DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . The following FINAL office action is in response to Applicant communication filed on 06/25/2026 regarding application 18/532,686. Claims 1, 4-7, 9, 12-15 and 17 have been amended. Claim 20 has been canceled. Claim 21 has been added as a new claim. have been canceled. Claims 1-19 and 21 are pending and have been rejected.
Response to Amendments
2. Applicant’s amendment filed on 06/25/2026 necessitated new grounds of rejection in this office action.
Response to Arguments
3. Applicant’s arguments, see page 9 of 14 filed on 06/25/2025, with respect to the 35 U.S.C. § 112 (b) Claim Rejections for Claims 4-7, 12-15 and 20 have been fully considered and are found to be persuasive. Therefore, the 35 U.S.C. § 112 (b) Claim Rejections for Claims 4-7, 12-15 and 20 withdrawn.
Response to 35 U.S.C. § 101 Arguments
4. Applicant’s 35 U.S.C. § 101 arguments, filed with respect to Claims 1-19 and 21 have been fully considered, but they are found not persuasive (see Applicant Remarks, Pages 9-13 of 14, dated 06/25/2026). Examiner respectfully disagrees.
Argument #1:
(A). Applicant argues that Claims 1-19 and 21 do not recite an abstract idea, law of nature of natural phenomenon under revised step 2a prong one of the 35 U.S.C § 101 analysis (see Applicant Remarks, Pages 9-10 of 14, dated 06/25/2026). Examiner respectfully disagrees.
Specifically, Applicant argues that the amended claim limitations of Independent Claims 1, 9 and 17 are not directed to an abstract idea because the claims when considered as a whole are directed to a specific technical system and method for collecting, normalizing and processing heterogeneous psychological and behavioral data through a machine learning model to generate and display personalized recommendations via a cross-application overlay interface. This is a concrete technical operation performed by a specifically configured computing device operating within a defined multi-system architecture (see Applicant Remarks, Page 9 of 14, dated 06/25/2026). Examiner respectfully disagrees.
The Applicant’s arguments have been fully considered, but they are found to be not persuasive. Here, for Independent Claims 1, 9 and 17, these steps are directed to the abstract idea of analyzing psychological and HR data to generate career recommendations, and the claim limitations fail to provide an inventive concept beyond generic computer implementation. Specifically, the claim encompasses the concept of mental processes and certain methods of organizing human activity.
The essence of the claim involves gathering psychological assessments, personality metrics, event data, and HR data, combining them to assess an individual, and providing a recommendation. This is a computerized version of a human mental process (analyzing how an employee feels/works to advise them) and a business/administrative practice (evaluating HR metrics and suggesting jobs).
Here is the breakdown of the claim limitation steps and their corresponding judicial exception groupings: Receiving PsyCap driver data and personality data: Corresponds to Mental Processes (observing, receiving, and evaluating human psychological/personal traits) and Certain Methods of Organizing Human Activity (gathering employee/business data). Providing/displaying GUI elements and receiving PsyCap pulse data: Falls under Certain Methods of Organizing Human Activity (conducting a survey/questionnaire) and Mental Processes (receiving user input). Receiving event data and HRMS data: Falls under Certain Methods of Organizing Human Activity (managing business, personnel, and employment data). Inputting data into a machine learning model: Falls under Mental Processes (correlating, analyzing, and synthesizing information). Displaying a third GUI element with recommendations: Falls under Certain Methods of Organizing Human Activity (managing personnel, making assignments, and organizing workflow).
The proper inquiry is whether the claim recites a judicial exception, not whether every claimed limitation can literally be performed mentally. The focus of Independent Claims 1, 9 and 17 remains directed toward collecting information regarding an employee's psychological characteristics, personality, experiences, organizational events, and HR information, evaluating that information using a predictive model, and providing recommendations or interventions based upon the evaluation.
More specifically, Independent Claims 1, 9 and 17 recites: receiving PsyCap driver information; receiving personality information; receiving employee pulse responses; receiving event information; receiving HR information; evaluating the collected information using a predictive model; and recommending interventions or opportunities. These limitations collectively describe evaluating information regarding people and making recommendations based upon that evaluation. Such activities constitute observations, evaluations, judgments, and opinions that fall within the mental process grouping identified in the 2019 PEG, even when performed using a computer. See Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016) (collecting information, analyzing information, and displaying results constitute abstract mental processes). Likewise, the claims recite managing employee development and workplace interventions, which fall within certain methods of organizing human activity, specifically managing personal behavior and relationships.
With respect to “Certain Methods of Organizing Human Activities” category, Examiner refers Applicant to MPEP § 2106.04 (a) (2) (II): “The sub-groupings encompass both activity of a single person and activity that involves multiple people, and thus, certain activity between a person and a computer may fall within the "certain methods of organizing human activity" grouping. It is noted that the number of people involved in the activity is not dispositive as to whether a claim limitation falls within this grouping.”
With respect to “Mental Processes” category, Examiner refers Applicant to MPEP § 2106.04 (a) (2) (III) (C): “Claims can recite a mental process even if they are claimed as being performed on a computer. The Examiner has reviewed Applicant’s Specification and determined that the claimed invention is described as concepts that are performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer (e.g., see Applicant’s Specification ¶ [0024]: “Indeed, the employee management system 102 may be any computer or processing device such as, a blade server, general-purpose personal computer (PC), Mac®, workstation, UNIX-based workstation, or any other suitable device.”), or 2) in a computer environment (e.g., see Applicant’s Specification ¶ [0027] and ¶ [0047]: “The interface 104 is used by the employee management system 102 for communicating with other systems in a distributed environment—including within the system 100—connected to the network 150 (e.g., customer device 132, information server(s) 144, and other systems communicably coupled to the network 150).”), or 3) is merely using a computer as a tool. Applicant argues that multiple databases prevent mental performance. This argument is not persuasive. Merely requiring information to originate from electronic databases does not remove an otherwise abstract mental evaluation from the mental process category. The Federal Circuit has repeatedly explained that merely collecting more information electronically before performing an abstract analysis does not confer eligibility. The focus of the claims remains analyzing employee information to generate recommendations.
Additionally, according to MPEP § 2106.04 (a) (2) (III) (B): “If a claim recites a limitation that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper, the limitation falls within the mental processes grouping, and the claim recites an abstract idea. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, 839 F.3d at 1139, 120 USPQ2d at 1474 (holding that claims to the mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper").”
Accordingly, Examiner maintains that Claims 1-19 and 21 are directed to abstract ideas under “Mental Processes” and “Certain Methods of Organizing Human Activities” Groupings under 35 U.S.C. § 101 Step 2A Prong 1.
Argument #2:
(B). Applicant argues that Claims 1-19 and 21 recite additional elements that integrate the judicial exception into a practical application under revised step 2a prong two of the 35 U.S.C. § 101 analysis (see Applicant Remarks, last ¶ of Page 10 thru 1st ¶ of Page 12, dated 06/25/2026). Examiner respectfully disagrees.
Specifically, Applicant argues that the amended claim limitations of Independent Claims 1, 9 and 17 integrate the idea into a practical application due to an improvement in the functioning of human capital management technology itself (see Applicant Remarks, last ¶ of Page 10, dated 06/25/2026). Examiner respectfully disagrees.
This argument is not persuasive. The claims merely recite inputting collected information into "a machine learning predictive model." The claims do not recite: any particular machine learning architecture, any improvement to machine learning, any new training technique, any improvement to model accuracy, any specialized neural network, any improved feature engineering, any improved computational efficiency, or any technological improvement to machine learning itself. Instead, the machine learning model is claimed solely as a generic analytical tool for processing employee information. The Federal Circuit has repeatedly held that merely applying generic artificial intelligence or machine learning to analyze information does not render claims patent eligible. See: SAP America, Inc. v. InvestPic, LLC, Electric Power Group and Recentive Analytics, Inc. v. Fox Corp court cases. Accordingly, the recited machine learning model merely performs the abstract analytical process using computer technology.
Independent Claims 1, 9 and 17: With respect to reliance on (e.g., “machine learning predictive model”) as an additional element shown in Independent Claims 1, 9 and 17 when considered both individually and as an ordered combination (as a whole) with these recited claim limitations, this additional element does not provide limitations that are indicative of integration into a practical application under step 2a prong 2 due to the following: (1) recites mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions by providing the results to the user on a computer (see MPEP § 2106.05 (f)) or (2) limiting a particular field of use or technological environment pertaining to organizing human activity/psychological assessment for evaluating employees through a subjective assessment process (evaluating employee psychology and performance) environment (see MPEP § 2106.05 (h)).
Moreover, with respect to Independent Claims 1, 9 and 17, certain/particular limitations shown recite (1) mere data gathering and (2) mere data transmitting/displaying, which when evaluated as additional elements, these activities at most amount to insignificant extra-solution activities (see MPEP § 2106.05 (g)).
Applicant argues that the claims improve human capital management technology. This argument is not persuasive. The alleged improvement concerns: predicting employee performance; measuring psychological capital; recommending interventions; and improving employee engagement. These are improvements to human resources management rather than improvements to computer technology. The claims do not improve the functioning of computers. Instead, generic computer components are used as tools to perform abstract employee assessment. Accordingly, the claims do not integrate the judicial exception into a practical application.
Accordingly, Examiner maintains that Claims 1-19 and 21 do not recite additional elements that integrate the judicial exception into a practical application under step 2a prong 2 of the 35 U.S.C. § 101 analysis.
Applicant argues that Independent Claims 1, 9 and 17 recite additional elements that integrate the judicial exception into a practical application under Revised Step 2A Prong Two according to the USPTO 2019 Revised Patent Subject Matter Eligibility Guidance and cites the case of McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-16 (Fed. Cir. 2016) as corroboration (see Applicant Remarks, last ¶ of Page 10 and 2nd ¶ of Page 11, dated 06/25/2026). Examiner respectfully disagrees.
The argument is not persuasive. McRO involved a specific set of rules that automatically generated improved animation without human animators. The present claims do not recite any specific rules governing the predictive model. Instead, Independent Claims 1, 9 and 17 merely recites: inputting data into a machine learning predictive model. No algorithm is recited. No specific predictive calculations are claimed. No technological rules are claimed. The claims therefore merely invoke generic predictive analytics. McRO is therefore distinguishable.
Applicant argues that Independent Claims 1, 9 and 17 recite additional elements that integrate the judicial exception into a practical application under Revised Step 2A Prong Two according to the USPTO 2019 Revised Patent Subject Matter Eligibility Guidance and cites the case of Enfish, LLC v. Microsoft Corp, 822. F.3d 1327 (Fed. Cir. 2016) as corroboration (see Applicant Remarks, 3rd ¶ of Page 11, dated 06/25/2026). Examiner respectfully disagrees.
Specifically, Applicant argues that the amended claims of Independent Claims 1, 9 and 17 reflect this same type of improvement to computer and data-processing functionality by requiring receiving heterogenous data from multiple disparate sources that is PsyCap driver data in a first data format, personality data in a second data format, pulse data in a first format, and event data in a third data format and converting that data into a standardized format before inputting it into a machine learning predictive model. Applicant argues that receiving multiple data formats and standardizing them constitutes a technological improvement similar to Enfish. This argument is not persuasive. The claims merely receive information originating from different databases. Although claim 21 recites converting data into a standardized format before input into the predictive model, the claims do not recite: any new database architecture; any new storage format; any new indexing technique; any improved memory organization; any improved communication protocol; any improvement to database retrieval; any reduction in processor utilization; any reduction in network traffic; or any other improvement to computer functionality.
Instead, the standardization merely prepares information for subsequent analysis. Normalizing information before analysis is a conventional data preprocessing step. The claims therefore merely use generic computer functionality as a tool to prepare information for abstract analysis. Unlike Enfish, the present claims do not improve the operation of the computer itself. Rather, they merely improve the quality of information being analyzed. Improving information content is not an improvement to computer technology. See: Electric Power Group and SAP America court cases.
Applicant’s reliance on Enfish, LLC v. Microsoft Corp, 822. F.3d 1327 (Fed. Cir. 2016) has been considered, but is not persuasive. Turning now to the “Enfish” case, Examiner reveals that the Federal Circuit did not find its claims as an eligible improvement, by simple virtue of mere allowing the computer to perform tasks not previously, but instead found a database improvement (see “Elec. Power Grp.p.1482 ¶2-¶3), further explain by configuring a memory according to a logical table that need not be stored contiguously in the computer memory, but instead appended with new columns that are available for immediate use through the creation of new column definition records, with one or more cells defined by the intersection of the rows and columns, and with the object identification number that, acting as a pointer of variable length between databases, to identify each said logical row, corresponding to a record of information (“Enfish LLC v. Microsoft Corp. , 118 USPQ2d 1684, U.S. Court of Appeals Federal Circuit, No. 2015-1244, May 12, 2016, 2016 BL 151342, 822 F.3d 1327”, hereinafter “Enfish” noting at p.1688 second to last ¶, pp. 1689-1690) providing a trifecta improvements in: increasing flexibility, providing faster search times, and smaller memory requirements (“Enfish” p.1690, second to last ¶) (emphasis added).
In Enfish, the claims improved the internal operation of the computer itself through a new self-referential database architecture. The present claims do not improve: database architecture;
processor operation; memory utilization; networking; storage; operating systems; or graphical rendering. Instead, the claims use conventional computing components to collect employee information and generate employee recommendations. Thus, the claims improve the content of employee assessments rather than computer technology. Accordingly, Enfish is inapplicable.
Indeed, as later elucidated by the Federal Circuit in “Elec. Power Grp”: “In Enfish, we applied the distinction to reject the § 101 challenge at stage one because the claims at issue focused not on asserted advances in uses to which existing computer capabilities could be put, but a particular database technique in how computers could carry out one of their basic functions of storage and retrieval of data (“Elec. Power Grp” p.1742 ¶3 last sentence citing “Enfish, 822 F.3d at 1335-36”; “Bascom, 2016 WL 3514158, at *5; cf. Alice, 134 S. Ct. at 2360”.
Whereas here, similar to “Elec. Power Grp” p.1742 ¶3 last sentence, 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 to allegedly allow the computer to perform the functions of “requiring receiving heterogenous data from multiple disparate sources that is PsyCap driver data in a first data format, personality data in a second data format, pulse data in a first format, and event data in a third data format and converting that data into a standardized format before inputting it into a machine learning predictive model” for teachings or following rules or instructions through using a computer in a human resource management system (HRMS) environment.
Applicant argues that Independent Claims 1, 9 and 17 recite additional elements that integrate the judicial exception into a practical application under Revised Step 2A Prong Two according to the USPTO 2019 Revised Patent Subject Matter Eligibility Guidance and cites the case of Core Wireless Licensing SARL v. LG Electronics, 880 F.3d 1356, 1362 (Fed. Cir. 2018) as corroboration (see Applicant Remarks, last ¶ of Page 11 thru 1st ¶ of Page 12, dated 06/25/2026). Examiner respectfully disagrees.
Applicant’s reliance on Core Wireless Licensing SARL v. LG Electronics, 880 F.3d 1356, 1362 (Fed. Cir. 2018) has been considered, but is not persuasive. Applicant points out that in the “Core Wireless” court case required that the application summary window listed a limited set of data, “each of the data in the list being selectable to launch the respective application and enable the selected data to be seen within the respective application” and “restrained the type of data that can be displayed in the summary window”. Examiner notes that the “Core Wireless case” "disclosed a specific technical manner of displaying a limited set of information to the user, rather than using conventional user interface methods to display a generic index on a computer. The court noted that prior art systems required a user to navigate through many different layers or views to access desired data or functionality, and that that process could "seem slow, complex and difficult to learn." In contrast, the court noted that the disclosed invention improves the efficiency of using the electronic device by permitting a limited list of common functions and commonly accessed stored data to be accessed directly from a main menu. Specifically, the application summary window addressed the problems associated with the small screen size by bypassing the additional levels of navigation necessitated by the small screen size. Examiner submits that while technological improvements need not to solely stem from: phoneme to keyframe lip synchronization in facial 3D animation in “McRO” supra, solved paging problem in small screen as in “Core Wireless” – supra it is still worth noting that each of “McRO” and “Core Wireless” raised above, are relevant in providing valuable insight to ascertain what actual technology is, and most importantly, to ascertain what constitutes deliberate improvement to actual technology or the computer itself as opposed to a mere entrepreneurial improvement. In this instant case however, Applicant merely argues in favor of Applicant merely argues in favor of an entrepreneurial best business practice of “displaying a first GUI element superimposed over a second GUI element from a separate third-party software application enabling cross-application data collection without disrupting the underlying application.” The important distinctions to note is that in the Core Wireless case, the problem statement focused on the limitations in the operation or function of prior art user interfaces caused by the small screens of certain computer devices. On the other hand, in the Trading Technologies cases, the problem statement focused on the types of information being provided to the user through the user interface. The information did not address any problem associated with a specific computer operation or characteristic, but rather a problem associated with the ability of the trader to carry out trading activities. Similarly, as in cited in the Trading Technologies case, Examiner points out that the Applicant has not addressed or pointed out any specific technical problem associated with a specific computer operation or characteristic. Here, in Independent Claims 1, 9 and 17, these claim limitations focus on the types of information which are being provided to the user through the graphical user interface (GUI) on the mobile electronic device. The claim limitations as recited in Independent Claims 1, 9 and 17 of the claimed invention governed what information is displayed and the formatting of that information. These limitations do not tie back to any particular technical problem and are not related to any specific computer operation or characteristic. The claims merely recite: displaying a GUI element over another GUI element with a hyperlink allowing user input. The claims do not recite: any improved graphical organization; any reduced navigation complexity; any improved device usability; any improved display efficiency; any improved interaction model; or any technological improvement to graphical interfaces. Unlike Core Wireless, the GUI merely serves as a vehicle for collecting user information and displaying recommendations. The GUI therefore performs insignificant extra-solution activity.
Argument #3:
(C). Applicant argues that Claims 1-19 and 21 recite additional elements that amount to significantly more than the recited judicial exceptions under revised step 2B of the 35 U.S.C. 101 analysis (see Applicant Remarks, Pages 12-13, dated 06/25/2026). Examiner respectfully disagrees.
Specifically, Applicant argues that amended claim limitations of Independent Claims 1, 9 and 17 recite significantly more than any alleged abstract idea because the relevant question is whether the additional elements, considered individually and as an ordered combination are WURC to a skilled artisan at the time of the invention and they cite Berkheimer v. HP Inc., 881 F.3d 1360, 1368-69 (Fed. Cir. 2018). Applicant respectfully submits that this factual question cannot be resolved against Applicant without evidentiary support and the Office Action provides none under 35 U.S.C. § 101 step 2B (see Applicant’s Remarks, Page 12, dated 06/25/2026). Examiner respectfully disagrees.
The argument is not persuasive. Examiner refers Applicant to Examiner’s 35 U.S.C. § 101 analysis section (e.g., Claim Rejections - 35 U.S.C. § 101 section shown below) shown for step 2B particularly for Independent Claims 1, 9 and 17. The claims do not recite additional elements that amount to significantly more than the recited judicial exceptions, because they are merely directed to the particulars of the abstract idea and likewise do not add significantly more to the above-identified judicial exceptions. The limitations are directed to limitations referenced in MPEP § 2106.05I.A. that are not enough to qualify as significantly more when recited in these claims with the abstract idea which include: (1) adding the words “apply it” (or an equivalent) with the judicial exception, (2) or mere instructions to implement an abstract idea on a computer and providing the results to the user on a computer, and (3) generally linking the use of the judicial exception to a particular technological environment or field of use.
Examiner refers Applicant to BSG Tech LLC v. Buyseasons Inc. decision (Aug. 15, 2018) court case noting that: “But the relevant inquiry is not whether the claimed invention as a whole is unconventional or non-routine. At Step two, we “search for an ‘inventive concept’… that is sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept] itself.” Alice, 134 S. Ct. at 2355 (internal quotation marks omitted) (quoting Mayo, 566 U.S. at 72-73). But this simply restates what we have already determined is an abstract idea. At Alice step two, it is irrelevant whether considering historical usage information while inputting data may have been non-routine or unconventional as a factual matter. As a matter of law, narrowing or reformulating an abstract idea does not add “significantly more” to it. See SAP Am., Inc. v. InvestPic, LLC. No. 2017-2081, slip op. at 14 (Fed. Cir. 2018). Applicant’s suggestion that specific limitations (or the claimed invention as a whole) must be shown to be well-understood, routine, and conventional to support the conclusion of subject matter ineligibility is not persuasive. Examiner submits that the question of novelty and non-obviousness evidence (application of prior art) is not relevant to the question of determining whether the claims as constructed contain an inventive concept. Lastly, Examiner cites the case of (Two-Way Media v. Comcast, (Fed. Cir. 2017)) and the District Court from this case concluded that “the proffered materials are irrelevant to the § 101 motion for judgment on the pleadings. None of the proffered materials addresses a § 101 challenge to claims of the asserted patents. The novelty and non-obviousness of the claims under §§ 102 and 103 does not bear on whether the claims are directed to patent-eligible subject matter under § 101. . . . Because the proffered materials are irrelevant to the instant § 101 issue, I have not considered them.” The appeal to Federal Circuit Court affirmed the District Court’s ruling that “eligibility and novelty are separate inquiries.”
Independent Claims 1, 9 and 17: With respect to reliance on (e.g., “machine learning predictive model”) as an additional element shown in Independent Claims 1, 9 and 17 when considered both individually and as an ordered combination (as a whole) with these recited claim limitations, this additional element does not amount to significantly more than the judicial exceptions under step 2B due to the following: (1) recites mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions by providing the results to the user on a computer (see MPEP § 2106.05 (f)) or (2) limiting a particular field of use or technological environment pertaining to organizing human activity/psychological assessment for evaluating employees through a subjective assessment process (evaluating employee psychology and performance) environment (see MPEP § 2106.05 (h)).
Moreover, with respect to Independent Claims 1, 9 and 17, certain/particular limitations shown recite (1) mere data gathering/receiving and (2) mere data transmitting/displaying, in which each of these claim limitations reflects mere insignificant extra-solution activities (see MPEP § 2106.05 (g)). Furthermore, these certain/particular claim limitations as demonstrated above for Independent Claims 1, 9 and 17 reflects Well-Understood, Routine and Conventional Activities (WURC) under MPEP § 2106.05 (d) ii: See Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec,838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359,1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
The additional elements of “machine learning” or “machine learning model” in Claims 1, 9 and 17 do not amount to significantly more than the judicial exceptions under step 2B due to being expressly recognized as Well-Understood, Routine and Conventional (WURC) in the art.
See for example; US PG Pub (US 2024/0321453 A1) hereinafter Funahashi, et. al. Funahashi notes at ¶ [0086]: “A commonly used method may be employed as the machine learning method. For example, a method such as decision tree, random forest, eXtreme gradient boosting (XGBoost), support vector machine (SBM), or neural network may be employed to calculate the parameters of the prediction models and thereby create the health management indicator prediction models.” At ¶ [0196]: For each of a plurality of subjects, the calculation unit 404 acquires a data set including the condition indicators, the motivation indicators, the work information, and the health management indicators. Then, the calculation unit 404 creates the prediction models 414 through analysis with a method such as multivariate analysis, Bayesian network, or machine learning with the condition indicators, the motivation indicators, and the work information as the explanatory variables and the health management indicators as the objective variables. See for example; Foreign Patent Application (EP 4207016 A1) hereinafter Ahmadi, et. al. Ahmadi at ¶ [0021]: “The machine learning algorithms determine correlations between the communication data and the surveys using customized algorithms derived from known machine learning algorithms. Labels of data to input into the machine learning algorithms are derived from onboarding surveys.” Correlations from the survey data may be determined by extracting known COPSOQ survey questions and correlations known in the art.
Rather, the additional elements—including: databases; GUIs; receiving information; displaying information; hyperlinks; predictive models; HRMS systems and computing devices—
are recited at a high level of generality and perform only their ordinary expected functions. No improvement to computer technology is recited. The ordered combination likewise merely follows the sequence of: collecting information; analyzing information; and displaying results.
Such ordered combinations have repeatedly been held abstract by the Federal Circuit. See Electric Power Group and SAP America court cases. Applicant has not identified any claim limitation that changes the functioning of the computer itself.
Moreover, Applicant argues that converting heterogeneous data into a standardized format provides a technical improvement. The argument is not persuasive. Claim 21 merely recites converting collected information into a standardized format before analysis. Data normalization is a preprocessing operation routinely performed before statistical analysis and machine learning. The claim does not specify: any particular normalization algorithm; any improved encoding; any new serialization technique; any improved storage format; or any improvement to computer processing. The "Standardized Format" Limitation (Dependent Claim 21): While formatting data sounds computational, claiming the idea of data normalization or data standardization at a high level of generality does not save the claim. Under RecogniCorp v. Nintendo, formatting, converting, or structuring data mathematically is an abstract concept unless the claim recites a specific technical improvement to database throughput or network efficiency. Because Claim 21 simply states the data is "converted into a standardized format" without explaining how (e.g., a novel compiler technique or specific data compression token architecture), it fails to integrate the idea into a practical application under step 2a prong 2 nor does this claim recite additional elements that are sufficient to amount to significantly more than the recited judicial exceptions under step 2B.
Therefore, the ordered combination of elements in the Dependent Claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself. Therefore, under Step 2B, Claims 1-19 and 21 do not include additional elements that are sufficient to amount to significantly more than the recited judicial exceptions. Thus, Claims 1-19 and 21 are ineligible with respect to the 35 U.S.C. § 101 analysis. Accordingly, Claims 1-19 and 21 do not recite an inventive concept.
Claim Rejections - 35 USC § 101
5. 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.
6. Claims 1-19 and 21 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1-19 and 21 are focused to a statutory category namely, a “process” or a “method” (Claims 1-8 and 21), a “system” or an “apparatus” (Claims 9-16) and a “computer program product” or an “article of manufacture” (Claims 17-19).
Step 2A Prong One: Independent Claims 1, 9 and 17 recites limitations that set forth the abstract idea(s), namely (see in bold except where strikethrough):
“” (see Independent Claim 9);
“” (see Independent Claim 9);
“” (see Independent Claim 17);
“receiving, , psychological capital (PsyCap) driver data that is stored in a first data format, wherein the PsyCap driver data includes one or more PsyCap drivers” (see Independent Claim 1);
“receiving, , personality data that is stored in a second data format” (see Independent Claim 1);
“displaying, , that is superimposed over a in which a link is provided that redirects a user to provide PsyCap pulse data” (see Independent Claim 1);
“receiving, , the PsyCap pulse data in a first format that is provided by the user through the link” (see Independent Claim 1);
“receiving, , event data in a third data format, wherein the event data includes one or more events” (see Independent Claim 1);
“receiving, , data ), wherein the data from the includes at least one of growth opportunities, team assignments, projects, work activities, goals, or accomplishments” (see Independent Claim 1);
“inputting, , the PsyCap driver data, the personality data, the PsyCap pulse data, the event data, and the data into a model to generate an assessment result” (see Independent Claim 1);
“displaying, and based on the assessment result, includes recommendation or intervention and a link to an opportunity managed by a third application” (see Independent Claim 1);
“receiving psychological capital (PsyCap) driver data that is stored in a first data format, wherein the PsyCap driver data includes one or more PsyCap drivers” (see Independent Claims 9 and 17);
“receiving personality data that is stored in a second data format” (see Independent Claims 9 and 17);
“displaying that is superimposed over a in which a link is provided that redirects a user to provide PsyCap pulse data” (see Independent Claims 9 and 17);
“receiving the PsyCap pulse data in a first format that is provided by the user through the link” (see Independent Claims 9 and 17);
“receiving event data in a third data format, wherein the event data includes one or more events” (see Independent Claims 9 and 17);
“receiving data ), wherein the data from the includes at least one of growth opportunities, team assignments, projects, work activities, goals, or accomplishments” (see Independent Claims 9 and 17);
“inputting the PsyCap driver data, the personality data, the PsyCap pulse data, the event data, and the data into a model to generate an assessment result” (see Independent Claims 9 and 17);
“displaying, based on the assessment result, includes recommendation or intervention and a link to an opportunity managed by a third application” (see Independent Claims 9 and 17).
Here, for Independent Claims 1, 9 and 17, these steps are directed to the abstract idea of analyzing psychological and HR data to generate career recommendations, and the claim limitations fail to provide an inventive concept beyond generic computer implementation. Specifically, the claim encompasses the concept of mental processes and certain methods of organizing human activity.
The essence of the claim involves gathering psychological assessments, personality metrics, event data, and HR data, combining them to assess an individual, and providing a recommendation. This is a computerized version of a human mental process (analyzing how an employee feels/works to advise them) and a business/administrative practice (evaluating HR metrics and suggesting jobs).
Here is the breakdown of the claim limitation steps and their corresponding judicial exception groupings:
Receiving PsyCap driver data and personality data: Corresponds to Mental Processes (observing, receiving, and evaluating human psychological/personal traits) and Certain Methods of Organizing Human Activity (gathering employee/business data).
Providing/displaying GUI elements and receiving PsyCap pulse data: Falls under Certain Methods of Organizing Human Activity (conducting a survey/questionnaire) and Mental Processes (receiving user input).
Receiving event data and HRMS data: Falls under Certain Methods of Organizing Human Activity (managing business, personnel, and employment data).
Inputting data into a machine learning model: Falls under Mental Processes (correlating, analyzing, and synthesizing information).
Displaying a third GUI element with recommendations: Falls under Certain Methods of Organizing Human Activity (managing personnel, making assignments, and organizing workflow).
Therefore, other than reciting (e.g., “Human Resource Management System (HRMS)” & “first GUI element” & “second GUI element” & “third GUI element” & “software application” & “first database” & “second database” & “one or more computers” & “one or more processors”, etc…), nothing in the claim elements precludes the steps from being performed as “Mental Processes” which pertains to (1) concepts performed in the human mind (including observations or evaluations or judgments) or (2) using pen and paper as a physical aid and additionally or alternatively as “Certain Methods of Organizing Human Activities” which pertains to (3) managing personal behavior or relationships or interactions between people (including teachings or following rules or instructions) or (4) fundamental economic principles or practices.
Therefore, at step 2a prong 1, Yes, Claims 1-19 and 21 recites an abstract idea. We proceed onto analyzing the claims at step 2a prong 2.
Step 2A Prong Two: With respect to Step 2A Prong Two of the eligibility inquiry (as explained in MPEP § 2106.04(d)), the judicial exception is not integrated into a practical application. Independent Claim 1 recites additional elements directed to: (e.g., “Human Resource Management System (HRMS)” & “first GUI element” & “second GUI element” & “third GUI element” & “software application” & “first database” & “second database”). Independent Claim 9 recites additional elements directed to: (e.g., “Human Resource Management System (HRMS)” & “first GUI element” & “second GUI element” & “third GUI element” & “software application” & “first database” & “second database” & “one or more computers” & “one or more processors”). Independent Claim 17 recites additional elements directed to: (e.g., “Human Resource Management System (HRMS)” & “first GUI element” & “second GUI element” & “third GUI element” & “software application” & “first database” & “second database” & “one or more processors”). These additional elements have been considered individually and in combination, but fail to integrate the abstract idea into a practical application because they amount to using computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment. See MPEP § 2106.05(f) and MPEP § 2106.05(h).
Independent Claims 1, 9 and 17: With respect to reliance on (e.g., “machine learning predictive model”) as an additional element shown in Independent Claims 1, 9 and 17 when considered both individually and as an ordered combination (as a whole) with these recited claim limitations, this additional element does not provide limitations that are indicative of integration into a practical application under step 2a prong 2 due to the following: (1) recites mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions by providing the results to the user on a computer (see MPEP § 2106.05 (f)) or (2) limiting a particular field of use or technological environment pertaining to organizing human activity/psychological assessment for evaluating employees through a subjective assessment process (evaluating employee psychology and performance) environment (see MPEP § 2106.05 (h)).
Moreover, with respect to Independent Claims 1, 9 and 17, certain/particular limitations shown recite (1) mere data gathering and (2) mere data transmitting/displaying, in which each of these claim limitations reflects mere insignificant extra-solution activities (see MPEP § 2106.05 (g)). While Independent Claims 1, 9 and 17 utilizes computer hardware (a computing device, databases, GUIs, and a machine learning model), the limitations simply instruct the computer to perform these computer functions (i.e., "collect data, store in a database, calculate, and display"). These claims merely use the computer as a tool to execute the abstract idea at a faster speed. It does not recite an improvement to the functioning of the computer itself, nor does it specify an unconventional machine-learning architecture or novel GUI technology that improves computer graphics. Thus, the abstract idea is not integrated into a practical application.
In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception. Therefore, at step 2a prong 2, Claims 1-19 and 21 are directed to the abstract idea and do not recite additional elements that integrate into a practical application.
Step 2B: (As explained in MPEP § 2106.05), it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Independent Claim 1 recites additional elements directed to: (e.g., “Human Resource Management System (HRMS)” & “first GUI element” & “second GUI element” & “third GUI element” & “software application” & “first database” & “second database”). Independent Claim 9 recites additional elements directed to: (e.g., “Human Resource Management System (HRMS)” & “first GUI element” & “second GUI element” & “third GUI element” & “software application” & “first database” & “second database” & “one or more computers” & “one or more processors”). Independent Claim 17 recites additional elements directed to: (e.g., “Human Resource Management System (HRMS)” & “first GUI element” & “second GUI element” & “third GUI element” & “software application” & “first database” & “second database” & “one or more processors”). These elements have been considered individually and in combination, but fail to add significantly more to the claims because they amount to using computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (computing environment) and does not amount to significantly more than the abstract idea itself. See MPEP § 2106.05 (f) and MPEP § 2106.05 (h). Notably, Applicant’s Specification suggests that the claimed invention relies on nothing more than a general-purpose computer executing the instructions to implement the invention (e.g., see at Applicant’s Specification ¶ [0024]: “Indeed, the employee management system 102 may be any computer or processing device such as, a blade server, general-purpose personal computer (PC), Mac®, workstation, UNIX-based workstation, or any other suitable device. In other words, the present disclosure contemplates computers other than general-purpose computers, as well as computers without conventional operating systems.”).
Independent Claims 1, 9 and 17: With respect to reliance on (e.g., “machine learning predictive model”) as an additional element shown in Independent Claims 1, 9 and 17 when considered both individually and as an ordered combination (as a whole) with these recited claim limitations, this additional element does not amount to significantly more than the judicial exceptions under step 2B due to the following: (1) recites mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions by providing the results to the user on a computer (see MPEP § 2106.05 (f)) or (2) limiting a particular field of use or technological environment pertaining to organizing human activity/psychological assessment for evaluating employees through a subjective assessment process (evaluating employee psychology and performance) environment (see MPEP § 2106.05 (h)).
Moreover, with respect to Independent Claims 1, 9 and 17, certain/particular limitations shown recite (1) mere data gathering and (2) mere data transmitting/displaying, in which each of these claim limitations reflects mere insignificant extra-solution activities (see MPEP § 2106.05 (g)). Furthermore, these certain/particular claim limitations as demonstrated above for Independent Claims 1, 9 and 17 reflects Well-Understood, Routine and Conventional Activities (WURC) under MPEP § 2106.05 (d) ii: See Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec,838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359,1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
The additional elements of “machine learning” or “machine learning model” in Claims 1, 9 and 17 do not amount to significantly more than the judicial exceptions under step 2B due to being expressly recognized as Well-Understood, Routine and Conventional (WURC) in the art.
See for example; US PG Pub (US 2024/0321453 A1) hereinafter Funahashi, et. al. Funahashi notes at ¶ [0086]: “A commonly used method may be employed as the machine learning method. For example, a method such as decision tree, random forest, eXtreme gradient boosting (XGBoost), support vector machine (SBM), or neural network may be employed to calculate the parameters of the prediction models and thereby create the health management indicator prediction models.” At ¶ [0196]: For each of a plurality of subjects, the calculation unit 404 acquires a data set including the condition indicators, the motivation indicators, the work information, and the health management indicators. Then, the calculation unit 404 creates the prediction models 414 through analysis with a method such as multivariate analysis, Bayesian network, or machine learning with the condition indicators, the motivation indicators, and the work information as the explanatory variables and the health management indicators as the objective variables. See for example; Foreign Patent Application (EP 4207016 A1) hereinafter Ahmadi, et. al. Ahmadi at ¶ [0021]: “The machine learning algorithms determine correlations between the communication data and the surveys using customized algorithms derived from known machine learning algorithms. Labels of data to input into the machine learning algorithms are derived from onboarding surveys.” Correlations from the survey data may be determined by extracting known COPSOQ survey questions and correlations known in the art.
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrates the abstract idea into a practical application. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that, as an ordered combination, amount to significantly more than the abstract idea itself.
Dependent Claims 2-8, 10-16, 18-19 and 21 recite substantially the same or similar additional elements as addressed above and when considered individually and as an ordered combination (as a whole) with these limitations recite the same abstract idea(s) as shown in Independent Claims 1, 9 and 17 along with further steps/details pertaining to “Mental Processes” which pertains to (1) concepts performed in the human mind (including observations or evaluations or judgments) or (2) using pen and paper as a physical aid and additionally or alternatively as “Certain Methods of Organizing Human Activities” which pertains to (3) managing personal behavior or relationships or interactions between people (including teachings or following rules or instructions) or (4) fundamental economic principles or practices.
Dependent Claims 2-8, 10-16 and 18-19 further narrow the abstract ideas, and are therefore still ineligible for the reasons previously provided in Steps 2A Prong 2 and Step 2B for Independent Claims 1, 9 and 17.
Dependent Claims 2-8, 10-16 and 18-19 merely refine the type of human data collected (Hope, Resilience, Optimism) or specify who is being managed (individual, team leader, or organization). Refining an abstract business practice by limiting it to a specific field or specific metrics does not integrate it into a practical application (Electric Power Group v. Alstom). Scheduling a poll post-event (Claims 8, 16) or during onboarding (Claims 2, 10, 18) constitutes "insignificant extra-solution activity." It is merely a collection mechanism to feed data into the abstract idea. None of these claims recite additional elements to integrate the judicial exception into a practical application under step 2a prong 2 nor do these claims recite additional elements that are sufficient to amount to significantly more than the recited judicial exceptions under step 2B.
The "Standardized Format" Limitation (Dependent Claim 21): While formatting data sounds computational, claiming the idea of data normalization or data standardization at a high level of generality does not save the claim. Under RecogniCorp v. Nintendo, formatting, converting, or structuring data mathematically is an abstract concept unless the claim recites a specific technical improvement to database throughput or network efficiency. Because Claim 21 simply states the data is "converted into a standardized format" without explaining how (e.g., a novel compiler technique or specific data compression token architecture), it fails to integrate the idea into a practical application under step 2a prong 2 nor does this claim recite additional elements that are sufficient to amount to significantly more than the recited judicial exceptions under step 2B.
Because the dependent claims fail to integrate the abstract idea into a practical application under Step 2A, they must be searched for an "inventive concept" under Step 2B. An inventive concept cannot reside in the abstract idea itself; it must be found in the remaining elements when viewed as an ordered combination. High Level of Generality: The terms "machine learning predictive model," "standardized format," "4-item pulse," and "hidden boosters of motivation" are functional and results-oriented. They describe what the system accomplishes, but not the specific technical how. Under Alice, simply stating a technical result without a detailed implementation strategy means the elements are treated as routine, conventional data-processing steps. The dependent claims narrow the scope of the abstract idea to specific psychological constructs (Hope, Optimism, Resilience) and specific HR environments (onboarding, team leaders, enterprise-wide analysis). However, narrowing an abstract idea with generic data-gathering mechanisms or basic data normalization rules (Claim 21) does not satisfy 35 U.S.C. § 101.
Therefore, the ordered combination of elements in the Dependent Claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself. Therefore, under Step 2B, Claims 1-19 and 21 do not include additional elements that are sufficient to amount to significantly more than the recited judicial exceptions. Thus, Claims 1-19 and 21 are ineligible with respect to the 35 U.S.C. § 101 analysis.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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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/DERICK J HOLZMACHER/ Patent Examiner, Art Unit 3625A
/SARA GRACE BROWN/Primary Examiner, Art Unit 3625
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