Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
2. 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.
3. Claims 1-21 are rejected under 35 U.S.C. §101 because the claimed invention recites and is directed to a judicial exception to patentability (i.e., a law of nature, a natural phenomenon, or an abstract idea) and does not include an inventive concept that is “significantly more” than the judicial exception under the January 2019 and October 2019 patentable subject matter eligibility guidance (2019 PEG) analysis which follows.
Step 1
4. Under the 2019 PEG step 1 analysis, it must first be determined whether the claims are directed to one of the four statutory categories of invention (i.e., process, machine, manufacture, or composition of matter). Applying step 1 of the analysis for patentable subject matter to the claims, it is determined that the claims are directed to the statutory category of a process (claim 20), a machine (claims 1-19) and a manufacture (claim 21). Therefore, we proceed to step 2A, Prong 1.
Step 2A, Prong 1
5. Under the 2019 PEG step 2A, Prong 1 analysis, it must be determined whether the claims recite an abstract idea that falls within one or more designated categories of patent ineligible subject matter (i.e., organizing human activity, mathematical concepts, and mental processes) that amount to a judicial exception to patentability.
Claim 1 recites the abstract idea of:
receive a current objection inquiry document for a rate change request from an insurance regulator, the current objection inquiry document including (i) at least one first objection to the rate change request and (ii) at least one first request for additional information;
[[electronically]] parse the current objection inquiry document to identify a first model input including text describing the at least one first objection and the at least one first request for additional information;
enter the first model input into [[the large language model]] to generate a first output including an [[electronic]] response document for responding to the current objection inquiry for the rate change request; and
transmit the [[electronic]] response document to the insurance regulator to respond to the at least one first objection and the at least one first request for additional information included in the current objection inquiry document.
Here, the recited abstract idea falls within one or more of the three enumerated 2019 PEG categories of patent ineligible subject matter, to wit: certain methods of organizing human activity, which includes fundamental economic practices or principles and/or commercial interactions (e.g., processes for responding to inquiries related to insurance rate change requests).
Step 2A, Prong 2
6. Under the 2019 PEG step 2A, Prong 2 analysis, the identified abstract idea to which claim 1 is directed does not include limitations or additional elements that integrate the abstract idea into a practical application.
Besides reciting the abstract idea, the limitations of claim 1 also recite generic computer components (e.g., a computer system comprising: at least one processor; at least one memory device in communication with the at least one processor, and AI tools including a large language model). In particular, the recited features of the abstract idea are merely being applied on a computer or computing device or via software programming that is simply being used as a tool (“apply it”) to implement the abstract idea. (See e.g., MPEP §2106.05(f)). Therefore, these additional elements are recited at a high level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components. In other words, the additional elements are simply used as tools to perform the abstract idea.
Claim 1 also recites the following limitations:
build the large language model for insurance rate change requests using at least the following input documents: (i) a plurality of historical rate change requests from an insurance provider including a description of each historical rate change request, (ii) a plurality of historical objection inquiries from insurance regulators to the plurality of historical rate change requests including one or more different objections and/or requests for information relating to each of the historical rate change requests, (iii) a plurality of historical responses from the insurance providers to the plurality of historical objection inquiries including responses to each of the one or more objections and/or requests for information, and (iv) a plurality of historical decisions from the insurance regulators responding to the plurality of historical responses from the insurance providers.
These limitations recite a process for building a large language model based on a variety of information (e.g., a plurality of historical rate change requests from an insurance provider). However, the claim does not provide significant technical detail regarding how the model is trained and/or implemented to generate responses to the received inquiries. Therefore, such limitations amount to no more than merely applying a generic large language model to implement the abstract idea on a computer. Simply defining the type of data used to train the large language model does not provide an indication of an improvement to large language model technology, or any other technology or technological field.
Thus, claim 1 does not include any limitations or additional elements that integrate the abstract idea into a practical application. As a result, claim 1 is directed to an abstract idea.
Step 2B
7. Under the 2019 PEG step 2B analysis, the additional elements of claim 1 are evaluated to determine whether they amount to something “significantly more” than the recited abstract idea. (i.e., an innovative concept). Here, the recited additional elements (e.g., a computer system comprising: at least one processor; at least one memory device in communication with the at least one processor, and AI tools including a large language model), do not amount to an innovative concept since, as stated above in the Step 2A, Prong 2 analysis, the claims are simply using the additional elements as a tool to carry out the abstract idea (i.e., “apply it”) on a computer or computing device and/or via software programming (See e.g., MPEP §2106.05(f)). The additional elements are specified at a high level of generality such that they are being used in the claims to simply implement the abstract idea and are not themselves being technologically improved (See e.g., MPEP 2106.05(I)(A)); (See also applicant’s Specification at least Paragraphs 91-111).
Thus, claim 1 does not recite any additional elements that amount to “significantly more” than the abstract idea.
Additional Independent Claims
8. Independent claims 20 and 21 are similarly rejected under 35 U.S.C. 101 for the reasons described below:
Claim 20 recites limitations that are substantially similar to those recited in claim 1. However, the primary difference between claims 20 and 1 is that claim 20 is drafted as a method rather than as a system. Similarly, as described above regarding claim 1, claim 20 recites generic computer components (e.g., a computer system including at least one processor in communication with at least one memory device and artificial intelligence (AI) tools including a large language model) that are simply being used as a tool (“apply it”) to implement the abstract idea. Therefore, since the same analysis should be used for claims 1 and 20, claim 20 is not patent eligible (See Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014)).
Claim 21 recites limitations that are substantially similar to those recited in claim 1. However, the primary difference between claims 21 and 1 is that claim 21 is drafted as a computer-readable storage media rather than as a system. Similarly, as described above regarding claim 1, claim 21 recites generic computer components (e.g., at least one non-transitory computer-readable storage media having computer-executable instructions embodied thereon, and at least one processor of a computer system) that are simply being used as a tool (“apply it”) to implement the abstract idea. Therefore, since the same analysis should be used for claims 1 and 21, claim 21 is not patent eligible (See Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014)).
Dependent Claims
9. Dependent claims 2-19 are also rejected under 35 U.S.C. 101 for the reasons described below:
Claim 2 simply refines the abstract idea because it recites process steps (e.g., receiving a decision document, parsing the decision document, generating a second output including a second response document, and transmitting the second response document to the insurance regulator) that fall under the category of organizing human activity, namely facilitating a transaction, as described above regarding claim 1. Additionally, merely stating that this process is performed by the large language model amounts to no more than merely applying generic computer components to implement the abstract idea on a computer.
Claim 3 simply provides further definition to the “second objection” recited in claim 3. Simply stating that the second representation the same as the first objection, different from the first objection, or a combination thereof, does not provide an indication of an improvement to any technology or technological field. Rather, this merely defines the type of objection received by the system.
Claim 4 simply provides further definition to the “second request for additional information” recited in claim 3. Simply stating that the second representation the same as the first request for additional information, different from the first request for additional information, or a combination thereof, does not provide an indication of an improvement to any technology or technological field. Rather, this merely defines the type of objection received by the system.
Claims 5 and 6 simply provides further definition to the “large language model” recited in claim 1. Simply stating that the large language model includes a generative AI large language model does not provide an indication of an improvement to any technology or technological field. Rather, this merely defines the type of large language model used by the system.
Claim 7 recites limitations that are substantially similar to the limitations of claim 1 regarding the building of the large language model. As described above regarding claim 1, simply defining the type of data used to train the large language model does not provide an indication of an improvement to large language model technology, or any other technology or technological field.
Claims 8 and 9 simply refine the abstract idea because they recite process steps (e.g., parsing the objection inquiry document, identifying key words, generating a query, and outputting a portion of text that responds to the first objection) that fall under the category of organizing human activity, namely facilitating a transaction, as described above regarding claim 1. Additionally, merely stating that this process is performed by the large language model and Natural Language Processing (NLP) tools amounts to no more than merely applying generic computer components to implement the abstract idea on a computer. The claims do not provide significant technical detail regarding how the large language model and the NLP tools operate to perform the claimed functions.
Claim 10 simply states that the large language model outputs a “transitional portion of the text” for transitioning between the first portion and the second portion. However, the claims do not provide significant technical detail regarding how the transitional portion of the text is generated and/or how it is applied to transition between the first portion and the second portion. Therefore, such limitations amount to no more than merely applying a generic large language model to implement the abstract idea on a computer.
Claim 11 simply states that the large language model outputs a “response header” for indicating a party who the electronic document is to be addressed to. However, the claims do not provide significant technical detail regarding how the response header is generated and/or how it is applied to indicate a party who the electronic document is to be addressed to. Therefore, such limitations amount to no more than merely applying a generic large language model to implement the abstract idea on a computer.
Claim 12 simply provides further definition to the “first output” recited in claim 1. Simply stating that the first output comprises a combination of the response header, the first portion, the second portion and the transitional portion does not provide an indication of an improvement to any technology or technological field. Rather, this merely defines the type of information included in the first output.
Claims 13 and 14 simply refine the abstract idea because they recite process steps (e.g., parsing the current decision document, identifying key words, generating a query, and outputting a portion of text that responds to the first objection and the first request for additional information) that fall under the category of organizing human activity, namely facilitating a transaction, as described above regarding claim 1. Additionally, merely stating that this process is performed by the large language model and Natural Language Processing (NLP) tools amounts to no more than merely applying generic computer components to implement the abstract idea on a computer. The claims do not provide significant technical detail regarding how the large language model and the NLP tools operate to perform the claimed functions.
Claim 15 simply states that the large language model outputs a “transitional portion of the text” for transitioning between the third portion and the fourth portion. However, the claims do not provide significant technical detail regarding how the transitional portion of the text is generated and/or how it is applied to transition between the third portion and the fourth portion. Therefore, such limitations amount to no more than merely applying a generic large language model to implement the abstract idea on a computer.
Claim 16 simply states that the large language model outputs a “response header” for indicating a party who the electronic document is to be addressed to. However, the claims do not provide significant technical detail regarding how the response header is generated and/or how it is applied to indicate a party who the electronic document is to be addressed to. Therefore, such limitations amount to no more than merely applying a generic large language model to implement the abstract idea on a computer.
Claim 17 simply provides further definition to the “second output” recited in claim 1. Simply stating that the first output comprises a combination of the response header, the first portion, the second portion and the transitional portion does not provide an indication of an improvement to any technology or technological field. Rather, this merely defines the type of information included in the first output.
Claim 18 simply states that the system is programmed to automatically track the progress of the various request, inquiries, and decisions described in claims 1 and 2. However, the claims do not provide any technical detail regarding how the progress of these features is tracked. Therefore, such limitations simply further refine the abstract idea.
Claim 19 simply states that the progress of each document is displayed on a dashboard for the user tot rack and follow up as needed. However, the claims do not provide significant technical detail regarding how the progress is displayed and/or how the user interacts with the interface. Therefore, this limitation amounts to no more than merely outputting/displaying data, which is a form of insignificant extra-solution activity (See MPEP 2016.05(g): OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015)). As stated in MPEP 2106.05(d), a factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity (Berkheimer v. HP, Inc., 881 F.3d 1360, 1368 (Fed. Cir. 2018)). In view of this requirement set forth by Berkheimer, this limitation does not integrate the abstract idea into a practical application, or amount to significantly more than the abstract idea, because the courts have found the concept of merely outputting/displaying data to be well-understood, routine, and conventional activity (See MPEP 2106.05(d): OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015)).
Thus, the dependent claims do not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application) that results in the claims being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Citation of Pertinent Prior Art
10. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
DiBella (U.S. Pre-Grant Publication No. 20040024619): Describes a system for facilitating the determination of property and casualty insurance rates. DiBella broadly describes a process for justifying a determined rate to a regulatory agency. However, DiBella does not disclose the specific process recited in claim 1 for communicating with an insurance regulator, parsing documents to identify objections to a rate change request, or applying a large language model that is trained based on various historical information.
Kane (U.S. Pre-Grant Publication No. 20020169642): Describes a comprehensive system for providing hosted service for insurance company reporting and data analysis. Kane discloses the use of a “checklist” for adhering to insurance regulations when submitting files to a regulatory site. However, Kane also does not sufficiently teach the specific processes recited in claim 1.
Ricci (U.S. Pre-Grant Publication No. 20260080481): Describes artificial intelligence (AI) supported interactive platforms for generating captive insurance policy proposals based on standard market insurance policy data. Ricci broadly discloses the use on artificial intelligence to generate insurance proposals that adhere to state and federal regulatory codes. However, Ricci also does not sufficiently teach the specific processes recited in claim 1.
Friedman (U.S. Patent No. 9659277): Describes systems and methods for identifying potentially inaccurate insurance data submitted by an insurance agent. Data submitted by an insurance agent may be analyzed based at least in part on information stored in a historic underwriting analytics database. However, Friedman also does not sufficiently teach the specific processes recited in claim 1.
A combination of prior art references could not be identified to reasonably teach the specific combination of limitations recited in the independent claims. While the prior art discloses processes and systems that are related to the claims of the instant application, no prior art reference could be identified to teach the specific process flow recited in the independent claims. Therefore, the claims have not been rejected under 35 U.S.C. 102/103.
Conclusion
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/WILLIAM D NEWLON/Examiner, Art Unit 3696
/MATTHEW S GART/Supervisory Patent Examiner, Art Unit 3696
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