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 .
Status of the Application
This final office action is in response to the amendment filed on 12/09/2025. Claims 1, 12, and 13 have been amended. Claims 2 and 13 have been cancelled. Claims 1, 3-12, and 14-20 are currently pending and have been examined below.
Claim Rejections – 35 U.S.C. 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, 3-12, and 14-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Per step 1 of the eligibility analysis set forth in MPEP § 2106, subsection III, the claims are directed towards a process, machine, or manufacture.
Per step 2A Prong One, Claim 1 recites specific limitations which fall within at least one of the groupings of abstract ideas enumerated in MPEP 2106.04(a)(2) as follows:
generation of a record to be presented to the synthetic jury;
generation of questions to be presented to the synthetic jury;
generation of rules of decision to be employed by the synthetic jury; and
generation of rules defining deliberative procedures to be employed by the synthetic jury.
As noted above, these limitations fall within at least one of the groupings of abstract ideas enumerated in MPEP 2106.04(a)(2). Specifically, these limitations fall within the group Certain Methods of Organizing Human Activity (i.e., 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). That is – the limitations above describe a simulating a deliberative jury process which is both a legal interaction and a method of managing interactions between people that falls within the certain methods of organizing human activity grouping. Additionally, the steps above also fall within the mental process grouping of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. Specifically, a human being can mentally (or with pen and paper) generate a record and questions to be presented to a jury, generate rules of decisions to be employed by a jury, and generate rules defining deliberative procedures to be employed by the synthetic jury. Accordingly claim 1 recites an abstract idea.
Per step 2A Prong 2, the Examiner finds that the judicial exception is not integrated into a practical application. Claim 1 recites the additional limitations of:
wherein the synthetic jury, deliberations and decisions are simulated through a large-language model (preamble);
generation of a synthetic jury, consisting a plurality of individual synthetic jurors prompted with defined juror characteristics;
generation of a synthetic deliberative environment in which the plurality of synthetic jurors iteratively apply the specified deliberative procedures until the specified rules of decision have been
satisfied;
providing, to a user via an output device, a user interface that enables the user to review and analyze the synthetic jury's deliberations and decisions.
The additional limitations when viewed individually and when viewed as an ordered combination, and pursuant to the broadest reasonable interpretation, do not integrate the abstract idea into a practical application because each of the additional elements are recited at high level of generality implementing the abstract idea on a computer (i.e. apply it) or generally linking the use of the judicial exception to a particular technological environment. Specifically:
With respect to generation of a synthetic jury, consisting of one or a plurality of individual synthetic jurors prompted with defined juror characteristics, Examiner notes that this limitation is recited at a high level of generality prompting with juror characteristics to generate a synthetic jury. The broadest reasonable interpretation of this limitation in view of the amended preamble (i.e., “wherein the synthetic jury, deliberations and decisions are simulated through a large-language model”) and Applicant’s specification appears to refer to “prompting of a large language model (“LLM”) . . . with a prompt or prompts specifying relevant juror characteristics” (paragraph [0016]). Further, paragraph [0039] of the specification specifies that “the terms ‘large language model’ or ‘LLM’ are used broadly to refer to artificial intelligence foundation models capable of being directed through training (generally on massive language datasets) and prompting to generate responsive text consistent with specified conditions and queries. For example, a large language model (currently exemplified by such commercial available LLMs as GPT-4 or Claude 3) once prompted with specified demographic characteristics will generally (typically subject to specifiable bounds of variation) provide responses to queries in a range consistent with the range of responses that might be provided by human respondents sharing such characteristics.” Claim 1 does not specify any technical details as to how the large language model is used or trained to generate a synthetic jury. Therefore, the claimed prompting with jury characteristics to generate a synthetic jury is merely used to generally apply the abstract idea without placing any limits on how the generative AI models function. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015). Here, Examiner has reviewed Applicant’s specification and notes that the specification merely discusses generic “commercial[ly] available LLMs as GPT-4.” At this level of generality, the recitation of claim limitations that attempt to cover any solution to an identified problem (i.e, generating a synthetic jury by prompting a generic commercially available LLM) merely generally links the abstract idea to a technical field/environment, namely a generic computing environment applying generic generative AI.
Further, Examiner notes that Recentive Analytics, Inc. v. Fox Corp. et al., No. 2023-2437, slip op. at 18 (Fed. Cir. Apr. 18, 2025) recently held that claims “that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101.” Here, Examiner takes the position that utilizing generic LLMs to generate a synthetic jury is the mere application of generic machine learning to a new data environment. Because no improvement to the underlying machine learning models is disclosed, this limitation does not integrate the abstract idea into a practical application.
With respect to generation of a synthetic deliberative environment in which the one or plurality of synthetic jurors iteratively apply the specified deliberative procedures until the specified rules of decision have been satisfied; Examiner notes that this limitation is recited at a high level of generality generating a synthetic deliberative environment. The broadest reasonable interpretation of this limitation in view of the amended preamble (i.e., “wherein the synthetic jury, deliberations and decisions are simulated through a large-language model”) in view of Applicant’s specification appears to refer to “implement a synthetic deliberative environment through a large language model” (paragraph [0021]). Further, paragraph [0039] of the specification specifies that “the terms ‘large language model’ or ‘LLM’ are used broadly to refer to artificial intelligence foundation models capable of being directed through training (generally on massive language datasets) and prompting to generate responsive text consistent with specified conditions and queries. For example, a large language model (currently exemplified by such commercial available LLMs as GPT-4 or Claude 3) once prompted with specified demographic characteristics will generally (typically subject to specifiable bounds of variation) provide responses to queries in a range consistent with the range of responses that might be provided by human respondents sharing such characteristics.” Claim 1 does not specify any technical details as to how the large language model is used or trained to generate a synthetic deliberative environment. Therefore, the claimed generation of a synthetic deliberative environment through iteratively applies deliberative procedures merely generally applies the abstract idea without placing any limits on how the generative AI is used to generate the synthetic deliberative environment. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015). Here, Examiner has reviewed Applicant’s specification and notes that the specification merely discusses generic “commercial[ly] available LLMs as GPT-4.” At this level of generality, the recitation of claim limitations that attempt to cover any solution to an identified problem (i.e., generating a synthetic deliberative environment through iteratively applying deliberative procedures) merely generally links the abstract idea to a technical field/environment, namely a generic computing environment applying generic generative AI.
Further, Examiner notes that Recentive Analytics, Inc. v. Fox Corp. et al., No. 2023-2437, slip op. at 18 (Fed. Cir. Apr. 18, 2025) recently held that claims “that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101.” Here, Examiner takes the position that utilizing generic LLMs/AI to generate a synthetic deliberative environment is the mere application of generic machine learning to a new data environment. Because no improvement to the underlying machine learning models is disclosed, this limitation does not integrate the abstract idea into a practical application.
Finally, with respect to “providing, to a user via an output device, a user interface that enables the user to review and analyze the synthetic jury's deliberations and decisions”, Examiner notes that this limitation is recited at a high level of generality using a generic output device and user interface to display the jury deliberations and decisions. At this level of generality, the generic output device and user interface merely generally links the abstract idea to a particular technological environment or merely utilizes a computer as a tool to perform the abstract idea.
Under step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are recited at a high level of generality and only generally link the use of the judicial exception to a particular technological environment. Thus, the same analysis applies here in 2B, i.e., mere instructions to apply an exception is a particular technological environment cannot provide an inventive concept.
Independent claim 12 is similar in scope to independent method claim 1 but adds that the synthetic deliberative processes is performed a plurality of times. Claim 12 further specifies “each process involving variations to none, some or all of the following features” which under the broadest reasonable interpretation includes a plurality of synthetic deliberative processes with no variations (i.e., running an identical deliberative process multiple times). At most this further narrows the abstract idea in claim 1, by performing the method multiple times and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Dependent claims 3-11 and 14-20 are rejected on a similar rational to the claims upon which they depend. Specifically, dependent claims 3-11 and 14-20 merely further narrow the abstract idea and therefore do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
35 U.S.C. 101
Applicant's arguments, see pages 6-12, filed 12/09/2025, with respect to the rejection(s) of claims 1, 3-12, and 14-20 under 35 U.S.C. 101 have been fully considered but are not persuasive.
First, Applicant argues that:
the claims are directed to generation of a synthetic simulation for analysis, not to processes regulating any actual interactions. Yet the judicial examples identified in MPEP 2106.04(a)(2)(11) (B)- (C) are directed to actual human interactions, whether commercial, legal, or social. Even the MPEP examples in which the activity of a single person is at issue incorporate an underlying interactive or transactional context. MPEP 2106.04(a)(2)(11) (introduction) (examples of a single person signing a contract online, or a method of anonymous (remarks page 7).
Examiner respectfully disagrees and replies that the limitations of “generation of a record to be presented to the synthetic jury; generation of questions to be presented to the synthetic jury; generation of rules of decision to be employed by the synthetic jury; and generation of rules defining deliberative procedures to be employed by the synthetic jury” describe the process of creating legal questions, generating rules for legal decisions, and generating rules around deliberative legal procedures which examiner interprets as legal interactions. Whether the record is presented to a real jury, a mock jury, or a simulated jury may be relevant to the question of whether the abstract idea is integrated into a practical application, but it does not negate the fact that generating a legal record, generating rules of decision, and generating rules of deliberative procedures are limitations that describe a method of organizing human activities. Moreover, as noted below, even if these limitations were not considered to be a method of organizing human activities, they would still fall within the “mental processes” grouping of abstract ideas.
Second, Applicant argues that:
Applicant respectfully responds that the claims as an ordered combination are not directed simply to the generation of records and questions to be presented to a jury, or rules of decision to be employed by a jury, or rules of deliberative procedures. Rather, the claims are directed to the production of a synthetically generated simulation of synthetic jury deliberations, created under specifically defined and varied simulation conditions in order to permit statistically meaningful analysis of the resulting deliberative records (remarks page 8).
First, the human mind is not capable of neutral self-direction and self-analysis independent of cognitive and other biases. In other words, no inquiring human mind, no matter how much time ( or pencils and paper) is available to it, is capable merely through abstract thought ofreliably (and repeatedly) comparing and contrasting deliberative results across a range of juries with differing demographic characteristics and biases, some of which, consciously or not, may also be shared by the inquiring human (remarks page 9).
In addition, simulation and statistical analysis of large scale synthetic jury simulation is an entirely new technical tool, allowing data to be generated and questions to be posed and analyzed that could not previously be generated or analyzed through any means (remarks page 9).
Examiner respectfully disagrees and replies that and replies that the limitations of “generation of a record to be presented to the synthetic jury; generation of questions to be presented to the synthetic jury; generation of rules of decision to be employed by the synthetic jury; and generation of rules defining deliberative procedures to be employed by the synthetic jury” fall within the mental process grouping of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. Specifically, a human being can mentally (or with pen and paper) generate a record and questions to be presented to a jury, generate rules of decisions to be employed by a jury, and generate rules defining deliberative procedures to be employed by the synthetic jury. Examiner notes that these steps could be performed whether or not the record, questions, rules of decision, or rules defining deliberative procedures were ultimately presented to a real jury, a mock jury or a synthetic jury. Applicant’s arguments related simulated jury deliberations are not relevant to the analysis under step 2A Prong One because all of the identified elements can be performed mentally.
Third, Applicant argues that:
The claimed synthetic jury simulation is not an abstract concept, or the "idea of a solution", but a particular solution to the technical problem of generating and analyzing synthetic jury data under controlled conditions. The claims are directed to a specific process for prompting a synthetic jury comprised of large language model juror agents. The claims do not encompass every possible method of applying machine learning or artificial intelligence tools to simulate or study juries. Rather, the claims are directed to procedures governing a structured simulation environment such that specifically defined and characterized deliberations engaged in by demographically prompted large-language model juror-agents can be analyzed in specific iterative contexts, and the very structure and restrictions of the procedural limitations defined by the claims are necessary to allow results that are capable of meaningful study. Other applications of machine learning generally or large language model techniques to jury and deliberative modeling are not foreclosed (remarks page 11).
Examiner respectfully disagrees. The claims are recited at a very high level of generality with the sole recitation of the specific type of artificial intelligence used provided in the amended preamble, which recites “where the synthetic jury, deliberations, and decisions are simulated through a large language model. The broadest reasonable interpretation of the limitation “generation of a synthetic jury, consisting a plurality of individual synthetic jurors prompted with defined juror characteristics” in view of the amended preamble (i.e., “wherein the synthetic jury, deliberations and decisions are simulated through a large-language model”) and Applicant’s specification appears to refer to “prompting of a large language model (“LLM”) . . . with a prompt or prompts specifying relevant juror characteristics” (paragraph [0016]). Further, paragraph [0039] of the specification specifies that “the terms ‘large language model’ or ‘LLM’ are used broadly to refer to artificial intelligence foundation models capable of being directed through training (generally on massive language datasets) and prompting to generate responsive text consistent with specified conditions and queries. For example, a large language model (currently exemplified by such commercial available LLMs as GPT-4 or Claude 3) once prompted with specified demographic characteristics will generally (typically subject to specifiable bounds of variation) provide responses to queries in a range consistent with the range of responses that might be provided by human respondents sharing such characteristics.” Claim 1 does not specify any technical details as to how the large language model is used or trained to generate a synthetic jury. Therefore, the claimed prompting with jury characteristics to generate a synthetic jury is merely used to generally apply the abstract idea without placing any limits on how the generative AI models function. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015). Here, Examiner has reviewed Applicant’s specification and notes that the specification merely discusses generic “commercial[ly] available LLMs as GPT-4.” At this level of generality, the recitation of claim limitations that attempt to cover any solution to an identified problem (i.e, generating a synthetic jury by prompting a generic commercially available LLM) merely generally links the abstract idea to a technical field/environment, namely a generic computing environment applying generic generative AI.
Fourth, Applicant argues that:
in enabling the generation of large scale synthetic jury modeling, the application enables a body of deliberative data and a field of study that have never previously existed (remarks page 11).
Similarly, the claims rejected by the Federal Circuit in Recentive Analytics, Inc. v. Fox Corp. et al., No. 2023-2437, slip op. at 15 (Fed. Cir. Apr. 18, 2025) involved the application of machine learning techniques merely to accomplish "task[s] [generation of event scheduling and network maps] previously undertaken by humans with greater speed and efficiency than could previously be achieved." The patent claims at issue in Recentive did not apply machine learning to enable study and analysis that had previously been impossible; they simply applied machine learning to a new data environment in order to accomplish - more efficiently - what was already previously possible (remarks page 12).
Examiner respectfully disagrees. Examiner notes that Recentive Analytics, Inc. v. Fox Corp. et al., No. 2023-2437, slip op. at 18 (Fed. Cir. Apr. 18, 2025) held that claims “that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101.” Here, even if the simulation of jury deliberations is viewed as a new data environment. Examiner takes the position that utilizing generic LLMs to generate a synthetic jury is the mere application of generic machine learning to a new data environment. Because no improvement to the underlying machine learning models is disclosed, this limitation does not integrate the abstract idea into a practical application.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US Patent Application Publication Number 20250265442 (“Brown”) discloses AI-generated juror panels assess case persuasiveness and simulation of jury decision-making
US Patent Application Publication Number 20250259082 (“Crabtree”) discloses a jury of AI agents evaluates arguments presented by different agents, while a judge agent moderates the debate, enforces constraints, and ensures logical consistency
US Patent Application Publication Number 20190295199 (“O'Dorisio”) discloses a legal simulation of a jury trial, the intelligent environment may comprise a courtroom, an AI judge, a first AI opposing counsel, a second AI opposing counsel, an AI co-counsel, an AI witness, and at least one AI juror.
However, the prior art fails to teach each and every limitation as claimed, and would involve hindsight reasoning to arrive at the claimed invention. Therefore, the claims are considered allowable over the prior art.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ALLAN J WOODWORTH, II/Primary Examiner, Art Unit 3622