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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/10/2026 has been entered.
Response to Amendment
The Amendment filed 3/10/2026 has been entered. Claims 4-5 and 12-13 are amended. Claims 1-15 are pending in the application.
Drawings
The drawings are objected to because Figure 3, in step box S310, recites the term "electronic social agent", which is inconsistent with the "digital assistant" and "input/output (I/O) device" terminology used in the specification (see, for example, [0056] describing Fig. 3), in Figures 1 and 2, and in the claims. The term "electronic social agent" does not appear elsewhere in the disclosure. Figure 3 should be brought into conformity with the description and claims. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as "amended." Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either "Replacement Sheet" or "New Sheet" pursuant to 37 CFR 1.121(d). The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities:
• [0009] recites "a system for providing a recommendation for a recommendation by a digital assistant", which repeats the phrase "a recommendation"; the duplicate phrase "for a recommendation" should be deleted.
• [0013] recites "Figure 3 is a flowchart of a method for selecting a customized persuasive action for presenting a recommendation for a user of an according to an embodiment", which omits the noun following "of an"; the sentence appears intended to read "for a user of an I/O device according to an embodiment."
• Figure 3, in step box S310, and any corresponding text use the term "electronic social agent" for what the remainder of the disclosure (see, for example, [0056] describing Fig. 3) terms the "digital assistant 120" operated by the "I/O device 170"; consistent terminology is required under 37 CFR 1.71(a), which calls for full, clear, concise, and exact terms.
Appropriate correction is required.
Claim Rejections - 35 U.S.C. 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-15 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention.
Independent claim 1 (a method), independent claim 8 (a non-transitory computer readable medium), and independent claim 9 (a system) each recite analyzing a historical dataset related to the user to compile a persuasive action, wherein the persuasive action is customized based on at least one convincing method and based on the analysis of the historical dataset and the current state of the user, and further recite that the persuasive action is a convincing method having a highest probability to cause the user to accept the recommendation of the digital assistant. These limitations are recited in functional, result-oriented terms: they claim the outcome of selecting the convincing method that has the highest probability of causing user acceptance, without reciting how that analysis and selection are performed. The specification does not reasonably convey possession of an inventor of how this claimed function is achieved. The specification discloses the desired result, namely a probability score that may be a number from 0 to 1 (specification [0052]), and it provides example message text for seven categories of convincing methods, including authority-based, consensus-based, liking-based, reward-based, reciprocity-based, commitment-based, and scarcity-based persuasive actions (specification [0042]-[0048]). However, the specification never discloses the specific algorithm by which the historical dataset and the current state are analyzed to compute that probability or to select the highest-probability convincing method. The specification states only that the analysis may be achieved using one or more algorithms, such as a machine learning algorithm (specification [0036], [0050], and [0058]), and that a customized persuasive action may be determined by learning from user behavior using reinforcement learning techniques (specification [0033] and [0063]). No model architecture, no input feature set, no input-to-output mapping, no training procedure, and no scoring computation is disclosed.
Merely stating that a computer performs a function, such as selecting the convincing method having the highest probability, without disclosing how the computer performs that function, does not demonstrate possession of the claimed invention. See Williamson v. Citrix Online, LLC, 792 F.3d 1339 (Fed. Cir. 2015); Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671 (Fed. Cir. 2015). Furthermore, the recited convincing method having a highest probability is a genus defined by the function or result it achieves. The example convincing methods of specification paragraphs [0042]-[0048] are presented as illustrative message text and are not tied by any disclosed common structure or algorithm to the claimed highest-probability selection. A genus claimed solely by a desired function or result, without disclosure of a representative number of species or of structural features common to the members of the genus that achieve that function, does not satisfy the written description requirement. See Ariad Pharmaceuticals, Inc. v. Eli Lilly & Co., 598 F.3d 1336, 1350 (Fed. Cir. 2010) (en banc); Abbvie Deutschland GmbH and Co. v. Janssen Biotech, Inc., 759 F.3d 1285, 1300-1301 (Fed. Cir. 2014).
Dependent claims 2-7 and 10-15 incorporate by reference all of the limitations of the independent claim from which they depend, including the analyzing and highest-probability selection limitations discussed above, and they do not add any disclosure that cures the deficiency. Accordingly, dependent claims 2 through 7 and 10 through 15 are rejected for the same reasons. Claims 7 and 15, which further recite computing a probability for each convincing method based in part on the current state of the user and using the convincing method with the highest probability, compound the deficiency by reciting the very probability computation that the specification does not disclose.
Dependent claims 3 and 11 further recite applying a machine learning model trained to determine the current state based on the collected real-time data. The specification states only that the collected dataset may be input into a machine learning model that is trained to provide a current state of the user (specification [0058]) and that the dataset may be fed into an algorithm such as a machine learning model (specification [0036]). The specification does not disclose the type of model, the training data or labeling, the input features, or the model architecture. Claims 3 and 11 therefore fail the written description requirement for this additional reason and do not cure the deficiency of their parent claims.
Claims 1 through 15 are rejected under 35 U.S.C. 112(a) as failing to comply with the enablement requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the invention commensurate in scope with these claims.
The claims are not enabled to their full scope with respect to compiling and selecting the persuasive action that is the convincing method having the highest probability to cause the user to accept the recommendation (claims 1, 8, and 9 and all of their dependents), and with respect to the machine learning model trained to determine the current state (claims 3 and 11). Whether undue experimentation is required is determined in light of the factors set forth in In re Wands, 858 F.2d 731, 737 (Fed. Cir. 1988):
(1) The breadth of the claims is broad. The independent claims reach any analysis of any historical dataset that yields the highest-probability convincing method, over an open-ended genus of convincing methods, so the claims demand commensurately broad enabling disclosure.
(2) The nature of the invention is a digital-assistant recommendation system whose asserted advance is selecting the persuasive action most likely to obtain user acceptance; the predictive selection algorithm is the heart of the invention.
(3) The state of the prior art included recommendation systems, sensor data analysis, and machine learning classifiers, but the art did not supply a known algorithm mapping a user historical dataset and current state to the highest-probability persuasion method.
(4) The level of ordinary skill is high, namely a person having a bachelor's degree in computer science with two to three years of experience in digital assistants, recommendation systems, and applied machine learning.
(5) The level of predictability in the art of software is generally high; however, predictability presupposes that the specification teaches the algorithm to be implemented. Here the specification teaches only the desired result and example message text, leaving the operative analysis, scoring, and selection algorithm for the skilled artisan to devise.
(6) The amount of direction provided by the inventor for the operative function is minimal. The specification provides example message templates (specification [0042]- [0048]) and a score range of 0 to 1 (specification [0052]) but no guidance on computing the score, ranking the methods, selecting features, or training a model. References to a machine learning algorithm and to reinforcement learning techniques are conclusory labels.
(7) There are no working examples of the selection algorithm. The persuasion-message paragraphs are illustrative message text rather than worked examples of computing the highest probability, and the walk-through of specification [0050]-[0051] asserts the result without showing the computation.
(8) The quantity of experimentation needed is undue. To practice the full claimed scope, a skilled artisan would have to design, train, and validate the entire predictive persuasion-selection model from scratch, which is open-ended research rather than routine implementation of a disclosed teaching.
Weighing the Wands factors as a whole, the breadth of the functional claims, the centrality of the undisclosed selection algorithm, the minimal direction provided, and the absence of any working example of the computation outweigh the general predictability of software. A person of ordinary skill in the art would be required to engage in undue experimentation to make and use the full scope of the claimed invention. Accordingly, claims 1-15 are rejected as failing to comply with the enablement requirement.
Claim Rejections - 35 U.S.C. 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The specific bases for indefiniteness are set forth below.
Regarding claims 1, 8, and 9: each independent claim recites collecting, via one or more sensors connected to the I/O device, real-time data related to a user of the digital assistant and later recites determining a recommendation for a user of the digital assistant to perform a certain activity, with intervening references to the user. The claims thus introduce the indefinite article 'a user of the digital assistant' twice, after 'the user' has already been used. This renders the claims indefinite because it is unclear whether the second recitation of 'a user of the digital assistant' refers to the same user whose data was collected or to a different, second user, and therefore whether each later recitation of 'the user' refers consistently to a single user. A person having ordinary skill in the art would not be apprised with reasonable certainty whether the claimed method, medium, and system are directed to providing a recommendation to a single user throughout or permit the recommendation to be determined for a user other than the one whose data was collected. For purposes of examination, and to advance prosecution, all recitations of 'a user' and 'the user' are interpreted under the broadest reasonable interpretation as referring to the same single user of the digital assistant, consistent with the specification, which describes a single user whose data is collected, whose current state is determined, and to whom the recommendation is presented (for example, specification [0020], [0034]-[0035], and [0050]).
Regarding claims 1, 8, and 9: each independent claim recites determining, in one of real-time and near real-time, a current state of the user based on the collected real-time data. The term 'near real-time' is a relative term which renders the claims indefinite. The term 'near real-time' is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Although the specification uses the phrase 'near real-time' (for example, specification [0035] and [0037]), it supplies no numerical tolerance, latency bound, or other objective measure of how much delay still qualifies as 'near' real-time, leaving the boundary between 'near real-time' processing and ordinary, non-real-time processing uncertain. See MPEP 2173.05(b); Datamize, LLC v. Plumtree Software, Inc., 417 F.3d 1342, 1350 (Fed. Cir. 2005). For purposes of examination, 'in one of real-time and near real-time' is interpreted under the broadest reasonable interpretation to encompass determining the current state contemporaneously with, or shortly after, collection of the underlying sensor data, grounded in specification [0035] and [0037]; any short, undefined processing delay is read to satisfy the limitation.
Regarding claims 1, 8, and 9: each independent claim recites wherein the persuasive action is a convincing method having a highest probability to cause the user to accept the recommendation of the digital assistant. The superlative term 'a highest probability' is a relative term which renders the claims indefinite. The term 'a highest probability' is not defined by the claim, the specification does not provide, within the four corners of the independent claims, a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The independent claims recite no objective standard, computed score, comparison set, or threshold by which a probability is determined to be 'highest,' and the indefinite article 'a highest' (rather than 'the highest' tied to a computed quantity) further obscures the reference set over which the maximum is taken. The act of computing and comparing probabilities for plural convincing methods appears only in dependent claims 7 and 15, so on the face of the independent claims it is unclear what set of candidate convincing methods the 'highest' is measured against or how 'highest' is to be evaluated. See MPEP 2173.05(b); Datamize, 417 F.3d at 1350. For purposes of examination, the limitation is interpreted under the broadest reasonable interpretation, in light of specification [0051]-[0052] (which describe computing a probability score from zero to one for each of a plurality of persuasive actions and selecting the persuasive action having the highest probability score to be accepted by the user), as requiring that the applied persuasive action be the convincing method that, among the candidate convincing methods evaluated, is selected as most likely to cause the user to accept the recommendation.
Regarding claim 4: the claim recites the limitation a current state of the user in the phrase 'wherein the determining, in one of real-time and near real-time, a current state of the user.' The claim introduce the indefinite article ‘a current state of the user’ after ‘the current state of the user’ has already been used in claim 1 from which claim 3 and then from which claim 4 depends. This renders the claims indefinite because it is unclear whether the second recitation of 'a current state of the user' refers to the same current state of the user or to a different current state of the user. A person having ordinary skill in the art would not be apprised with reasonable certainty what the claimed method is directed to. For purposes of examination, and to advance prosecution, said recitation is interpreted under the broadest reasonable interpretation as referring to the current state of the user.
Regarding claims 7 and 15: each claim recites computing a probability for each convincing method based in part of the current state of the user. The phrase 'based in part of the current state of the user' is grammatically ambiguous. The preposition 'of' in 'based in part of' is not idiomatic, and it is unclear whether the intended meaning is that the probability is based in part on the current state of the user (the current state being one of several bases) or whether some other relationship is intended. A person having ordinary skill in the art could not determine with reasonable certainty the intended basis for the recited probability computation. See MPEP 2173.05; Nautilus, 572 U.S. at 901. For purposes of examination, the limitation is interpreted under the broadest reasonable interpretation as computing, for each candidate convincing method among the enumerated alternatives, a probability that is based in part on the current state of the user, grounded in specification paragraphs [0051]-[0052].
Regarding claim 12: the claim recites the limitation the I/O device in the phrase 'obtained from sources external to the I/O device.' There is insufficient antecedent basis for this limitation in the claim. Claim 12 depends from claim 11, which depends from independent system claim 9. Claim 9 and claim 11 recite 'the system,' 'one or more sensors connected to the system,' and 'the system executing the digital assistant,' but neither claim 9 nor claim 11 introduces 'an input/output (I/O) device.' Accordingly, the recitation of 'the I/O device' in claim 12 lacks a prior corresponding recitation of an I/O device in its dependency chain. For purposes of examination, 'the I/O device' in claim 12 is interpreted as ‘the system’.
Claims 2-7 depend, directly or indirectly, from claim 1, and claims 10-15 depend, directly or indirectly, from claim 9. Each of these dependent claims incorporates by reference all of the limitations of its respective independent claim and does not cure the indefiniteness identified above with respect to claims 1 and 9 (including the relative terms 'near real-time' and 'a highest probability,' and the ambiguous multiple introduction of 'a user'). Each such dependent claim is therefore rejected under 35 U.S.C. 112(b) for the same reasons as its parent. Claims 7 and 15, and claim 12 are additionally rejected for the further, independent reasons set forth above.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The analysis of the claims will follow the 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (“2019 PEG”).
Claim 1
Step 1: This claim recites “A method for…, comprising:”; therefore, it is directed to the statutory category of a process.
Step 2A Prong 1: This claim recites, inter alia:
determining, in one of real-time and near real-time, a current state of the user based on the collected real-time data, wherein the current state of the user is a state of the user and a state of the environment surrounding the user: These limitations recite a mentally performable process of evaluation in near real-time of a current state of the user based on observed real-time data, wherein the current state of the user is a location state of the user and a state of the environment surrounding the user consistent with Applicant’s specification [0100] where the current state may indicate that the user is sitting in the living room and a time.
determining a recommendation for a user (interpreted as the user per the 35 U.S.C. 112(b) rejection set forth above) of the digital assistant to perform a certain activity, wherein the recommendation is determined based on the current state of the user: These limitations recite a mentally performable process with the aid of pen and paper of observing the current state of the user of the digital assistant, such a recommendation of nearing bedtime, and using judgement/evaluation to provide a recommendation to perform a certain activity, such as to a recommendation to shutoff the digital assistant consistent based on being in the living room at a particular time consistent with Applicant specification [0017]-[0018], [0100].
analyzing a historical dataset related to the user to compile a persuasive action, wherein the persuasive action is customized based on at least one convincing method and based on the analysis of the historical dataset and the current state of the user: These limitations recite a mentally performable process with the aid of pen and paper of using judgement/evaluation on an observed historical dataset related , such as historically when the user has gone to bed, to select a persuasive action, wherein the persuasive action is customized based on at least one convincing method, such as reminding the user of a set goal for bedtime previously established, and based on the mental evaluation of the historical dataset and the observed current time of the user consistent with Applicant’s specification [0020], [0026], [0034], [0047].
wherein the persuasive action is a convincing method having a highest probability to cause the user to accept the recommendation of the digital assistant: These limitation recites a mathematical relationship of organizing and manipulating information wherein persuasive action is a convincing method to cause the user to accept the recommendation of the digital assistant through mathematical correlating of the persuasive action as convincing method having a highest probability to cause the user to accept the recommendation similar to organizing information and manipulating information through mathematical correlations see MPEP 2106.04(a)(2)(I)(A)(iv).
Thus, this claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of this claim are as follows:
A method for providing a recommendation by a digital assistant using a persuasive action, comprising: collecting, via one or more sensors connected to the I/O device, real-time data related to a user of the digital assistant and an environment surrounding the user; presenting the determined recommendation by applying the persuasive action: These additional elements merely recite insignificant extra-solution activities of mere data gathering and output as all uses of the judicial exception of determining a current state of the user and analyzing to compile a persuasive action require collecting real-time data related to a user of the digital assistant and an environment surrounding the user and for the determined recommendation to be presented by applying the persuasive action. See MPEP 2106.05(g).
executed by an input/output (I/O) device, wherein the recommendation is presented via at least one of a speaker and a display unit of the I/O device executing the digital assistant: These additional elements are recited at a high level of generality and merely amount to invoking computers or other machinery, e.g. executed by an input/output (I/O) device and presenting via at least one of a speaker and a display merely as a tool, to apply the underlying mental processes corresponding to determining a recommendation. See MPEP 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception when analyzed with this claim as a whole do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include insignificant extra-solution activities of data gathering and output recited by “A method for providing a recommendation by a digital assistant using a persuasive action, comprising: collecting, via one or more sensors connected to the I/O device, real-time data related to a user of the digital assistant and an environment surrounding the user; presenting the determined recommendation by applying the persuasive action”. These insignificant extra-solution activities are well-understood routine and conventional activities similar to receiving or transmitting data over a network and presenting offers and gathering statistics see MPEP 2106.05(d)(II). Additional elements further include invoking computers or other machinery to apply the underlying judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP 2106.05.
Claim 2
Step 1: a process, as in claim 1.
Step 2A Prong 1: This claim recites, inter alia:
determining an alternate recommendation when the user rejects the presented recommendation: These limitations recite a mental process of using judgement/evaluation to determine an alternate recommendation when the user is observed to have rejected the presented recommendation.
compiling an alternate persuasive action based on analysis of the historical dataset: These limitations recite a mental process of using judgement/evaluation to selectively determine an alternate persuasive action based on mentally evaluating the historical dataset consistent with Applicant’s specification [0038].
Thus, this claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of this claim are as follows:
monitoring a feedback of the user to the presented recommendation: These additional elements merely recite insignificant extra-solution activity of mere data gathering of feedback of the user to the presented recommendation. See MPEP 2106.05(g).
presenting the determined alternate recommendation by applying the alternate persuasive action: These additional elements are recited at a high level of generality to recite the idea of presenting the determined alternative recommendation by applying the alternate persuasive action but fails to recite details of how the alternate persuasive action is applied and does not describe any mechanism for presenting the determined alternate recommendation, thus this limitation merely amounts to a recitation of the words “apply it” by reciting only the idea of presenting the determined alternate recommendation by applying the alternate persuasive action as an outcome but fails to recite details of how the outcome is accomplished and does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception when analyzed with this claim as a whole do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include insignificant extra-solution activities of data gathering and output recited by “monitoring a feedback of the user to the presented recommendation”. These insignificant extra-solution activities are well-understood routine and conventional activities similar to recording a customer’s order see MPEP 2106.05(d)(II). Additional elements further include adding the words equivalent to “apply it” with the judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP 2106.05.
Claim 3
Step 1: a process, as in claim 1.
Step 2A Prong 1: This claim recites, inter alia:
wherein determining the recommendation further comprises: determine the current state based on the collected real-time data: These limitations further recite a mental process of determining the current state based on observation of the collected real-time data.
Thus, this claim recites a judicial exception.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of this claim are as follows:
applying a machine learning model trained to: These additional elements are recited at a high level of generality and represent applying generic machine learning algorithm to implement the underlying abstract idea. See MPEP 2106.05(f).
Thus, the way in which the additional elements use or interact with the judicial exception when analyzed with this claim as a whole do not integrate the judicial exception into a practical application.
Step 2B: The additional elements from Step 2A Prong 2 include invoking computers or other machinery to apply the underlying judicial exception. Thus, the additional elements, viewed individually or in combination, do not provide an inventive concept or otherwise amount to significantly more than the abstract idea itself. See MPEP 2106.05.
Claim 4
Step 1: a process, as in claim 3.
Step 2A Prong 1: This claim recites, inter alia:
wherein the determining, in one of real-time and near real-time, a current state of the user (interpreted as the current state of the user per the 35 U.S.C. 112(b) rejection set forth above) is further based on historical data related to past activity of the user obtained from sources external to the I/O device: These limitations recite furthering the mentally performable process of determining, in one of real-time and near real-time, the current state of the user by further observing the historical data related to past activity of the user obtained from sources external to the I/O device.
Step 2A Prong 2 & Step 2B: There are no additional elements recited so this claim does not provide a practical application and is not considered to be significantly more. As such, this claim is patent ineligible.
Claim 5
Step 1: a process, as in claim 1.
Step 2A Prong 1: This claim recites, inter alia:
wherein the convincing method of the persuasive action is at least one of: authority-based persuasive, consensus-based persuasive, reward-based persuasive, reciprocity-based persuasive, commitment-based persuasive, and scarcity-based persuasive action: These limitations further the mentally performable process in claim 1 of customizing a persuasive action by further using judgement/evaluation to customize the persuasive action using a convincing method that is anyone of the convincing method of authority-based persuasive, consensus-based persuasive, reward- based persuasive, reciprocity-based persuasive, commitment-based persuasive, and scarcity-based persuasive action consistent with Applicant’s specification [0041]-[0048].
Step 2A Prong 2 & Step 2B: There are no additional elements recited so this claim does not provide a practical application and is not considered to be significantly more. As such, this claim is patent ineligible.
Claim 6
Step 1: a process, as in claim 5.
Step 2A Prong 1: This claim recites, inter alia:
compiling the persuasive action to communicate at least one preconfigured message: These limitations recite a mentally performable process with the aid of pen and paper of compiling the persuasive action that was mentally evaluated to communicate at least one preconfigured message.
Step 2A Prong 2 & Step 2B: There are no additional elements recited so this claim does not provide a practical application and is not considered to be significantly more. As such, this claim is patent ineligible.
Claim 7
Step 1: a process, as in claim 5.
Step 2A Prong 1: The claim recites, inter alia:
further comprising: computing a probability for each convincing method based in part of the current state of the user; and using the convincing method with the highest probability to compile the persuasive action: These limitations recite a mentally performable process of using judgement/evaluation to determine a probability score for each convincing method based in part on observing the current state of the user and using mental judgement/evaluation to selectively compile the persuasive action associated with the highest computed probability score consistent with Applicant’s specification [0052]-[0053]. Additionally, these limitations recite mathematical concepts of a mathematical calculation to compute a probability and mathematical relationship relating the highest probability with the persuasive action variable
Step 2A Prong 2 & Step 2B: There are no additional elements recited so the claim does not provide a practical application and is not considered to be significantly more. As such, the claim is patent ineligible.
Claim 8
Step 1: This claim is directed to “A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process, the process comprising:”; therefore, this claim is directed to the statutory category of an article of manufacture.
Step 2A Prong 1: This claim recites the same abstract ideas as in claim 1 as the judicial exception.
Step 2A Prong 2: The judicial exception recited in this claim is not integrated into a practical application. The only difference between claim 8 and claim 1 is that claim 8 is directed to “A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process, the process comprising:” However, mere recitation that a judicial exception is to be performed using generic computer equipment in their ordinary capacity, i.e. a non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process, cannot meaningfully integrate the judicial exception into a practical application. See MPEP 2106.05(f). With that exception, the analysis at this step mirrors that of claim 1.
Step 2B: The additional elements from Step 2A Prong 2 of this claim does not contain significantly more than the judicial exception. The only difference between claim 8 and claim 1 is that claim 8 is directed to “A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process, the process comprising:” However, mere recitation that a judicial exception is to be performed using generic computer equipment in their ordinary capacity, i.e. a non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process, cannot amount to significantly more than the judicial exception. See MPEP 2106.05(f). With that exception, the analysis at this step mirrors that of claim 1.
Claims 9-15
Step 1: These claims are directed to “A system…comprising:”; therefore, these claims are directed to the statutory category of machines.
Step 2A Prong 1: These claims recite the same abstract ideas as in claims 1-7, respectively, as the judicial exception.
Step 2A Prong 2: The judicial exception recited in these claims are not integrated into a practical application. The only difference between claims 9-15 and claims 1-7 is that claims 9-15 are directed to “A system for providing a recommendation by a digital assistant using a persuasive action, comprising: a processing circuitry; and a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:” However, mere recitation that a judicial exception is to be performed using generic computer equipment in their ordinary capacity, i.e. a processing circuitry; and a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system, cannot meaningfully integrate the judicial exception into a practical application. See MPEP 2106.05(f). With that exception, the analysis at this step mirrors that of claims 1-7, respectively.
Step 2B: The additional elements from Step 2A Prong 2 of these claims do not contain significantly more than the judicial exception. The only difference between claims 9-15 and claims 1-7 is that claims 9-15 are directed to “A system for providing a recommendation by a digital assistant using a persuasive action, comprising: a processing circuitry; and a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:” However, mere recitation that a judicial exception is to be performed using generic computer equipment in their ordinary capacity, i.e. a processing circuitry; and a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system, cannot amount to significantly more than the judicial exception. See MPEP 2106.05(f). With that exception, the analysis at this step mirrors that of claims 1-7, respectively.
Claim Rejections - 35 U.S.C. 103
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.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Aggarwal et al. (US 2018/0107930 A1) (hereinafter Aggarwal) in view of VAN HALTEREN et al. (US 2014/0122104 A1) (hereinafter HALTEREN).
Regarding independent claim 1, Aggarwal teaches a method for providing a recommendation by a digital assistant, executed by an input/output (I/O) device, using a persuasive action ([0012], [0021] "techniques of this disclosure may enable a virtual, computational assistant ... to notify, without user prompting, information that may be of interest to the user"; a virtual, computational assistant (a digital assistant) executes at a computing device 110A (an I/O device) to notify without user prompting (for providing a recommendation by using a persuasive action)), comprising:
collecting, via one or more sensors connected to the I/O device, real-time data related to a user of the digital assistant and an environment surrounding the user ([0061] "sensor information obtained by sensors (e.g., position sensors, accelerometers, gyros, barometers, ambient light sensors, proximity sensors, microphones, and any other sensor) of computing device 210"; sensors (via one or more sensors) of computing device 210 (of the I/O device) supply sensor information (real-time data) characterizing the user and the physical and virtual environment of the device and the user (relative to a user of the digital assistant and an environment surrounding the user));
determining, in one of real-time and near real-time, a current state of the user based on the collected real-time data, wherein the current state of the user is a state of the user and a state of the environment surrounding the user ([0060] "define a context of computing device 210 that specifies the characteristics of the physical and/or virtual environment of computing device 210 and a user of computing device 210 at a particular time"; the context module defines a context (determining a current state of the user) of the device and the user at a particular time (in one of real-time and near real-time) that specifies the characteristics of the physical and virtual environment (based on the collected real-time data, wherein the current state of the user is a state of the user and a state of the environment surrounding the user));
determining a recommendation for the user of the digital assistant to perform a certain activity, wherein the recommendation is determined based on the current state of the user ([0044], [0060] "suggest an action (e.g., reschedule the flight to Topeka)"; based on the defined context, the assistant proactively, without prompting, suggests an action (a recommendation to perform a certain activity) for the user); and
presenting the determined recommendation by applying the persuasive action, wherein the recommendation is presented via at least one of a speaker and a display unit of the I/O device executing the digital assistant ([0042] "assistant module 122 may cause UID 112 to output an audible notification ... Additionally, or alternatively, assistant module 122 may cause UID 112 to output for display a visible notification"; the assistant outputs the notification (and presenting the determined recommendation) either as an audible notification via a speaker (a speaker) or as a visible notification for display (a display unit)).
Aggarwal does not expressly teach analyzing a historical dataset related to the user to compile a persuasive action, wherein the persuasive action is customized based on at least one convincing method and based on the analysis of the historical dataset and the current state of the user, and wherein the persuasive action is a convincing method having a highest probability to cause the user to accept the recommendation of the digital assistant.
However, HALTEREN teaches analyzing a historical dataset related to the user to compile a persuasive action, wherein the persuasive action is customized based on at least one convincing method and based on the analysis of the historical dataset and the current state of the user ([0026] “behavior change engine…gather data regarding a particular subject and support a human coach by proposing personalized messages based on the user profile”, [0043] "coaching messages ... are generated according to a personalized influence strategy ... The system 100 enables matching of behavioral data 122b with data corresponding to the Subjects responsiveness to specific persuasive messages to determine a susceptibility to one or more influence strategies"; the coaching engine analyzes the behavioral data of the user profile (analyzing a historical dataset related to the user) to generate a personalized message according to a personalized influence strategy (to compile a persuasive action, wherein the persuasive action is customized based on at least one convincing method) by matching behavioral data with the user's responsiveness (and based on the analysis of the historical dataset and the current state of the user)), and wherein the persuasive action is a convincing method having a highest probability to cause the user to accept the recommendation of the digital assistant (claim 9, [0043] "estimating ... a likelihood of success for at least one of a plurality of psychological influence strategies based at least in part on at least one response received from the Subject"; the system estimates a likelihood of success for each of a plurality of psychological influence strategies (wherein the persuasive action is a convincing method having a highest probability) and selects on that basis to ensure effective arguments (to cause the user to accept the recommendation of the digital assistant)).
Because Aggarwal and HALTEREN are analogous art and within the same field of endeavor, specifically computer-implemented systems that present recommendations or messages to a user in order to influence the user's behavior, and are further reasonably pertinent to the same problem solving area of causing a user to accept and act upon a recommendation presented by an automated assistant, accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the personalized influence-strategy selection of HALTEREN with the proactive sensor-driven recommendation assistant of Aggarwal, with a reasonable expectation of success, such that the assistant of Aggarwal composes the suggested action according to the influence strategy estimated to be most effective for the user, to teach analyzing a historical dataset related to the user to compile a persuasive action ... wherein the persuasive action is a convincing method having a highest probability to cause the user to accept the recommendation. This modification would have been motivated by the desire to increase the likelihood that the user accepts the suggested action by matching messages to the user's susceptibility serves to ensure usage of arguments that are effective for the specific subject (HALTEREN [0043]).
Regarding independent claim 8, it is a non-transitory computer readable medium claim that is substantially the same as the method of claim 1. Thus, claim 8 is rejected for the same reason as the method of claim 1. In addition, Aggarwal teaches a non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process for providing a recommendation by a digital assistant, executed by an input/output (I/O) device ([0005] "a computer-readable storage medium including instructions that when executed cause one or more processors of a system to determine content for a conversation with a user of a computing device"; a computer-readable storage medium (a non-transitory computer readable medium) stores instructions (instructions) that when executed cause one or more processors (a processing circuitry) of the assistant).
Regarding independent claim 9, it is a system claim that is substantially the same as the method of claim 1. Thus, claim 9 is rejected for the same reason as the method of claim 1. In addition, Aggarwal teaches a system for providing a recommendation by a digital assistant using a persuasive action, comprising: a processing circuitry; and a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system ([0004], [0055] "a system that includes one or more processors and a memory comprising instructions that when executed cause the one or more processors to determine content for a conversation with a user of a computing device"; one or more processors 240 (a processing circuitry) and storage components 248 storing a memory comprising instructions (a memory containing instructions) configure the computing device).
Regarding dependent claim 2, Aggarwal, in view of HALTEREN, teach the method of claim 1, monitoring a feedback of the user to the presented recommendation (see HALTEREN [0033] "adapt to the subjects reception of the messages delivered to the subject, or otherwise learn the Subjects responses, and/or reaction, to the personalized messages delivered"; the engine learns the subject's responses and reactions to the personalized messages (a feedback of the user)); determining an alternate recommendation when the user rejects the presented recommendation (see HALTEREN [0045], [0067] "alternatives may be computed, i.e. more active means of transportation ... other forms of transportation that require more physical activity may be presented to the subject"; upon detecting the behavior of the subject the system computes and presents an alternative (an alternate recommendation)); compiling an alternate persuasive action based on analysis of the historical dataset (see HALTEREN [0049], [0056] "reverts back to step 305 to search and select a new text fragment to replace the one that has already been used"; where a message was already used the engine searches and selects a new replacement text fragment from the fact database (an alternate persuasive action compiled from the historical dataset)); and presenting the determined alternate recommendation by applying the alternate persuasive action (see HALTEREN [0067], [0049] "other forms of transportation that require more physical activity may be presented to the subject and/or the coach in the notification in step 509"; the computed alternative is presented to the user in the notification using the newly selected replacement text fragment).
Regarding dependent claim 3, Aggarwal, in view of HALTEREN, teach the method of claim 1, applying a machine learning model trained to determine the current state based on the collected real-time data (see HALTEREN [0039] "A machine learning algorithm may be trained on a set of classifications provided by human coaches ... to classify the behavior of the Subject into an activity pattern"; a machine learning algorithm (a machine learning model) trained on a set of classifications uses activity-monitor data to classify the user's behavior into an activity pattern (the current state)).
Regarding dependent claim 4, Aggarwal, in view of HALTEREN, teach the method of claim 3, wherein the determining, in one of real-time and near real-time, a current state of the user is further based on historical data related to past activity of the user obtained from sources external to the I/O device (see HALTEREN claim 11, [0057] "receiving ... data, including a geographical location of a mobile device associated with the Subject and Subject activity corresponding to the geographical location, from the mobile device associated with the subject"; the system receives data including a geographical location and the user's activity from a mobile device associated with the user (sources external to the I/O device)).
Regarding dependent claim 5, Aggarwal, in view of HALTEREN, teach the method of claim 1, wherein the convincing method of the persuasive action is at least one of: authority-based persuasive, consensus-based persuasive, reward-based persuasive, reciprocity-based persuasive, commitment-based persuasive, or scarcity-based persuasive action (see HALTEREN claim 9, [0043] "the psychological influence strategies include authority, consensus, Scarcity, and commitment"; the psychological influence strategies enumerated include authority, consensus, scarcity, and commitment (the convincing method)).
Regarding dependent claim 6, Aggarwal, in view of HALTEREN, teach the method of claim 5, compiling the persuasive action to communicate at least one preconfigured message (see HALTEREN [0024], [0032] "a text fragment database 114 that may include a collection of standardized text fragments. Each of the text fragments may be a potential personalized message"; the personalized message is composed from a collection of standardized text fragments stored in the text fragment database (at least one preconfigured message)).
Regarding dependent claim 7, Aggarwal, in view of HALTEREN, teach the method of claim 5, computing a probability for each convincing method based in part on the current state of the user (see HALTEREN claim 9 "estimating ... a likelihood of success for at least one of a plurality of psychological influence strategies"; the system estimates a likelihood of success for each of a plurality of psychological influence strategies (a probability for each convincing method)); and using the convincing method with the highest probability to compile the persuasive action (see HALTEREN claim 10 "the selecting step is based at least in part on the estimates of the likelihood of Success and the certainty of the estimates"; the selecting step is based on the estimates of the likelihood of success).
Regarding dependent claim 10, the rejection of claim 2 is applied in the same manner to the corresponding system-form recitation of claim 10.
Regarding dependent claim 11, the rejection of claim 3 is applied in the same manner to the corresponding system-form recitation of claim 11.
Regarding dependent claim 12, the rejection of claim 4 is applied in the same manner to the corresponding system-form recitation of claim 12, the recitation of sources external to the system being the system-form counterpart of sources external to the I/O device.
Regarding dependent claim 13, the rejection of claim 5 is applied in the same manner to the corresponding system-form recitation of claim 13.
Regarding dependent claim 14, Aggarwal, in view of HALTEREN, teach the system of claim 9, compile the persuasive action to communicate at least one preconfigured message (see HALTEREN [0024], [0032] "a text fragment database 114 that may include a collection of standardized text fragments. Each of the text fragments may be a potential personalized message"; the personalized message is composed from a collection of standardized text fragments (at least one preconfigured message)). Claim 14 depends from base system claim 9 and accordingly does not incorporate the convincing-method enumeration of claim 13.
Regarding dependent claim 15, Aggarwal, in view of HALTEREN, teach the system of claim 9, compute a probability for each convincing method based in part on the current state of the user (see HALTEREN claim 9 "estimating ... a likelihood of success for at least one of a plurality of psychological influence strategies"; the system estimates a likelihood of success for each of a plurality of psychological influence strategies (a probability for each convincing method)); and use the convincing method with the highest probability to compile the persuasive action (see HALTEREN claim 10 "the selecting step is based at least in part on the estimates of the likelihood of Success and the certainty of the estimates"; the selecting step is based on the estimates of the likelihood of success). Claim 15 depends from base system claim 9 and accordingly does not incorporate the convincing-method enumeration of claim 13.
Response to Arguments
Applicant’s amendments to claims 5 and 13 and corresponding Remarks dated 3/10/2026, on page 7, regarding the claim objections are persuasive, consequently, the claim objections set forth in the Office Action dated 9/11/2025 are withdrawn.
Applicant’s amendments to claims 4 and 12 and corresponding Remarks dated 3/10/2026, on page 7, regarding corresponding 35 U.S.C. 112(a) rejections have overcome the 35 U.S.C. 112(a) rejections set forth in the Office Action dated 9/11/2025. However, upon reconsideration, the pending claims are rejected under 35 U.S.C. 112(a) because of issues as set forth in the 35 U.S.C. 112(a) rejections detailed above.
Applicant’s amendments to claims and corresponding Remarks dated 3/10/2026, on pages 7-8, regarding corresponding 35 U.S.C. 112(b) rejections have overcome the 35 U.S.C. 112(b) rejections set forth in the Office Action dated 9/11/2025. However, upon reconsideration, the pending claims are rejected under 35 U.S.C. 112(b) because of issues as set forth in the 35 U.S.C. 112(b) rejections detailed above.
Applicant’s arguments within Remarks dated 3/10/2026, on pages 8-15, traversing the 35 U.S.C. 101 rejections have been fully considered but are not persuasive.
The 35 U.S.C. 101 rejection of claims 1-15 is maintained as set forth above. Each argument is addressed in turn.
Regarding preemption and the abstract-idea groupings: Applicant argues that the claims "do not preempt or substantially preempt any abstract idea" and "do not... even fall within" the three groupings of abstract ideas, namely mathematical concepts, certain methods of organizing human activity, and mental processes.
Examiner respectfully disagrees.
First, the absence of complete preemption does not demonstrate that a claim is patent eligible. Questions of preemption are inherent in, and are resolved by, the two-part Alice/Mayo framework applied in the rejection above; where, as here, the claims are determined to recite a judicial exception that is not integrated into a practical application and that does not add significantly more, the preemption concern is fully addressed by that analysis. See MPEP 2106.04(a); Ariosa Diagnostics, Inc. v. Sequenom, Inc., 788 F.3d 1371, 1379 (Fed. Cir. 2015) ("the absence of complete preemption does not demonstrate patent eligibility"). Second, Applicant's assertion that the claims do not fall within any grouping is conclusory and is contradicted by the Step 2A Prong One analysis above: the "determining... a current state of the user," "determining a recommendation," and "analyzing a historical dataset... to compile a persuasive action" limitations recite mental processes, namely observations, evaluations, and judgments, within the grouping of MPEP 2106.04(a)(2)(III), and the "convincing method having a highest probability" limitation recites a mathematical concept within the grouping of MPEP 2106.04(a)(2)(I). A bare assertion to the contrary, unaccompanied by any analysis of the actual claim language, does not rebut the rejection.
Regarding the argument that the claims do not recite a mental process because of sensor collection and real-time analysis: Applicant argues that the claims do not recite a mental process because "collecting, via one or more sensors connected to the I/O device, real-time data" cannot be performed in the mind even with pencil and paper, and because the collected data cannot be "analyzed in real-time or near real-time by a person," relying on dictionary and encyclopedia definitions of "real-time" as connoting millisecond or microsecond speeds.
Examiner respectfully disagrees.
The argument is misplaced for the reasons given in the rejection above. The "collecting, via one or more sensors" limitation is not relied upon as part of the abstract idea; it is identified at Step 2A Prong Two as an additional element constituting insignificant extra-solution activity of mere data gathering. See MPEP 2106.05(g). Examiner does not contend, and the rejection does not require, that a human collect sensor data in the mind. That limitation is treated as an additional element precisely because it is not part of the mental process. The mental-process limitations are instead the "determining a current state of the user," "determining a recommendation," and "analyzing a historical dataset... to compile a persuasive action" steps, each of which is an observation, evaluation, or judgment of the type that falls within the mental-process grouping. See MPEP 2106.04(a)(2)(III). The recitation "in one of real-time and near real-time" does not remove the "determining a current state" step from the mental-process grouping. The speed at which an evaluation is said to be performed does not change whether the step is the type of observation, evaluation, or judgment that can practically be performed in the human mind. The August 4, 2025 USPTO memorandum, "Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. 101," cautions examiners only against placing within the mental-process grouping limitations that the human mind is not equipped to perform, expressly identifying such examples as complex neural-network operations and multidimensional matrix calculations; evaluating a user's current state from observed data is not such a limitation. Moreover, Applicant's reliance on a millisecond or microsecond definition of "real-time" is not commensurate with the claim or the specification. The claim recites no numerical latency bound, and, as set forth in the 35 U.S.C. 112(b) rejection above, "in one of real-time and near real-time" is interpreted under the broadest reasonable interpretation to encompass "determining the current state contemporaneously with, or shortly after, collection of the underlying sensor data," such that "any short, undefined processing delay is read to satisfy the limitation," grounded in specification [0035] and [0037]. Applicant cannot, on the one hand, urge in traversing the 35 U.S.C. 112(b) rejection that "near real-time" is a known and definite term, and, on the other hand, import an unclaimed millisecond bound in order to argue that the determining step exceeds human capability. The further "analyzing a historical dataset... to compile a persuasive action" step is not even qualified by "real-time" or "near real-time," and so is not subject to any speed-based argument at all. Finally, Examiner's prior observation regarding conventional vehicle drivers and aircraft pilots remains apt. A person observing instruments and evaluating a current state and an appropriate next action contemporaneously is performing exactly the type of real-time or near-real-time evaluation contemplated by the claims. Applicant's response that such persons act in "human time" rather than "real-time as understood in the art" again rests on an unclaimed speed limitation. Nothing in the claim precludes the determining steps from being read as mentally performable evaluations. The claims therefore recite an abstract idea under Step 2A Prong One.
Regarding the argument that "highest probability" does not recite a mathematical concept: Applicant argues that selecting a persuasive action "having a highest probability" does not recite a mathematical concept because the claim "does not recite a mathematical formula, equation, or calculation," and that probability is, at most, a selection criterion within a larger technical process, citing McRO and Diehr.
Examiner respectfully disagrees.
A claim limitation need not set forth a mathematical formula in symbolic form to recite a mathematical concept; the mathematical-concepts grouping includes mathematical relationships expressed in words. See MPEP 2106.04(a)(2)(I). The limitation "wherein the persuasive action is a convincing method having a highest probability to cause the user to accept the recommendation of the digital assistant" sets forth a mathematical relationship, namely the selection of a maximum from among computed probabilities, and dependent claims 7 and 15 confirm this by reciting "computing a probability for each convincing method... and using the convincing method with the highest probability." That the independent claim states the relationship in prose rather than in symbols does not remove it from the grouping.
In any event, even if the "highest probability" limitation were not treated as a mathematical concept, Step 2A Prong One would still be satisfied, because the limitation independently recites a mental process. Selecting the convincing method most likely to cause a particular user to accept a recommendation is an evaluation or judgment of the type a human performs in deciding how best to persuade another person, and it can be performed in the mind or with the aid of pen and paper. See MPEP 2106.04(a)(2)(III); specification [0050]-[0052]. The abstract-idea determination thus does not depend solely on the mathematical-concept characterization.
McRO and Diehr do not aid Applicant, and both are directed to the separate question, addressed at Step 2A Prong Two below, of whether a claim that involves a judicial exception is nonetheless directed to a patent-eligible application of it. In Diehr the mathematical equation was applied within a process that physically cured synthetic rubber, an existing technological process, and the claim was eligible because it improved that existing technological process, not because it was implemented on a computer. In McRO the claims recited specific rules of a particular type that improved computer animation. Here, by contrast, the claim recites no comparable technological process and no specific rule set; it recites the abstract evaluation and selection itself and then applies it on a generic input/output device. The "mere mention of a highest probability," as Applicant puts it, is therefore not the dispositive point. The point is that the claim is directed to the abstract evaluation and selection, with no additional element that integrates it into a practical application, as explained below.
Regarding the argument that the claims are directed to an improvement in the functioning of a computer: Applicant argues that the claims are directed to an improvement in the functioning of a computer rather than to an abstract idea, relying on specification paragraph [0016] ("reduced processing time and, thus, improved computational efficiency in the modification and execution of digital assistant routines") and specification paragraph [0019] ("the efficiency of the I/O device executing the digital assistant is being improved as unsuitable outputs are being avoided, which would... prompt a user to manually reconfigure the I/O device"), and citing Enfish, Thales, and RecogniCorp.
Examiner respectfully disagrees.
Under MPEP 2106.04(d)(1) and 2106.05(a), as informed by Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB Sept. 26, 2025) (precedential), an asserted technological improvement integrates a judicial exception into a practical application only where the claim itself reflects the disclosed improvement, that is, where the claim recites the components or steps that provide the improvement. Here it does not. The claim recites the abstract evaluations themselves, namely determining the current state, determining a recommendation, analyzing a historical dataset to compile a persuasive action, and selecting the highest-probability convincing method, together with generic data gathering via sensors, generic presentation via a speaker and a display, and a generic input/output device executing a digital assistant. The claim recites no data structure, no algorithm, no model architecture, no resource-management step, and no other limitation directed to how the computer is made to run faster or more efficiently. Any asserted reduction in processing time or improvement in computational efficiency therefore is not reflected in the claim.
Moreover, the asserted gain flows from the abstract idea itself. Specification paragraph [0019] attributes the improved "efficiency" to "generating and implementing persuasive actions" so that "unsuitable outputs are being avoided," that is, to making a better persuasion decision by selecting the convincing method most likely to be accepted. Avoiding "unsuitable outputs" by reaching a better persuasion decision is an improvement in the quality of the abstract decision-making, not an improvement in the functioning of the computer. As MPEP 2106.05(a) states, the judicial exception alone cannot provide the improvement. Even under Applicant's own framing, that an improvement to a computer changes "how the computer decides what to do, when to do it, and what resources to use, not just reaching a better conclusion," the claim recites no such system-level limitation; it recites only the reaching of a better conclusion, namely the highest-probability persuasive action, which Applicant concedes is insufficient.
Applicant's "exists only because of the computer" arguments, namely reduced device reconfiguration, conservation of limited input-output bandwidth, and avoidance of wasted processing and interaction cycles, are not commensurate with the claim. The claim contains no limitation directed to device reconfiguration, to input-output bandwidth, or to the management of processing or interaction cycles. These are arguments addressed to the specification, not recited claim features, and features not claimed cannot confer eligibility. See MPEP 2145; In re Self, 671 F.2d 1344 (CCPA 1982).
The cited cases are distinguishable for the same reason, namely that in each the claim recited the specific technological mechanism credited with the improvement. See Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016) (self-referential table data structure); Thales Visionix Inc. v. United States, 850 F.3d 1343 (Fed. Cir. 2017) (a particular configuration of inertial sensors and a particular method of using the raw sensor data to track an object on a moving platform). The present claim recites no analogous mechanism. RecogniCorp does not assist Applicant; there the Federal Circuit held the claims ineligible, and Applicant cites the case only for the general proposition that not all software claims are abstract, which does not establish eligibility of these claims. Consistent with Ex Parte Desjardins, where the claim recites the desired result or outcome rather than the particular way of achieving it, the claim does not reflect a technological improvement. Furthermore, the maintained 35 U.S.C. 112(a) rejection above establishes that the specification does not disclose the algorithm by which the analysis and the highest-probability selection are performed. Under MPEP 2106.05(a), where the specification sets forth an improvement only in a conclusory manner, that is, a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art, the examiner should not determine that the claim improves technology or a technical field. The judicial exception is therefore not integrated into a practical application.
Regarding the argument that the claims amount to significantly more: Applicant argues that the claims amount to a technical solution that is significantly more than an abstract idea, and that "the technological environment is the entire reason for the invention."
Examiner respectfully disagrees.
As set forth at Step 2B above, the additional elements, namely collecting real-time data via sensors and presenting the recommendation via a speaker and a display, which are insignificant extra-solution data gathering and output under MPEP 2106.05(d) and (g); the generic input/output device, processing circuitry, and memory, which invoke generic computer components as a tool under MPEP 2106.05(f); and the machine learning model applied to determine the current state in claims 3 and 11, which generally links the exception to a technological environment under MPEP 2106.05(h), do not, individually or in combination, amount to significantly more than the abstract idea. Applicant's contention that "the technological environment is the entire reason for the invention" confirms, rather than rebuts, the analysis, because generally linking the use of a judicial exception to a particular technological environment or field of use is expressly identified in MPEP 2106.05(h) as not providing an inventive concept. Reciting the abstract idea and applying it with generic computer components does not supply significantly more. See MPEP 2106.05; Alice Corp. v. CLS Bank Int'l, 573 U.S. 208 (2014).
Accordingly, Applicant's arguments are not persuasive, and the rejection of claims 1-15 under 35 U.S.C. 101 is maintained.
Applicant’s arguments within Remarks dated 3/10/2026, on pages 15-22, traversing the 35 U.S.C. 103 rejections over Penubothula in view of SARIKAUA have been fully considered but are moot in view of a new grounds of rejection under 35 U.S.C. 103 over Aggarwal in view of HALTEREN.
Conclusion
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/KC CHEN/Primary Patent Examiner, Art Unit 2143
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