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 . In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Status of the Claims
The pending claims in the present application are claims 1-4, 6-14, and 19-25, as presented in the Response of 11 August 2026.
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.
Claims 1-4, 6-14, and 19-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The paragraphs below provide rationales for the rejection. The rationales are based on the multi-step subject matter eligibility test outlined in MPEP 2106.
Step 1 of the eligibility analysis involves determining whether a claim falls within one of the four enumerated categories of patentable subject matter recited in 35 USC 101. (See MPEP 2106.03(I).) That is, Step 1 asks whether a claim is to a process, machine, manufacture, or composition of matter. (See MPEP 2106.03(II).) The “apparatus” of claims 1-4, 6-8, 22, and 23 constitutes a machine under 35 USC 101, the “method” of claims 9-13, 21, 24, and 25 constitutes a process under the statute, and the “non-transitory computer readable medium” of claims 14, 19, and 20 constitutes a manufacture under the statute. Accordingly, claims 1-4, 6-14, and 19-25 meet the criteria of Step 1 of the eligibility analysis. The claims, however, fail to meet the criteria of subsequent steps of the eligibility analysis, as explained in the paragraphs below.
The next step of the eligibility analysis, Step 2A, involves determining whether a claim is directed to a judicial exception. (See MPEP 2106.04(II).) This step asks whether a claim is directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea. (See id.) Step 2A is a two-prong inquiry. (See MPEP 2106.04(II)(A).) Prong One and Prong Two are addressed below.
In the context of Step 2A of the eligibility analysis, Prong One asks whether a claim recites an abstract idea, law of nature, or natural phenomenon. (See MPEP 2106.04(II)(A)(1).) Using independent claim 1 as an example, the claim recites the following abstract idea limitations:
"An energy efficient collaboration for environmental social and governance (ESG) data consolidation and validation ... comprising: ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... a correlation graph generator ... to: ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... determine local correlations between ESG dimensions by determining correlation between historical data sets for corresponding ESG dimensions; ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... generate, based on the determined local correlations and for each organization avatar entity (OAE) of a plurality of OAEs, a local correlation graph of associated ESG dimensions; ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... determine, based on the local correlation graph of associated ESG dimensions, global correlations between the ESG dimensions by determining mean correlation between specified ESG dimensions across the plurality of OAEs; and ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... generate, based on the determined global correlations and for each OAE of the plurality of OAEs, a global correlation graph of associated ESG dimensions; ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... an ESG dimension analyzer ... to: identify, based on the global correlation graph, correlated ESG dimensions for each ESG data analyzer of a plurality of ESG data analyzers with respect to a set of ESG dimensions on which an ESG data analyzer of the plurality of ESG data analyzers collects data for at least one OAE of the plurality of OAEs; ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... a collaboration analyzer ... to: determine, based on the correlated ESG dimensions for each ESG data analyzer of the plurality of ESG data analyzers, collaboration potential between the plurality of ESG data analyzers; ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... a collaboration potential analyzer, ... to: generate, based on the collaboration potential between the plurality of ESG data analyzers, decentralized groups of collaborating ESG data analyzers; ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... a data model generator ... to: update, for each decentralized group of the decentralized groups of collaborating ESG data analyzers, a data model for each ESG data analyzer with respect to each ESG dimension corresponding to each OAE for which the ESG data analyzer is collecting data; ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... an anomalous event analyzer ... to: identify, for the ESG data analyzer that is collecting data and based on an associated updated data model, a potential anomalous ESG event at a specific ESG dimension, wherein to identify the potential anomalous ESG event at the specific ESG dimension, the anomalous event analyzer is configured to: ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... rebuild, for the ESG data analyzer that is collecting data, a local data model to generate the updated data model; and ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... determine a difference between the updated data model from the local data model; and ..." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
"... a OAE controller ... to: control, based on the identified potential anomalous ESG event, operation of the OAE associated with the ESG data analyzer that is collecting data." - See below regarding MPEP 2106.04(a), certain methods of organizing human activity, and mental processes
The above-listed limitations of independent claim 1, when applying their broadest reasonable interpretations in light of their context in the claim as a whole, fall under enumerated groupings of abstract ideas outlined in MPEP 2106.04(a). For example, limitations of the claim can be characterized as: commercial or legal interactions associated with collaboration among ESG analyzers, for use on anomalous ESG events; and managing personal behavior or relationships or interactions between people, including among ESG analyzers and those tasked with determining feasibility of collaboration between ESG analyzers, which fall under the certain methods of organizing human activity grouping of abstract ideas (see MPEP 2106.04(a)). Limitations of the claim also can be characterized as: concepts performed in the human mind, including observation (e.g., the recited “identify” steps), and evaluation and/or judgment (e.g., the recited “determine,” "generate," "identify," "update," "rebuild," and "control" steps), which fall under the mental processes grouping of abstract ideas (see MPEP 2106.04(a)). Accordingly, for at least these reasons, claim 1 fails to meet the criteria of Step 2A, Prong One of the eligibility analysis.
In the context of Step 2A of the eligibility analysis, Prong Two asks if the claim recites additional elements that integrate the judicial exception into a practical application. (See MPEP 2106.04(II)(A)(2).) Continuing to use independent claim 1 as an example, the claim recites the following additional element limitations:
The claimed “ESG data consolidation and validation” is performed an “apparatus” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
“... at least one hardware processor; ...” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “correlation graph generator” is “executed by the at least one hardware processor” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “ESG dimension analyzer” is “executed by the at least one hardware processor” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “collaboration analyzer” is “executed by the at least one hardware processor” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “collaboration potential analyzer” is “executed by the at least one hardware processor” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “data model generator” is “executed by the at least one hardware processor” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “anomalous event analyzer” is “executed by the at least one hardware processor” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “OAE controller” is “executed by the at least one hardware processor” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The above-listed additional element limitations of independent claim 1, when applying their broadest reasonable interpretations in light of their context in the claim as a whole, are analogous to: accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, and mere automation of manual processes, which courts have indicated may not be sufficient to show an improvement in computer-functionality (see MPEP 2106.05(a)(I)); a commonplace business method being applied on a general purpose computer, gathering and analyzing information using conventional techniques and displaying the result, and selecting a particular generic function for computer hardware to perform from within a range of fundamental or commonplace functions performed by the hardware, which courts have indicated may not be sufficient to show an improvement to technology (see MPEP 2106.05(a)(II)); a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions, and merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions, which do not qualify as a particular machine or use thereof (see MPEP 2106.05(b)(I)); a machine that is merely an object on which the method operates, which does not integrate the exception into a practical application (see MPEP 2106.05(b)(II)); use of a machine that contributes only nominally or insignificantly to the execution of the claimed method, which does not integrate a judicial exception (see MPEP 2106.05(b)(III)); transformation of an intangible concept such as a contractual obligation or mental judgment, which is not likely to provide significantly more (see MPEP 2106.05(c)); use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea, a commonplace business method or mathematical algorithm being applied on a general purpose computer, and requiring the use of software to tailor information and provide it to the user on a generic computer, which courts have found to be mere instructions to apply an exception, because they do no more than merely invoke computers or machinery as a tool to perform an existing process (see MPEP 2106.05(f)); mere data gathering in the form of obtaining information about transactions using the Internet to verify transactions and consulting and updating an activity log, which courts have found to be insignificant extra-solution activity (see MPEP 2106.05(g)); and identifying the participants in a process for hedging risk as commodity providers and commodity consumers, because limiting the use of the process to these participants did no more than describe how the abstract idea of hedging risk could be used in the commodities and energy markets, specifying that the abstract idea of monitoring audit log data relates to transactions or activities that are executed in a computer environment, because this requirement merely limits the claims to the computer field, i.e., to execution on a generic computer, and limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, which courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception (see MPEP 2106.05(h)). Further, a claim like claim 1 that has broad applicability across many fields of endeavor may not provide meaningful limitations that integrate a judicial exception into a practical application or amount to significantly more, wherein, for instance, a claim that generically recites an effect of the judicial exception or claims every mode of accomplishing that effect, amounts to a claim that is merely adding the words "apply it" to the judicial exception (see MPEP 2106.05(f)). For at least these reasons, claim 1 fails to meet the criteria of Step 2A, Prong Two of the eligibility analysis.
The next step of the eligibility analysis, Step 2B, asks whether a claim recites additional elements that amount to significantly more than the judicial exception. (See MPEP 2106.05(II).) The step involves identifying whether there are any additional elements in the claim beyond the judicial exceptions, and evaluating those additional elements individually and in combination to determine whether they contribute an inventive concept. (See id.) The ineligibility rationales applied at Step 2A, Prong Two, also apply to Step 2B. (See id.) For all of the reasons covered in the analysis performed at Step 2A, Prong Two, independent claim 1 fails to meet the criteria of Step 2B. As a result, claim 1 is rejected under 35 USC 101 as ineligible for patenting.
Regarding claims 2-4, 6-8, 22, and 23, the claims depend from independent claim 1, and expand upon limitations introduced by claim 1. The dependent claims are rejected at least for the same reasons as claim 1. For example, the dependent claims recite abstract idea limitations similar to the abstract idea limitations of claim 1, that fall under the same abstract idea groupings as the abstract idea limitations of claim 1 (e.g., the "wherein the collaboration analyzer is ... to determine, based on the correlated ESG dimensions for each ESG data analyzer of the plurality of ESG data analyzers, the collaboration potential between the plurality of ESG data analyzers by: determining, for each pair of ESG data analyzers of the plurality of ESG data analyzers, a degree to which ESG data analyzers of the pair of ESG data analyzers collaborate with each other to enrich their data collection" of claim 2, the "wherein the collaboration potential analyzer is ... to generate, based on the collaboration potential between the plurality of ESG data analyzers, the decentralized groups of collaborating ESG data analyzers by: generating a collaboration graph between the plurality of ESG data analyzers, wherein, for the collaboration graph, weights of edges represent collaboration potentials between connected ESG data analyzers" of claim 3, the "wherein the collaboration potential analyzer is ... to generate the collaboration graph between the plurality of ESG data analyzers by: retaining, for the collaboration graph, edges that include a collaboration potential that is greater than a specified threshold" of claim 4, the "wherein the anomalous event analyzer is ... to: determine, for a specified number of ESG dimensions, whether a data anomaly is true for the OAE associated with the ESG data analyzer; and identify, based on a determination that the data anomaly is true for the OAE associated with the ESG data analyzer for the specified number of ESG dimensions, the potential anomalous ESG event" of claim 6, the "wherein the anomalous event analyzer is ... to: determine, for a specified number of OAEs in a cluster of OAEs, whether a data anomaly is true; and identify, based on a determination that the data anomaly is true for the specified number of OAEs in the cluster of OAEs, the potential anomalous ESG event for the cluster of OAEs" of claim 7, the "wherein the anomalous event analyzer is ... to: determine, for a specified number of OAEs in a cluster of OAEs, whether a data anomaly is true for a specified ESG dimension; and identify, based on a determination that the data anomaly is true for the specified ESG dimension for the specified number of OAEs in the cluster of OAEs, the potential anomalous ESG event at a global level for the specified ESG dimension" of claim 8, the "wherein to identify the potential anomalous ESG event, the anomalous event analyzer is configured to: determine whether the difference between the updated data model and the local data model exceeds a first threshold; determine whether a change between an updated correlation and a prior correlation of the specific ESG dimension with a correlated ESG dimension exceeds a second threshold; determine whether the determinations are absent for at least a specified fraction of other organization avatar entities in a cluster associated with the organization avatar entity; and identify the potential anomalous ESG event based on determining that the difference exceeds the first threshold, the change exceeds the second threshold, and the determinations are absent for the specified fraction of the other organization avatar entities" of claim 22, and the "wherein the collaboration potential between a pair of ESG data analyzers of the plurality of ESG data analyzers, is determined based on: operational proximity between a pair of OAEs of the plurality of OAEs associated with the pair of ESG data analyzers, and statistical correlational proximities among ESG dimensions monitored by the pair of ESG data analyzers" of claim 23). The dependent claims recite further additional elements that are similar to the additional elements of claim 1, that fail to warrant eligibility for the same reasons as the additional elements of claim 1 (e.g., the "apparatus ... executed by the at least one hardware processor" of claim 2, the "apparatus ... executed by the at least one hardware processor" of claim 3, "apparatus ... executed by the at least one hardware processor" of claim 4, "apparatus ... executed by the at least one hardware processor" of claim 6, "apparatus ... executed by the at least one hardware processor" of claim 7, "apparatus ... executed by the at least one hardware processor" of claim 8, the "apparatus" of claim 21, the "apparatus" of claim 22, and the "apparatus" of claim 23). Accordingly, claims 2-4, 6-8, 22, and 23 also are rejected as ineligible under 35 USC 101.
Regarding claims 9-13, 21, 24, and 25, while the claims are of different scope relative to claims 1, 3, 4, and 23 the claims recite limitations similar to the limitations of claims 1, 3, 4, and 23. As such, the rejection rationales applied to reject claims 1-4, 6-8, 22, and 23 also apply for purposes of rejecting claims 9-13, 21, 24, and 25. Limitations recited by claims 9-13, 21, 24, and 25 that do not have a counterpart in claims 1, 3, 4, and 23 (such as the recited “further comprising: determining whether the difference between the updated data model and the local data model exceeds a first threshold; determining whether a change between an updated correlation and a prior correlation of the specific ESG dimension with a correlated ESG dimension exceeds a second threshold; determining whether the determinations are absent for at least a specified fraction of other organization avatar entities in a cluster associated with the organization avatar entity; and identifying the potential anomalous ESG event based on determining that the difference exceeds the first threshold, the change exceeds the second threshold, and the determinations are absent for the specified fraction of the other organization avatar entities" of claim 21, and the "wherein updating the data model further comprises: combining ... data corresponding to different organization avatar entities (OAEs) of the plurality of OAEs; and determining ... a mean value across the different OAEs to learn the updated data model" of claim 25), fail to warrant a finding of eligibility, because such limitations are abstract idea elements that fail to meet the criteria of Step 2A, Prong One, for the same reasons as the abstract idea elements of claims 1, 3, 4, and 23. In addition, the recited "by the at least one hardware processor" limitations of claim 25 amount to additional elements that fail to meet the criteria of Step 2A, Prong Two and Step 2B, for the same reasons as the additional elements of claims 1, 3, 4, and 23. Claims 9-13, 21, 24, and 25 are, therefore, also rejected as ineligible under 35 USC 101.
Regarding claims 14, 19, and 20, while the claims are of different scope relative to claims 1, 6, and 7, the claims recite limitations similar to the limitations of claims1, 6, and 7. As such, the rejection rationales applied to reject claims 1, 6, and 7 also apply for purposes of rejecting claims 14, 19, and 20. Claims 14, 19, and 20 are, therefore, also rejected as ineligible under 35 USC 101.
Examiner Remarks
This Office Action does not assert any prior art rejections against claims 1-4, 6-14, and 19-25, because the claims distinguish over the closest prior art of record. U.S. Pat. App. Pub. No. 2024/0086817 A1 to Bessenyei et al. (hereinafter referred to as "Bessenyei"), WIPO Int'l Pub. No. 2020/259716 A1 to Li et al. (hereinafter referred to as "Li"), and IOSCO. NOON, UNDER EMBARGO UNTIL, and ON TUESDAY. "Environmental, social and governance (ESG) ratings and data products providers." (2021) (herein after referred to as "IOSCO") are representative of the closest prior art of record.
Using independent claim 1 as an example, the claim recites the following limitations:
... a collaboration potential analyzer, executed by the at least one hardware processor, to: generate, based on the collaboration potential between the plurality of ESG data analyzers, decentralized groups of collaborating ESG data analyzers;
a data model generator, executed by the at least one hardware processor, to:
update, for each decentralized group of the decentralized groups of collaborating ESG data analyzers, a data model for each ESG data analyzer with respect to each ESG dimension corresponding to each OAE for which the ESG data analyzer is collecting data;
an anomalous event analyzer, executed by the at least one hardware processor, to:
identify, for the ESG data analyzer that is collecting data and based on an associated updated data model, a potential anomalous ESG event at a specific ESG dimension, wherein to identify the potential anomalous ESG event at the specific ESG dimension, the anomalous event analyzer is configured to:
rebuild, for the ESG data analyzer that is collecting data, a local data model to generate the updated data model; and
determine a difference between the updated data model from the local data model; ...
Regarding Bessenyei, the reference discloses, “A Software-as-a-Service infrastructure is provided to perform data analytics, wherein a given analytic is defined in a spreadsheet according to a formula, and wherein the formula is associated with an Environmental, Social and Governance (ESG) impact” (Abstract), “Depending on use case, the data sources may be public data, e.g., published or otherwise readily-accessible data about public companies, private data, e.g., data about a private company and that is not necessarily published or otherwise available from public sources, or a combination of both public and private data. Whether public or private, typically the data is associated with one or ESG-related metrics associated with a company or a group of companies” (para. [0021]), “The platform enables user (e.g., investors, managers, consumers, employees and other stakeholders) to understand ESG risks and opportunities, and also to quantify holistic impact of investments to maximize positive impact on the environment, and on society” (para. [0021]), and “the data sources 106 comprise a taxonomy of product groups and associated key impact drivers available to the platform” and “outcome-driven environmental and social metrics (e.g., product portfolio, grams of sugar per $ of revenue, grams of plastic per $ of revenue, etc.) are identified in the data sources 106” (para. [0022]). Bessenyei does not, however, appear to disclose, teach, or suggest the recited collaboration potential between ESG analyzers, decentralized groups of ESG analyzers, and local data model versus updated data model, limitations of independent claim 1.
Regarding Li, the reference discloses, “processing the alternative data to determine a knowledge graph” (English-language translation, p. 2), and “FIG. 3 is a detailed flowchart of step S100 of an embodiment of the ESG indicator monitoring method of this application. In this embodiment, the knowledge graph includes: a key information graph. In step S100, the alternative The steps of data processing to determine the knowledge graph include: Step S101, extracting key information from the alternative data based on artificial intelligence technology, where the key information includes: key nodes and key relationships” (English-language translation, p. 4). Although the ESG-related knowledge graphs appear to be similar to the claimed model(s), Li does not appear to disclose, teach, or suggest use of such models in a way that remedies the deficiencies of Bessenyei, or otherwise reads on the above-noted limitations of independent claim 1.
Regarding IOSCO, the reference discloses "Environmental, Social and Governance (ESG) Ratings and Data Products Providers" (p. 1), and "Following consolidation moves in recent years, some of these larger, more established market participants – notably credit rating agencies, exchanges, data and index providers – have begun to acquire smaller and more specialised ESG providers (see Table 1) and/or have invested significant resources to develop their own ESG expertise/capacities. However, where consolidations have occurred, only a few companies appear to have been fully integrated into the acquiring company, with the vast majority of acquired companies retaining their legal status by becoming a subsidiary of the acquiring entity" (p. 10). But IOSCO also does not appear to disclose, teach, or suggest the recited collaboration potential between ESG analyzers, decentralized groups of ESG analyzers, and local data model versus updated data model, limitations of independent claim 1.
Due to the deficiencies of Bessenyei, Li, and IOSCO, as set forth above, independent claim 1 distinguishes over the closest prior art of record. The other independent claims recite limitations similar to those recited by claim 1, and thus, also distinguish over the closest prior art of record. The claims that depend from the independent claims distinguish over the closest prior art of record due at least to their dependency.
Response to Arguments
On pp. 11-20 of the Response, the applicant requests reconsideration and withdrawal of the claim rejection under 35 USC 101. More specifically, with respect to Step 2A, Prong One, the applicant argues that "the limitations of amended claim 1 are not directed to an abstract idea merely because they involve analyzing ESG-related data. The amended claim 1 enables detecting ESG anomalies at multiple levels (dimension, organization, cluster, and global) by manipulation of large-scale data structures, graph generation, computational correlation analysis, distributed model building. Clearly, the amended claim 1 requires manipulation of large-scale data structures, graph generation, computational correlation analysis, distributed model building, and automated control of devices which cannot realistically be performed mentally, even with pen and paper." (Response, p. 12.) The examiner finds these arguments unpersuasive. Much of what is argued is not claimed, or can be performed with or without a generic computer. For example, the claim does not recite anything "large-scale," and it is unclear to the examiner why a person using their mind, a pen, and paper could not generate a graph, compute and analyze correlations, or build distributed models, by generating and manipulating various forms of data. None of these words or phrases requires anything complex or technological. They might, but they are claimed with wording so broad that the examiner should not be limited to only such narrow interpretations.
The applicant also argues that "the technical problem associated with acquisition and analysis of reliable ESG data is due to large numbers of ESG dimensions, multiple organization avatar entities, complex operating environments, and data privacy issues." (Response, p. 12.) The applicant contends, "amended claim 1 provides technical solution to the above-mentioned technical problem by providing dynamic runtime collaboration among ESG data analyzers" (Id. at p. 13.) The examiner finds these arguments unpersuasive. The problems associated with acquisition and analysis of reliable ESG data read like ESG problems associated with ESG data and ESG analyzers, not technical problems. The examiner sees no correlation between any aspects of the claimed invention and operating environments. Data privacy issues also are not necessarily technical problems. Further, dynamic runtime collaboration is not claimed, and thus, arguments about it hold little weight.
The applicant also argues that "equations (1)-(4) mathematically define these correlation computations and graph structures constructions across a plurality of ESG dimensions and OAEs and therefore cannot be performed in the human mind" (Response, p. 13.) The examiner finds these arguments unpersuasive. No equations are claimed. Also, they might just be abstract idea elements in the form of mathematical concepts.
The applicant also argues, "These graph-based computations and clustering operations constitute specialized computational processing rather than mere mental process." (Response, p. 13.) The examiner finds these arguments unpersuasive. None of the claimed graph-based computations and clustering operations are specialized computational processing. They are abstract idea elements performed by generic computational processing. The former is the mental process, while the latter is just an additional element that is of little significance at Step 2A, Prong One.
The applicant also argues that "the subject matter of the amended claim 1 enables energy savings through reduction of computational resources required by determining which ESG data analyzers can cooperate most effectively to build ESG data models and identification of a potential anomalous ESG event. These improvements represent technical improvements to the operation of the ESG monitoring system itself rather than an abstract business concept." (Response, p. 14.) The examiner finds these arguments unpersuasive. Technical improvements are not particularly relevant at Step 2A, Prong One. Even if they were, it is unclear to the examiner how use of computational resources to perform the claimed steps would involve reducing use of said computational resources.
The applicant also argues that "the claimed generation of local and global correlation graphs, determination of collaboration potentials across distributed ESG data analyzers, creation of decentralized collaboration groups, rebuilding and comparison of statistical data models, multi-level anomaly detection, and automatic control of OAEs are precisely the type of computer-implemented operations that cannot practically be performed mentally." (Response, p. 14.) The examiner finds these arguments unpersuasive. All of these features could be performed mentally by a person analyzing various forms of ESG-related data. For example, a person working for an ESG analyzer that is trying to acquire another ESG analyzer, would be determining collaboration potential across the two ESG analyzers. That is something a person would contemplate for a merger or acquisition. There is nothing inherently technological about the step that would make it impractical to perform mentally. The only thing that might not be a mental process is the control being automatic, but that is just use of a generic computer, and plays no role in the Step 2A, Prong One analysis.
The applicant also argues that "amended claim 1 recites a specific computational framework for distributed graph-based ESG data consolidation, decentralized model generation, anomaly detection, and automated operational control using specialized software components executed by at least one processor." (Response, p. 14.) The examiner finds these arguments unpersuasive. There is nothing "specific" about use of a generic, conventional "hardware processor" in the claims.
Regarding Step 2A, Prong Two, the applicant argues that "amended claim 1 nevertheless integrates any such alleged judicial exception into a practical application." (Response, pp. 14 and 15.) According to the applicant, "Claim 1 recites a specific technical architecture and a particular sequence of operations that collectively solve technological problems associated with ESG data consolidation, decentralized data-model generation, anomaly detection, and computational resource utilization in a metaverse environment." (Id. at p. 15.) The examiner finds these arguments unpersuasive. Claim 1 does not recite any specific technical architecture. It recites "at least one hardware processor," which is not specific at all. Further, neither ESG data consolidation, decentralized data-model generation, nor anomaly detection is necessarily a technological problem. Also, it is unclear to the examiner why a claimed method that utilizes computational resources in the form of generic, conventional hardware processors, to perform business/legal analyses, somehow solves a problem associated with said hardware processors.
The applicant also argues that "the specification expressly identifies technological challenges associated with ESG data analysis. Specifically, the specification emphasizes that acquisition and analysis of reliable ESG data is technically challenging due to the relatively large number of ESG dimensions, complexities of operating environments, and data privacy concerns." (Response, p. 15.) The examiner finds these arguments unpersuasive. There being a large number of ESG dimensions is not a technological challenge. That is a data challenge that exists with all kinds of business and legal data. It also is unclear what in the claimed invention overcomes technological challenges associated with complexities of operating environments or data privacy. Data privacy is not necessarily a technological challenge. Privacy for paper records is one example of a non-technological challenge.
The applicant also argues that "amended claim 1 provides the technical solutions ... by providing dynamic runtime collaboration among ESG data analyzers. The dynamic runtime collaboration includes a collective broadcast-based interaction among ESG data analyzers to learn ESG data models." (Response, p. 15.) The applicant asserts that "The technical solution involves the execution of a sequence of steps in a particular order." (Id.) The applicant emphasizes the discussion, in the specification, of weighted correlation graphs, decentralized groups of ESG data analyzers, decentralized collaboration groups, updating local and other data models, rebuilding said models, identifying anomalies based on model divergence, filtering, correlation-change analysis, cluster-level analysis, confidence estimation, and the like. (Id. at p. 16.) The applicant characterizes at least some of these as involving "a specific computational technique." (Id.) The examiner finds these arguments unpersuasive. Dynamic runtime collaboration is not claimed. Further, the steps emphasized by the applicant are abstract idea elements, not technical solutions, or things requiring any specific computational techniques. The claimed steps are much broader than the narrow interpretations proposed by the applicant.
The applicant also argues that the "OAE controller to control operation of an OAE based upon the identified anomalous ESG event" should be considered. (Response, p. 17.) The applicant emphasizes Memo guidance warning examiners against oversimplifying claim limitations and expanding application of the "apply it" consideration, eligibility rationales from Ex Parte Desjardins, and various court decisions. (See id.) The examiner finds these arguments unpersuasive. The examiner is not oversimplifying the claims. The 35 USC 101 section above uses the explicit wording of the claims to make the rejection. Further, an OAE controller can be a person that performs some kind of action in a company to mitigate ESG issues, and thus, such aspects are viewed as abstract idea elements. Further, the examiner does not see any correlation between the claimed invention and the identified eligibility rationales involving machine learning training (e.g., like in Ex Parte Desjardins). Phrases from decisions need to be considered in context, not in a vacuum.
The applicant also argues that the claims reflect an improvement to the functioning of a computer or another technology or technical field, and also cover a particular solution or particular way to achieve a desired outcome rather than merely claiming the idea of the outcome. (See Response, p. 18.) According to the applicant "These interrelated components operate together to improve ESG anomaly detection accuracy and computational efficiency." (Id.) The examiner finds these arguments unpersuasive. The improvement, in the claimed invention, is to collaboration between ESG data analyzers, which is an improvement to an abstract idea element, not to computer functionality, another technology, or a technical field.
Regarding Step 2B, the applicant argues that "amended claim 1 does not merely recite generic computer components performing conventional functions. Rather, amended claim 1 recites a specific and non-generic ordered combination of operations performed by at least a correlation graph generator, a data model generator, an anomalous event analyzer, and an OAE controller, each executed by at least one hardware processor." (Response, p. 19.) The applicant views this as being like the non-conventional and non-generic arrangement from BASCOM. (Id.) The applicant also argues that factual evidence was not provided for the well-understood, routine, conventional ineligibility rationale. (See id. at p. 20.) The examiner finds these arguments unpersuasive. The use of "at least one hardware processor" to process data is using a generic computer component to perform a conventional function. The fact that some specific form of business/legal data is processed by the processor, does not change that fact. Also, the well-understood, routine, conventional ineligibility rationale has not been relied upon to make the rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Such prior art includes the following:
U.S. Pat. No. 11,610,168 B2 to Yoon et al. discloses, "Disclosed is a method for analyzing a risk of a cooperator supply chain. The method calculates a risk score based on text data associated with an evaluation target company, provides visual information on the risk score of the evaluation target company through a bar graph, a tracking graph, a scatter plot graph, a network diagram, and a map diagram, and generates a chat room for managing a supply chain between the evaluation target company and the cooperator to support real-time communication." (Abstract.)
U.S. Pat. App. Pub. No. 2014/0279623 A1 to Mislove et al. discloses, "Systems and methods are described for determining a weighted rating and a relative rating. In some embodiments, a receiving module and rating module are configured to receive an identity of a collector, a list of raters, and a social graph, determine for at least one rater a set of non-intersecting paths between the rater and the collector, calculate capacity values for non-intersecting paths, normalize path values, convert path values to a user weight, and apply the at least one rater's weight to the at least one rater's rating. In some embodiments, a receiving module and rating module are also configured to receive a rating for each of the items rated by the rater, calculate a transformed rating, calculate a relative rating, and assign a relative rating to an item." (Abstract).
U.S. Pat. App. Pub. No. 2023/0069078 A1 to Pennington et al. discloses, "The various embodiments described herein relate to systems, methods, and devices associated with distributed ledger systems (e.g., distributed ledger technology implemented on a decentralized network) that can be used to handle and manage the distribution and access of data in a manner that preserves the benefits of distributed ledger technology while enabling the private sharing of data. More specifically, the distributed ledger systems contemplated herein involve distributed ledger technology (DLT)-based data management platforms that can be implemented on nodes of a data management network." (Abstract.)
CN Pat. App. Pub. No. 110472884 A to Li et al. discloses, "The invention claims an ESG index monitoring method, device, terminal device and storage medium, the ESG index monitoring method comprises the following steps: obtaining alternative data, and the alternative data processing to determine the knowledge map from the alternative data extracting ESG event, and combining the knowledge map to the ESG event for ESG index score, output warning information to the relationship of the ESG event ESG index score according to the scoring result. The invention avoids the situation of industry individuals not actively disclosing data caused by individual ESG index cannot effectively provide reference for individual relation, improves the accuracy of ESG-related information and data of the real time performance and effectiveness." (English-language Abstract.)
English-language translation of CN Pat. App. Pub. No. 110472884 A (see above).
Marra A, Carlei V, Baldassari C. Exploring networks of proximity for partner selection, firms' collaboration and knowledge exchange. The case of clean‐tech industry. Business Strategy and the Environment. 2020 Mar;29(3):1034-44.
IOSCO. NOON, UNDER EMBARGO UNTIL, and ON TUESDAY. "Environmental, social and governance (ESG) ratings and data products providers." (2021).
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THOMAS Y. HO, whose telephone number is (571)270-7918. The examiner can normally be reached Monday through Friday, 9:30 AM to 5:30 PM Eastern.
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/THOMAS YIH HO/Primary Examiner, Art Unit 3624
