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 .
Response to Amendment
The amendment filed 29 January 2025 has been entered. Applicant amended claims 1, 11, and 21 and previously cancelled claims 9 and 19. Accordingly, claims 1-8, 10-18, and 20-21 remain pending.
Response to Arguments
Applicant's arguments filed 29 January 2025 with respect to the 35 USC 101 rejection have been fully considered but they are not persuasive.
Applicant’s remarks:
Independent claims 1, 11 and 21 have been amended to clarify that the method is for generating a dataset that can be safely shared in order to train an Al model. Applicant submits that the current claims are similar in nature, with respect to the 101 rejection, to those at issue in SRIInt'l v. Cisco Sys., Inc., 930 F.3d 1295, 1304 (Fed. Cir. 2019) (referred to further herein as "SRI"), in which the claims were found allowable. The claims are not directed to just analyzing data from multiple sources to detect suspicious activity. Instead, the claims are directed to an improvement in computer network technology.
Claims 1-8, 10-18 and 20-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Applicant respectfully traverses this rejection.
Applicant’s support:
[A] Applicant respectfully submits that the training of Al models is clearly related to computer
technology. Similar to SRI in which the claim focus was on the specific improvements in computer capabilities that allow monitoring of network data in order to automatically detect largescale attacks, the current claims focus on providing the largescale datasets that can be used for training an Al models. The problem with providing such datasets, particularly in the health care field, is how to provide a useful dataset that does not comprise personal information. As will be appreciated, it would be desirable to train an Al model on the dataset directly as the "real" dataset would have the most utility. However, this must be balanced against the privacy concerns of potentially identifying individuals within the dataset…Applicant believes that this mirror the current claims in which the computer device receives the real dataset and generates a synthetic dataset based on it using one of a plurality of specific synthesizing techniques and then sampling the synthetic dataset to generate a synthetic microdata dataset (similar to the detection of suspicious network activity based on analysis of network traffic data in SRI). As currently claimed, once the synthetic datasets are generated, they are used to estimate the re-identification risk (similar to generating reports of suspicious activity in SRI) and then the dataset can either be shared for training the Al model if the risk is acceptable, or if the risk is not acceptable, an anonymization process can be applied to the dataset and the risk re-evaluated.
[B] As such, Applicant respectfully submits that the human mind is not equipped to analyze the data as recited in claims 1, 11, and 21.
[C] For at least the reasons discussed above, claims 1, 11, and 21, as well as its associated dependent claims, are directed to patent eligible subject matter under 35 U.S.C. § 101.
Examiner’s remarks
[A] The preamble of the claims recite that the generated data set is useable to training an AI model. If the limitation is merely an intended use of the claimed invention or a field of use limitation, then it cannot integrate the judicial exception (see MPEP 2106.04(d)(2)). The limitations in the claims under its broadest reasonable interpretation continue to cover performance of the limitations being an abstract idea directed to mental process and/or mathematical concepts. The steps can be performed by a human using pencil and paper but for the recitation of generic computing such as generic computer. The amendment has failed to preclude the limitations recited in the claims from being performed manually by a human via a mental process or by a human using pencil and paper. Therefore, under BRI, the steps of the claims can be performed in the human mind (with aid of pencil and paper), wherein the concepts is performed on a generic computer/the computer is merely tool to perform the concept.
MPEP 2106.04(a)(2)(III)(A) described the category of claims which can practically be performed in the human mind: such as: mere data collection, analysis, comparing known information, and display certain results of the collection and analysis. The present claims fall into the category of inventions which can practically be performed in the human mind, wherein the limitations of the claims involves data collection (receiving, generating, adjusting/ removing data), analysis/ comparing known information (processing and determining), and display certain results of the collection and analysis (output the data). The amendment has failed to preclude the limitations recited in the claims from being performed manually by a human via a mental process or by a human using pencil and paper.
In addition, the amended claims fail to integrate the abstract idea into a practical application or add significantly more. The claimed efficient computing by applying the abstract idea on a computer does not integrate the judicial exception into a practical application or provide inventive concepts (see MPEP 2106.05(f)). An improvement in the judicial exception itself is not an improvement in the technology. The efficient computing by applying the abstract idea on a computer does not integrate the judicial exception into a practical application or provide inventive concepts (see MPEP 2106.05(f)). Please see MPEP 2106.05(a), which also recites “the judicial exception alone cannot provide the improvement” because the improvement is provided by one or more additional elements. Further, MPEP 2106.05(a) also recites that “a claim whose entire scope can be performed mentally, cannot be said to improved computer technology”. To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. The claims must include more than mere instructions to perform the method on a generic components to qualify as an improvement to an existing technology.
[B] The use of a physical aid (e.g., pencil and paper or a slide rule) to help perform a mental step (e.g., a mathematical calculation) does not negate the mental nature of the limitation, but simply accounts for variations in memory capacity from one person to another (MPEP 2106.04(a)(2)(III)(B)).
[C] As indicated in the examiner’s remarks above and in the current office action, the argued limitations in the independent claims do not overcome the 35 USC 101 rejection. Thus, the independent claims are not allowable and their dependent claims are not allowed based on their dependencies.
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 1-8, 10-18, 20-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) 1, 11, and 21 recite a computer implemented method of generating a dataset that comprises receiving a dataset to be shared of a population having a population of size N…; determining a re-identification risk of sharing the received dataset for training the AI model by: generating a synthetic population dataset from the dataset to be shared, the synthetic population dataset comprising N records using a synthetic data generation process, wherein generating the synthetic population dataset from the dataset to be shared uses at least one of: a sequential decision tree process; a copula fitting process; a Gaussian copula fitting process; a d-vine copula fitting process; a deep learning process; and Bayesian Networks; generating a synthetic microdata dataset by sampling the synthetic dataset; determining an equivalence class size in the synthetic population dataset of records in the synthetic microdata dataset; and estimating the re-identification risk based on the population equivalence class size of records in the synthetic microdata dataset; and when the determined re-identification risk is acceptable, outputting the received dataset; and when the determined re-identification risk is not acceptable, adjusting the received dataset by applying an anonymization process applied to the received dataset and determining the re-identification risk of the adjusted dataset.
The limitations pertaining to the computer implemented method of generating a dataset, as drafted, is a process that, under its broadest reasonable interpretation covers performance of the limitations being an abstract idea that can be performed by a human using pen and paper but for the recitation of generic computer, being computer implemented method. Thus, other than reciting “a computer implemented method” or “executed by a computing device” nothing in the claim elements precludes the step from practically being performed by a human using pen and paper. If a claim limitation under its broadest reasonable interpretation covers performance in the mind, or by a human using pen and paper but for the recitation of generic computer component, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims 1, 11, and 21 recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claims 1, 11, and 21 only recites additional elements of “outputting the received dataset”; “a computer implemented method” as recited in claim 1, and “executed by a processor” as recited in claims 11 and 21 to perform the limitations recited in claims 1, 11, and 21. The processor is recited at a high level of generality (i.e., as a generic processor performing a generic computer function of generating a dataset) such that it amounts no more than mere instructions to apply the exception using a generic computer component. In addition, “outputting the received dataset ” is not an additional element that integrates the abstract idea into a practical application because output of the data is considered extra-solution activity. Accordingly, this additional elements do not integrate the abstract idea into a practical application because it does not impose meaningful limits on practicing the abstract idea. Thus, claims 1, 11, and 21 recite an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. With respect to the integration of the abstract idea into a practical application, the additional element of using a processor to perform the limitations recited in claim 1, 11, and 21 amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. In addition, “outputting an indication of the re-identification risk for use in evaluating sharing of the dataset to be shared” is not an additional element that integrates the abstract idea into a practical application because output of the data is considered extra-solution activity. The claims are not patent eligible.
Claims 2 and 12 recite “… wherein determining the re-identification risk is based on an estimate of a sample-to-population match rate and comprises: estimating the sample-to-population match rate according to:
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,where:
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is the estimate of the sample-to-population match rate; n is the size of the synthetic microdata dataset; and
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is the size of the equivalence class in the synthetic population dataset that record k of the synthetic microdata dataset belongs to”. The limitation is regarded as a process directed to a mental process and mathematical concept. Because the limitation(s) do(es) not add any significant element, the claim(s) do(es) not integrate the judicial exception into a practical application. Likewise, for the same rational, the claim(s) also therefore do(es) not recite additional elements that amount to significantly more than the judicial exception. Thus, the claims 2 and 12 are not eligible under 35 U.S.C 101.
Claims 3 and 13 recite “…determining an equivalence class size in the synthetic microdata dataset of records in the synthetic microdata dataset, wherein determining the re-identification risk is further based on an estimate of a population-to-sample match rate, estimating the population-to-sample match rate according to
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is the estimate of the population-to-sample match rate; N is the size of the synthetic dataset; n is the size of the synthetic microdata dataset; and
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is the size of the equivalence class in the synthetic dataset that record k of the synthetic microdata dataset belongs to”. The limitation is regarded as a process directed to a mental process and mathematical concept. Because the limitation(s) do(es) not add any significant element, the claim(s) do(es) not integrate the judicial exception into a practical application. Likewise, for the same rational, the claim(s) also therefore do(es) not recite additional elements that amount to significantly more than the judicial exception. Thus, the claims 3 and 13 are not eligible under 35 U.S.C 101.
Claims 4 and 14 recite “…wherein the re-identification risk is determined according to max (
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,
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)”. The limitation is regarded as a process directed to a mental process and mathematical concept. Because the limitation(s) do(es) not add any significant element, the claim(s) do(es) not integrate the judicial exception into a practical application. Likewise, for the same rational, the claim(s) also therefore do(es) not recite additional elements that amount to significantly more than the judicial exception. Thus, the claims 4 and 14 are not eligible under 35 U.S.C 101.
Claims 5 and 15 recite “...wherein the re-identification risk is determined according to
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”. The limitation is regarded as a process directed to a mental process and mathematical concept. Because the limitation(s) do(es) not add any significant element, the claim(s) do(es) not integrate the judicial exception into a practical application. Likewise, for the same rational, the claim(s) also therefore do(es) not recite additional elements that amount to significantly more than the judicial exception. Thus, the claims 5 and 15 are not eligible under 35 U.S.C 101.
Claims 6 and 16 recite “…wherein generating the synthetic population dataset from the dataset to be shared uses a copula fitting process”. The limitation is regarded as a process directed to a mental process and mathematical concept. Because the limitation(s) do(es) not add any significant element, the claim(s) do(es) not integrate the judicial exception into a practical application. Likewise, for the same rational, the claim(s) also therefore do(es) not recite additional elements that amount to significantly more than the judicial exception. Thus, the claims 6 and 16 are not eligible under 35 U.S.C 101.
Claims 7 and 17 recite “…wherein the copula is a Gaussian copula or a D-vine Copula”. The limitation is regarded as a process directed to a mental process and mathematical concept. Because the limitation(s) do(es) not add any significant element, the claim(s) do(es) not integrate the judicial exception into a practical application. Likewise, for the same rational, the claim(s) also therefore do(es) not recite additional elements that amount to significantly more than the judicial exception. Thus, the claims 7 and 17 are not eligible under 35 U.S.C 101.
Claims 8 and 18 recite “…wherein generating the synthetic population dataset from the dataset to be shared uses an average of a Gaussian copula fitting process and a D-vine copula fitting process”. The limitation is regarded as a process directed to a mental process and mathematical concept. Because the limitation(s) do(es) not add any significant element, the claim(s) do(es) not integrate the judicial exception into a practical application. Likewise, for the same rational, the claim(s) also therefore do(es) not recite additional elements that amount to significantly more than the judicial exception. Thus, the claims 8 and 18 are not eligible under 35 U.S.C 101.
Claims 10 and 20 recite “…determining if the re-identification risk is acceptable for sharing of the dataset to be shared; when the re-identification risk is not acceptable for sharing, modifying dataset to be shared and determining the re-identification risk of the modified data set”. The limitation is regarded as a process directed to a mental process and mathematical concept. Because the limitation(s) do(es) not add any significant element, the claim(s) do(es) not integrate the judicial exception into a practical application. Likewise, for the same rational, the claim(s) also therefore do(es) not recite additional elements that amount to significantly more than the judicial exception. Thus, the claims 10 and 20 are not eligible under 35 U.S.C 101.
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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FELICIA FARROW whose telephone number is (571)272-1856. The examiner can normally be reached M - F 7:30am-4:00pm (EST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alexander Lagor can be reached on (571)270-5143. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/F.F/Examiner, Art Unit 2437
/ALEXANDER LAGOR/Supervisory Patent Examiner, Art Unit 2437
