DETAILED ACTION
The following NON-FINAL Office Action is in response to application 18/957620. This communication is the first action on the merits. Claims 1-10 are currently pending and have been rejected as follows.
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 .
Information Disclosure Statement
Applicant filed an Information Disclosure Statement (IDS) on 11/22/2024. This filing is in compliance with 37 C.F.R. 1.97.
As required by M.P.E.P. 609(C), the applicant's submission of the Information Disclosure Statement is acknowledged by the examiner and the cited references have been considered in the examination of the claims now pending. As required by M.P.E.P. 609(C), a copy of the PTOL -1449 form, initialed and dated by the examiner, is attached to the instant office action.
Drawings
The drawings filed on 11/22/2024 are acceptable as filed.
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 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Here, under considerations of the broadest reasonable interpretation of the claimed invention, Examiner finds that the Applicant invented a method and system for data set validation to facilitate data set and algorithm bias certification and scoring. Examiner formulates an abstract idea analysis, following the framework described in the MPEP as follows:
Step 1: The claims are directed to a statutory category, namely a "method" (claims 6-10) and "system" (claims 1-5).
Step 2A - Prong 1: The claims are found to recite limitations that set forth the abstract idea(s), namely, regarding claim 1:
… pass the first data set through a series of filters to reduce the first data set to its core information content;
analyze the core information content to determine an information gain obtained by filtering the first data set based on an information entropy of the core information content;
certify the data set if the information gain exceeds a threshold;
create a certified model …;
use the certified model to generate a baseline output using the first data set as input; and
…
use the second data set as an input to the certified model to generate a set output;
perform a bias characterization analysis by comparing the baseline output to the set output;
generate a bias characterization score from the bias characterization analysis;
…
score the second data set based on a plurality of scoring metrics, which includes the bias characterization score and a provenance score, wherein the provenance score is determined by analyzing a plurality of provenance metrics comprising at least one of persistence failures, regulatory violations, and chain of custody inconsistencies; and create and store a data set value score as a weighted combination of the scores of the plurality of scoring metrics
Independent claim 6 recite substantially similar claim language.
Dependent claims 2-5, and 7-10 recite the same or similar abstract idea(s) as independent claims 1 and 6 with merely a further narrowing of the abstract idea(s) to particular data characterization and/or additional data analyses performed as part of the abstract idea.
The limitations in claims 1-10 above falling well-within the groupings of subject matter identified by the courts as being abstract concepts, specifically the claims are found to correspond to the category of:
"Certain methods of organizing human activity- fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)" as the limitations identified above are directed to data set validation to facilitate data set and algorithm bias certification and scoring and thus is a method of organizing human activity including at least commercial or business interactions or relations and/or a management of user personal behavior; and/or
"Mental processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)" as the limitations identified above include mere data observations, evaluations, judgements, and/or opinions, e.g. including user observation and evaluation through data set validation to facilitate data set and algorithm bias certification and scoring, which is capable of being performed mentally and/or using pen and paper.
Step 2A - Prong 2: Claims 1-20 are found to clearly be directed to the abstract idea identified above because the claims, as a whole, fail to integrate the claimed judicial exception into a practical application, specifically the claims recite the additional elements of:
" A system for data set validation, bias characterization, and valuation, comprising: a computing device comprising a memory, a processor, and a non-volatile data storage device; a data set and model certification manager comprising a first plurality of programming instructions that, when operating on the processor, cause the computing device to: retrieve a first data set from the non-volatile data storage device;… store the certified data set, the certified model, and the baseline output in the non-volatile data storage device; and a bias characterization auditor comprising a second plurality of programming instructions that, when operating on the processor, cause the computing device to: receive a second data set; retrieve the certified model and the baseline output from the non-volatile data storage device; … and store the bias characterization score in the non-volatile data storage device; and a data valuation engine comprising a third plurality of programming instructions that, when operating on the processor, cause the computing device to: " (claims 1 and 6) “by training a machine learning algorithm with the certified data set,” (claims 1 and 6) however the aforementioned elements merely amount to generic components of a general purpose computer used to "apply" the abstract idea (MPEP 2106.0S(f)) and thus fails to integrate the recited abstract idea into a practical application, furthermore the high-level recitation of receiving data from a generic "system" is at most an attempt to limit the abstract to a particular field of use (MPEP 2106.0S(h), e.g.: "For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie lndem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags).") and/or merely insignificant extra-solution activity (MPE 2106.05(g)) and thus further fails to integrate the abstract idea into a practical application;
Step 2B: Claims 1-10 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements as described above with respect to Step 2A Prong 2 merely amount to a general purpose computer that attempts to apply the abstract idea in a technological environment (MPEP 2106.0S(f)), including merely limiting the abstract idea to a particular field of use of data set validation to facilitate data set and algorithm bias certification and scoring as explained above, and/or performs insignificant extra-solution activity, e.g. data gathering or output, (MPEP 2106.0S(g)), as identified above, which is further found under step 2B to be merely well-understood, routine, and conventional activities as evidenced by MPEP 2106.0S(d)(II) (describing conventional activities that include transmitting and receiving data over a network, electronic recordkeeping, storing and retrieving information from memory, electronically scanning or extracting data from a physical document, and a web browser's back and forward button functionality). Therefore, similarly the combination and arrangement of the above identified additional elements when analyzed under Step 2B also fails to necessitate a conclusion that the claims amount to significantly more than the abstract idea directed to data set validation to facilitate data set and algorithm bias certification and scoring.
Claims 1-10 are accordingly rejected under 35 USC§ 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea(s)) without significantly more.
Note: The analysis above applies to all statutory categories of invention. As such, the presentment of any claim otherwise styled as a machine or manufacture, for example, would be subject to the same analysis.
For further authority and guidance, see:
MPEP § 2106
https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility
Subject Matter Overcoming Prior Art
Claims 1-10 are found to be provisionally allowable over the currently know prior art. The claims would be found to be allowable if they overcame the 35 USC 101 rejection.
Reasons for Overcoming the Prior Art
It appears that the instant invention is beyond the skill of one of ordinary skill in the art. Accordingly the invention would NOT have been obvious because one of ordinary skill could not have been expected to achieve it, NOR would they have been able to predict the results, and as such, they would have had no capability of expecting success.
The following is an examiner's statement of features not found in the prior art of record:
Claims 1-10 overcome the prior art of record and are found to be provisionally allowable. The following limitations of claim 1,
…
retrieve a first data set from the non-volatile data storage device;
pass the first data set through a series of filters to reduce the first data set to its core information content;
analyze the core information content to determine an information gain obtained by filtering the first data set based on an information entropy of the core information content;
certify the data set if the information gain exceeds a threshold;
create a certified model by training a machine learning algorithm with the certified data set;
use the certified model to generate a baseline output using the first data set as input;
…
receive a second data set;
retrieve the certified model and the baseline output from the non-volatile data storage device; use the second data set as an input to the certified model to generate a set output;
perform a bias characterization analysis by comparing the baseline output to the set output;
generate a bias characterization score from the bias characterization analysis;
…
score the second data set based on a plurality of scoring metrics, which includes the bias characterization score and a provenance score, wherein the provenance score is determined by analyzing a plurality of provenance metrics comprising at least one of persistence failures, regulatory violations, and chain of custody inconsistencies;
…
in combination with the remainder of the claim limitations are neither taught nor suggested, singularly or in combination, by the prior art of record. Furthermore, neither the prior art, the nature of the problem, nor knowledge of a person having ordinary skill in the art provides for any predictable or reasonable rationale to combine prior art teachings. Independent claim 6, and dependent claims 2-5 and 7-10 are likewise provisionally allowable.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
The closest prior art of record is described as follows:
Chandramouli et al. (U.S. Patent Application Publication Number 2012/0254333) - The abstract provides for the following: A method and apparatus for automatically identifying harmful electronic messages, such as those presented in emails, on Craigslist or on Twitter, Facebook and other social media websites, features methodology for discriminating unwanted garbage communications (spam) and unwanted deceptive messages (scam) from wanted, truthful communications based upon patterns discernable from samples of each type of electronic communication. Methods are proposed that enable discrimination of wanted from unwanted communications in short electronic messages, such as on Twitter and for multilingual application.
Myslinski (U.S. Patent Application Publication Number 2014/0188461) - The abstract provides for the following: A fact checking system is able to verify the correctness of information and/or characterize information by comparing the information with one or more sources. The fact checking system automatically monitors, processes, fact checks information and indicates a status of the information. Fact checking results are able to be validated by re-fact checking the fact check results.
Myslinski (U.S. Patent Application Publication Number 2013/0151240) - The abstract provides for the following: A fact checking system is able to verify the correctness of information and/or characterize information by comparing the information with one or more sources. The fact checking system automatically monitors, processes, fact checks information and indicates a status of the information. The fact checking system is able to be interactive with a user, so that a user is able to respond to a fact check result and receive additional information.
Hoffberg (U.S. Patent Number 9818136) - The abstract provides for the following: A system and method providing for communication and resolution of utility functions between participants, wherein the utility function is evaluated based on local information at the recipient to determine a cost value thereof. A user interface having express representation of both information elements, and associated reliability of the information. An automated system for optimally conveying information based on relevance and reliability.
Rashid Hussain Khokhar et al. “Enabling Secure Trustworthiness Assessment and Privacy Protection in Integrating Data for Trading Person-Specific Information.” The abstract provides for the following: With increasing adoption of cloud services in the e-market, collaboration between stakeholders is easier than ever. Consumer stakeholders demand data from various sources to analyze trends and improve customer services. Data-as-a-service enables data integration to serve the demands of data consumers. However, the data must be of good quality and trustful for accurate analysis and effective decision making. In addition, a data custodian or provider must conform to privacy policies to avoid potential penalties for privacy breaches. To address these challenges, we propose a twofold solution: 1) we present the first information entropy-based trust computation algorithm, IEB_Trust, that allows a semitrusted arbitrator to detect the covert behavior of a dishonest data provider and chooses the qualified providers for a data mashup and 2) we incorporate the Vickrey–Clarke–Groves (VCG) auction mechanism for the valuation of data providers’ attributes into the data mashup process. Experiments on real-life data demonstrate the robustness of our approach in restricting dishonest providers from participation in the data mashup and improving the efficiency in comparison to provenance-based approaches. Furthermore, we derive the monetary shares for the chosen providers from their information utility and trust scores over the differentially private release of the integrated dataset under their joint privacy requirements.
Overman et al. (WO Patent Application Publication Number WO/2010/042936) - The abstract provides for the following: One embodiment of the present invention relates to a system for measurement and verification of data related to at least one financial derivative instrument, wherein the data related to the at least one financial derivative instrument is associated with at least a first financial institution and a second financial institution, and wherein the first financial institution and the second financial institution are different from one another.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW H. DIVELBISS whose telephone number is (571) 270-0166. The fax phone number is 571-483-7110. The examiner can normally be reached on M-Th, 7:00 - 5:00. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O’Connor can be reached on (571) 272-6787.
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/M. H. D./
Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624