.
The Pending Claims Comply with 35 U.S.C. § 101
Applicant Argues: Applicant submits that the pending claims are patent-eligible. "The Supreme Court in Mayo laid out a framework for determining whether an applicant is seeking to patent a judicial exception itself, or a patent-eligible application of the judicial exception. See Alice Corp., 134 S. Ct. at 2355, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. 66, 101 USPQ2d 1961)." (MPEP 2106(I). "The first part of the Mayo test is to determine whether the claims are directed to an abstract idea, a law of nature or a natural phenomenon (i.e., a judicial exception)." (MPEP 2106(I)). If the Office determines that the claim is directed to a judicial exception, "the second part of the Mayo test is to determine whether the claim recites additional elements that amount to significantly more than the judicial exception." (MPEP 2106(I)).
Examiner’s Response: The examiner respectfully disagrees for the reasons set forth below.
First Part - The Pending Claims are Not Directed to An Abstract Idea - Step 2A, Prong One.
Applicant Argues: The Office Action essentially recites the entirety of claim 7 and concludes that the claim recites managing personal behavior or relationships or interactions between people, or mental processes. This characterization oversimplifies the claim and ignores specific technological operations recited. The 2019 PEG contains the abstract idea classification of: "Certain methods of organizing human activity-fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)". (2019 PEG, page 52).
Applicant notes that the claim language is not included in the defined 2019 PEG classification of "Certain methods of organizing human activity", "commercial or legal interactions" or "managing personal behavior or relationships between people". The 2019 PEG states that "Claims that do not recite matter that falls within these enumerated groupings of abstract ideas should not be treated as reciting abstract ideas". (2019 PEG, page 53). Applicant submits that the pending claims do not recite the subject matter described in the enumerated groupings above. Instead, the pending claims recite limitations of "mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object", which is not an abstract idea that falls within any of the groupings defined by the 2019 Revised Guidance. The claim therefore recites a specific computational data-processing architecture, not merely "evaluating candidates" or "managing human activity." Therefore, because the pending claims do not recite an abstract idea, the pending claims are patent-eligible under 35 U.S.C. § 101 and should be allowed.
The claims recite specific technological processing operations. Claim 7 recites:
"mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object;"
"comparing the unique capabilities geometric object to an ideal geometric object representing capabilities of an ideal candidate by comparing areas or volumes;"
"determining whether the unique capabilities geometric object deviates from the ideal
geometric object in a plurality of capability areas in a positive, negative or neutral amount;" and
"selecting the capability profile of the candidate for automatic hiring or retention when the candidate profile does not deviate significantly in a negative amount from the unique capabilities geometric object."
These are concrete computational operations and a specific outcome of hiring or retaining a candidate by electronic means. The specification explains that the invention performs: multidimensional geometric modeling, Euclidean distance computations, weighted capability comparisons, statistical filtering, clustering analysis, machine-learning-based scoring, and classifier operations. See, e.g., paragraphs [0056]-[0069], [0073], and [0078].
The claims are therefore directed to a specific computerized analytical framework, similar to claims found eligible in: Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016); McRO, Inc. v. Bandai Namco Games, 837 F.3d 1299 (Fed. Cir. 2016); and Finjan, Inc. v. Blue Coat Systems, 879 F.3d 1299 (Fed. Cir. 2018). Like those cases, the present claims recite specific techniques for computerized data modeling and analysis rather than a generalized business objective.
Examiner’s Response: The examiner respectfully disagrees. The examiner notes that comparing a candidate’s capability profile to a work profile is noted fall under "Certain methods of organizing human activity” as it recites "managing personal behavior or relationships between people". The examiner notes the limitations as argued “mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object" are limitations that fall within the abstract idea. The examiner further notes mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object" are limitations that fall within the abstract idea. The examiner respectfully notes the claims have been amended now to recite for claim(s) 31, and similar representative claim(s) 7 and 30 use of a work simulation application and EEG readings from an EEG reader device and further use of machine learning that includes deep neural networks and a tree classifier. These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Therefore, the examiner finds this argument not persuasive.
Applicant Argues: The Office Action has argued that the claim falls with the mental processing group because it recites concepts performed in the human mind, including observations, evaluations, judgments, and opinions. The Office Action states that the claim limitations cover performance of the limitation in the mind but recites generic computer components. Applicant respectfully disagrees.
A correct Step 2A, Prong One analysis does not support treating claim 7 as directed to a mental process. In the Memorandum "Reminders on Evaluating Subject Matter Eligibility of Claims Under 35 U.S.C. § 101," issued by the Deputy Commissioner for Patents on August 4, 2025 to Technology Center 3600, among others, the Office instructed examiners to invoke the mental-process grouping only where a limitation can practically be performed in the human mind or with pen and paper, and cautioned against characterizing computationally complex or machine-based operations as mental steps. See also 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence (eff. July 17, 2024).
Claim 7 fails the mental-process test in at least three respects. First, the qualitative data set is, by the claim's terms, scored "by a qualitative scoring service"; the specification describes that service as employing machine learning, including deep neural networks and a long short- term memory recurrent neural network, to score subjective responses. A person does not perform that step in the mind. Second, mapping quantitative and qualitative data sets into a space of two or more dimensions to form a multi-dimensional geometric object-described in the specification as data modeled in N dimensions and compared using hyper-dimensional vector comparison-is not of a type practically performed mentally.
The August 4, 2025 Memorandum also directs examiners to distinguish claims that recite a judicial exception from those that merely involve one. To the extent the comparing and determining steps touch mathematics or evaluation, they operate upon a computer-generated data structure.
These operations are not practically performable in the human mind. The Federal Circuit has repeatedly held that claims are not mental processes merely because a human could theoretically attempt portions of the analysis. See McRO, 837 F.3d at 1318 ("the claimed process uses a combined order of specific rules that renders information into a specific format that is then used and applied to create desired results"). The present claims recite a specific computational framework that materially exceeds human mental capability.
Examiner’s Response: The examiner respectfully disagrees. The examiner notes by a qualitative scoring service and further mapping quantitative and qualitative data sets into a space of two or more dimensions to form a multi-dimensional geometric object encompass steps that a user can manually perform in the human mind or by a human using a pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “mental processes” grouping of abstract ideas. The examiner respectfully notes the claims have been amended now to recite for claim(s) 31, and similar representative claim(s) 7 and 30 use of a work simulation application and EEG readings from an EEG reader device and further use of machine learning that includes deep neural networks and a tree classifier. These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Therefore, the examiner finds this argument not persuasive.
First Part - The Claims Integrate Any Alleged Abstract Idea Into a Practical Application - Step 2A, Prong Two.
Applicant Argues: Assuming, arguendo, that the pending claims did recite a judicial exception that falls under the enumerated groupings of abstract ideas defined in the 2019 PEG, which Applicant strongly denies, the 2019 PEG states that "A claim is not "directed to" a judicial exception, and thus is patent-eligible, if the claim as a whole integrates the recited judicial exception into a practical application of that exception." (2019 PEG, page 53). In evaluating whether a judicial exception is integrated into a practical application of the judicial exception, the 2019 PEG states that, "Examiners evaluate integration into a practical application by: (a) Identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (b) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application". (2019 PEG, pages 54-55).
The 2019 Revised Guidance provides that one consideration which is indicative of a practical application of a judicial exception is "An additional element [that] reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field". (2019 PEG, page 55). Applicant submits that the pending claims recite limitations for an improvement in a computer-related technology. Namely, the pending claims are directed to improvements in computerized work simulation and candidate hiring systems.
The specification repeatedly explains that prior systems suffered from deficiencies including: unreliable self-reporting, interview bias, poor predictive capability, and inability to process qualitative capability data effectively. See paragraphs [0002]-[0005], [0033]-[0037]. The invention improves these systems through: computerized work simulation environments, multidimensional capability modeling, geometric capability analysis, machine-learning-assisted qualitative scoring, classifier-driven role matching and automated selection for hiring. The claims therefore improve the functioning of computerized candidate-evaluation systems themselves. This is analogous to the technological improvements recognized in: Enfish; CardioNet, LLC v. InfoBionic, Inc., 955 F.3d 1358 (Fed. Cir. 2020); and SRI Int'l, Inc. v. Cisco Sys., Inc., 930 F.3d 1295 (Fed. Cir. 2019).
In addition, claim 7 does not merely analyze information or re-format information but applies specific data transformations. The claim specifically transforms quantitative and qualitative simulation-derived datasets into multidimensional geometric objects representing capability profiles. The claims then apply geometric comparison techniques to those transformed structures. The specification explains that these geometric objects may include: polygonal capability representations, multidimensional capability vectors, weighted capability geometries, and Euclidean-distance-based comparisons. See paragraphs [0056]-[0060]. This is a practical technological implementation, not an abstract idea untethered from technological processing.
Dependent claims further recite particularized machine-learning implementations and reinforce practical application integration. For example: claim 7 recites deep neural networks; claim 16 recites decision tree classifiers; claim 19 recites attrition prediction using classifiers; and claim 20 recites clustering operations. These are concrete computational techniques. The Office Action incorrectly dismisses these limitations as generic computer implementation without evidentiary support. The claims do not merely invoke a generic computer as a tool. Rather, the claims employ specific computational architectures to perform multidimensional capability modeling and role matching.
Therefore, the pending claims are a practical application of the asserted judicial exception because the pending claims, when considered as a whole, include additional elements that reflect an improvement to a computer-related technology. Therefore, the pending claims are directed to a patent-eligible concept under 35 U.S.C. § 101 and should be allowed.
Examiner’s Response: The examiner respectfully notes the claims have been amended now to recite for claim(s) 31, and similar representative claim(s) 7 and 30 use of a work simulation application and EEG readings from an EEG reader device and further use of machine learning that includes deep neural networks and a tree classifier. These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea (i.e., work simulation, multidimensional capability modeling, geometric capability analysis, qualitative scoring, driven role matching and selection for hiring). See MPEP 2106.05(f). Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Therefore, the examiner finds this argument not persuasive.
Second Part - The Elements of each Claim Transform the Nature of the Pending Claims into Significantly More than a Judicial Exception - Step 2B.
Applicant Argues: Applicant submits that in accordance with the second part of the Mayo test, the featuresrecited in the pending claims, when considered both individually and as an ordered combination, recite additional elements that amount to significantly more than the judicial exception. "Limitations that the courts have found to qualify as "significantly more" when recited in a claim with a judicial exception include ... [a]dding a specific limitation other than what is well- understood, routine, conventional activity in the field, or adding unconventional steps that confine the claim to a particular useful application, e.g., a non-conventional and non-generic arrangement of various computer components for filtering Internet content, as discussed15 in BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1350-51, 119 USPQ2d 1236, 1243 (Fed. Cir. 2016)" (MPEP 2106.05(A)).
The Office Action analyzes the claim limitations individually but fails to evaluate the ordered combination of elements as required by BASCOM Global Internet Services, Inc. v. AT&T Mobility LLC, 827 F.3d 1341 (Fed. Cir. 2016). The claims recite a non-conventional combination involving: work-simulation-generated quantitative and qualitative datasets; multidimensional geometric capability object formation; geometric comparison operations, and selecting and hiring of a candidate profile. The specification repeatedly describes this framework as a novel system architecture and no novelty or obviousness rejection was received in the Office Action. See paragraphs [0056]-[0078]. The Office Action provides no evidence that this ordered combination was conventional.
Under Berkheimer v. HP Inc., 881 F.3d 1360 (Fed. Cir. 2018), whether claim elements are well-understood, routine, and conventional is a factual determination. The Office Action contains only conclusory assertions that the additional elements are "generic." The Office Action cites no evidence demonstrating that the claimed elements were conventional. Accordingly, the rejection fails to establish a prima facie case under Step 2B.
Consequently, claim 7 recites an inventive concept that is confined to a particular useful application, and goes well beyond merely claiming "an abstract idea" or claim elements performed in the mind as asserted by the Office Action. Even assuming, arguendo, that the pending claims were directed to an abstract idea as asserted by the Office Action, to which Applicant strongly denies, the pending claims, as a whole, include an inventive concept that is patent-eligible under 35 U.S.C. § 101 and the pending claims should be allowed.
The dependent claims recite additional technological limitations that materially reinforce eligibility. Examples include: Euclidean-distance calculations (claim 17), normalization computations (claim 18), decision tree classifiers (claims 16 and 19), and clustering algorithms (claim 20). These limitations further distance the claims from any alleged mental process or generalized business practice.
Accordingly, based on the foregoing, Applicant respectfully submits that pending claims 7-31 recite statutory subject matter pursuant to 35 U.S.C. § 101, and Applicant respectfully requests that the rejection of the claims under 35 U.S.C. § 101 be withdrawn.
Examiner’s Response: The examiner respectfully disagrees. The examiner has considered the claim as a whole. The examiner notes as amended the claim does not include any additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more to the exception. As discussed below with respect to integration of the abstract idea into a practical application, the additional elements of for Claim(s) 31, and similar representative claim(s) 7 and 30, i.e., use of a work simulation application and EEG readings from an EEG reader device and further use of machine learning that includes deep neural networks and a tree classifier; thus, amounts to no more than mere instructions to apply the exception using a generic computer component and do not add anything that is not already present when they are considered individually or in combination. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, under Step 2B, there are no meaningful limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself.
Further, the examiner never addressed any additional claim elements as well-understood, routine, and conventional, thus, the evidentiary requirement under Berkheimer is not applicable.
Therefore, the examiner finds this argument not persuasive.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 7-10, 14, and 16-31 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Step 1: claim(s) 7-20 are directed to process. Therefore, the claims are directed to statutory subject matter under Step 1 (Step 1: YES). See MPEP 2106.03.
Prong 1, Step 2A: Claim 7 taken as representative, recites at least the following limitations that recite an abstract idea:
A method for comparing a capability profile of a candidate to a work profile, comprising:
generating a quantitative data set representing a quantitative scoring of abilities of the candidate based on a responses of the candidate to problems and choice models presented using a work simulation
scoring a qualitative data set representing a qualitative scoring of the abilities of the candidate as scored by a qualitative scoring service, wherein the qualitative scoring service scores qualitative answers
mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object;
comparing the unique capabilities geometric object to an ideal geometric object representing capabilities of an ideal candidate by comparing areas or volumes;
determining whether the unique capabilities geometric object deviates from the ideal geometric object in a plurality of capability areas in a positive, negative or neutral amount;
selecting the capability profile of the candidate for
Claim 30 taken as representative, recites at least the following limitations that recite an abstract idea:
A method for comparing a capability profile of a candidate to a work profile, comprising:
generating a quantitative data set representing a quantitative scoring of abilities of the candidate based on responses of the candidate to problems and choice models presented using a work simulation
scoring a qualitative data set representing a qualitative scoring of the abilities of the candidate as scored by a qualitative scoring service, wherein the qualitative scoring service scores qualitative answers
mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object;
comparing the unique capabilities geometric object to an ideal geometric object representing capabilities of an ideal candidate by computing a match percentage using a Euclidean distance of capability values from role capability values, wherein the Euclidean distance is converted into a percent by normalizing the Euclidian distance according to a maximum distance possible;
determining whether the unique capabilities geometric object deviates from the ideal geometric object in a plurality of capability areas in a positive, negative or neutral amount;
selecting the capability profile of the candidate for
Claim 31 taken as representative, recites at least the following limitations that recite an abstract idea:
A method for comparing a capability profile of a candidate to a work profile, comprising:
generating a quantitative data set representing a quantitative scoring of abilities of the candidate based on responses of the candidate to problems and choice models presented using a work simulation
scoring a qualitative data set representing a qualitative scoring of the abilities of the candidate as scored by a qualitative scoring service, wherein the qualitative scoring service scores qualitative answers
filtering out capabilities of a candidate that are not statistically significant to success in the work profile, wherein the filtering out capabilities takes place before the unique capabilities geometric object is created;
mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object;
using a decision tree
determining an attrition value using the decision tree
comparing the unique capabilities geometric object to an ideal geometric object representing capabilities of an ideal candidate by comparing areas or volumes;
determining whether the unique capabilities geometric object deviates from the ideal geometric object in a plurality of capability areas in a positive, negative or neutral amount;
determining whether or not to recommend the capability profile of the candidate based on an aggregation of an amount of deviation measured using weighted capability areas and results of the decision tree
selecting the capability profile of the candidate for
The above limitations, under their broadest reasonable interpretation, fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, enumerated in MPEP 2106.04(a)(2)(II), in that they recite managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions). The broadest reasonable interpretation of these limitations for claim(s) 31, and similar representative claim(s) 7 and 30, includes generating a quantitative data set representing a quantitative scoring of abilities of the candidate based on responses of the candidate to problems and choice models presented using a work, wherein the quantitative data set includes a work sample and quantitative answers are sent to the quantitative scoring for scoring and entry in the capability profile of the candidate; scoring a qualitative data set representing a qualitative scoring of the abilities of the candidate as scored by a qualitative scoring, wherein the qualitative scoring service scores qualitative; filtering out capabilities of a candidate that are not statistically significant to success in the work profile, wherein the filtering out capabilities takes place before the unique capabilities geometric object is created; mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object; using a decision tree to determine whether qualitative attributes of the candidate fit a role; determining an attrition value using the decision tree to predict an attrition segment for a candidate based on the capabilities of the candidate; comparing the unique capabilities geometric object to an ideal geometric object representing capabilities of an ideal candidate by comparing areas or volumes; determining whether the unique capabilities geometric object deviates from the ideal geometric object in a plurality of capability areas in a positive, negative or neutral amount; determining whether or not to recommend the capability profile of the candidate based on an aggregation of an amount of deviation measured using weighted capability areas and results of the decision tree; selecting the capability profile of the candidate for automatic hiring or retention when the candidate profile does not deviate significantly in a negative amount from the unique capabilities geometric object and the decision tree classifier determines the candidate fits the role, thus, claim 31, and similar representative claim(s) 7 and 30, falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas as they recite managing personal behavior or relationships or interactions between people.
The above limitations, under their broadest reasonable interpretation, fall within the “Mental Processes” grouping of abstract ideas, enumerated in MPEP 2106.04(a)(2)(III), in that they recite as concepts performed in the human mind, including observations, evaluations, judgments, and opinions. Nothing in these claim element(s) precludes the step(s) from practically being performed in the mind. For example, the broadest reasonable interpretation of these limitations for claim(s) 31, and similar representative claim(s) 7 and 30, includes generating a quantitative data set representing a quantitative scoring of abilities of the candidate based on responses of the candidate to problems and choice models presented using a work, wherein the quantitative data set includes a work sample and quantitative answers are sent to the quantitative scoring for scoring and entry in the capability profile of the candidate; scoring a qualitative data set representing a qualitative scoring of the abilities of the candidate as scored by a qualitative scoring, wherein the qualitative scoring service scores qualitative; filtering out capabilities of a candidate that are not statistically significant to success in the work profile, wherein the filtering out capabilities takes place before the unique capabilities geometric object is created; mapping the quantitative data set and the qualitative data set into a space with two or more dimensions to form a unique capabilities geometric object; using a decision tree to determine whether qualitative attributes of the candidate fit a role; determining an attrition value using the decision tree to predict an attrition segment for a candidate based on the capabilities of the candidate; comparing the unique capabilities geometric object to an ideal geometric object representing capabilities of an ideal candidate by comparing areas or volumes; determining whether the unique capabilities geometric object deviates from the ideal geometric object in a plurality of capability areas in a positive, negative or neutral amount; determining whether or not to recommend the capability profile of the candidate based on an aggregation of an amount of deviation measured using weighted capability areas and results of the decision tree; selecting the capability profile of the candidate for automatic hiring or retention when the candidate profile does not deviate significantly in a negative amount from the unique capabilities geometric object and the decision tree classifier determines the candidate fits the role, which, encompass steps that a user can manually perform in the human mind or by a human using a pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “mental processes” grouping of abstract ideas.
Accordingly, these claims recite an abstract idea. (Prong 1, Step 2A: YES). The types of identified abstract ideas are considered together as a single abstract idea for analysis purposes.
Prong 2, Step 2A: Limitations that are not indicative of integration into a practical application include: (1) Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)), (2) Adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)). Claim(s) 31, and similar representative claim(s) 7 and 30, recite i.e., use of a work simulation application and EEG readings from an EEG reader device and further use of machine learning that includes deep neural networks and a tree classifier. These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. These elements in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component and merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements, even in combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
As such, under Prong 2 of Step 2A, when considered both individually and as a whole, the limitations of Claim(s) 31, and similar representative claim(s) 7 and 30 are not indicative of integration into a practical application (Prong 2, Step 2A: NO). See MPEP 2106.04(d).
Since Claim(s) 31, and similar representative claim(s) 7 and 30 recites an abstract idea and fails to integrate the abstract idea into a practical application, Claim(s) 31, and similar representative claim(s) 7 and 30 is “directed to” an abstract idea under Step 2A (Step 2A: YES). See MPEP 2106.04(d).
Step 2B: The recitation of the additional elements is acknowledged, as identified above with respect to Prong 2 of Step 2A. These additional elements do not add significantly more to the abstract idea for the same reasons as addressed above with respect to Prong 2 of Step 2A.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of for Claim(s) 31, and similar representative claim(s) 7 and 30, i.e., use of a work simulation application and EEG readings from an EEG reader device and further use of machine learning that includes deep neural networks and a tree classifier; thus, amounts to no more than mere instructions to apply the exception using a generic computer component and do not add anything that is not already present when they are considered individually or in combination. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, under Step 2B, there are no meaningful limitations in claim(s) 31, and similar representative claim(s) 7 and 30 that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself (Step 2B: NO). See MPEP 2106.05.
Accordingly, under the Subject Matter Eligibility test, Claim(s) 31, and similar representative claim(s) 7 and 30 are ineligible.
Regarding Claims 8-10, 14, and 16-29, claim(s) 8-10, 14, and 16-29 further defines the abstract idea that is present in their respective independent claims and hence are abstract for at least the reasons presented above w/ respect to “Certain Methods of Organizing Human Activity” as the claims recite further concepts of managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions and/or further recite “Mental Processes” as the claims recite further concepts that can be performed in the human mind, including observations, evaluations, judgments, and opinions. These dependent claim does not include any additional elements that integrate the abstract idea into a practical application; as such elements are recited at a high level of generality such that it amounts not more than mere instructions to apply the exception using a generic computer component (i.e., claim(s) 16 and 19 – tree classifiers claim 22 – high level machine learning models and/or claim 25 – description of the work simulation application presenting content and claim 26 – recurrent neural network w/ text/video response and claim 29 – reception of data from an external system). Even in combination, these additional elements do not integrate the abstract idea into a practical application and do no not amount to significantly more than the abstract idea itself. Thus, the aforementioned claims are not patent-eligible.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ASFAND M SHEIKH/Primary Examiner, Art Unit 3626
