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 .
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.
Claim 1:
Step 2A, Prong 1 analysis:
The claim(s) recite(s) in part:
• “analyzing, by one or more processors, a conversation of a user in real-time utilizing at least one of natural language processing (NLP) and machine learning, wherein the analyzing identifies one or more personality traits of the user;”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses viewing the conversation of a user and determining the personality traits of a user. This would be seen as a mental process because a person having ordinary skill of the art would be able to view the user’s input (conversation) and determine the user’s personality traits, the claim recites performing the analyzing, determining and configuring steps by one or more processors.
• “determining, by the one or more processors, an appropriate communication style for an RPA chatbot to use when persuading the user to accept an Artificial Intelligence (AI) driven decision by leveraging the identified one or more personality traits; and”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses viewing the personality traits of a user and choosing the correct tone to communicate with the user. This would be seen as a mental process because a person having ordinary skill of the art would be able to view the user’s input and determine which communication style would best persuade the user.
• “configuring, by the one or more processors, the RPA chatbot to use the determined appropriate communication style for the user. ”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses configuring the chatbot to use the appropriate communication style. This would be seen as a mental process because a person having ordinary skill of the art would be able to configure the chatbot according to the user’s input.
Step 2A, Prong 2 analysis:
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of:
• “by the one or more processors” This limitation is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicia I exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
• “utilizing at least one of natural language processing (NLP) and machine learning” which is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(g).
• “RPA chatbot” which is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(g).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
• “by the one or more processors” This limitation is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicia I exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
• “utilizing at least one of natural language processing (NLP) and machine learning” This limitation is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicia I exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
• “RPA chatbot” This limitation is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicia I exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Claim 2:
Step 2A, Prong 1 analysis:
The claim(s) recite(s) in part:
• “utilizing, by the one or more processors, the decision-making history to analyze the conversation and a plurality of subsequent conversations inclusive of at least one of a behavior and a choice of the user over time, wherein a customized persuasive strategy of the RPA chatbot is generated for the user and additional users.”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses viewing the personality traits of a user and selecting at least one behavior and choice of the user, and in part generating a strategy to persuade the user based on their selections. This would be seen as a mental process because a person having ordinary skill of the art would be able to view the user’s input and generate a strategy to best persuade the user.
Step 2A, Prong 2 analysis:
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of:
• “by the one or more processors” This limitation is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicia I exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
• The additional elements of “storing, by the one or more processors, a decision-making history of the user in a database;” which is recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
• The additional elements of “retrieving, by the one or more processors, the decision-making history from the database; and” which is recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
• “by the one or more processors” This limitation is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicia I exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
• The additional elements of “storing, by the one or more processors, a decision-making history of the user in a database;” which is recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
• The additional elements of “retrieving, by the one or more processors, the decision-making history from the database; and” which is recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Claim 3:
Step 2A, Prong 2 analysis:
“creating an AI model to accurately predict the at least one of the behaviors and the choice of the user.” is/are recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
“creating an AI model to accurately predict the at least one of the behaviors and the choice of the user.” is/are recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Claim 4:
Step 2A, Prong 2 analysis:
“wherein creating the AI model further includes using one or more classifications, clustering, decision trees, and reinforcement learning techniques to predict the at least one of the behaviors and the choice of the user.” is/are recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
“wherein creating the AI model further includes using one or more classifications, clustering, decision trees, and reinforcement learning techniques to predict the at least one of the behaviors and the choice of the user.” is/are recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Claim 5:
Step 2A, Prong 2 analysis:
“using the AI model to develop at least one parameter to be used by the RPA chatbot“ is/are recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
“using the AI model to develop at least one parameter to be used by the RPA chatbot“ is/are recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Claim 6:
Step 2A, Prong 1 analysis:
The claim(s) recite(s) in part:
• “further comprising configuring the RPA chatbot with the at least one parameter, including at least one of a user language and a sentiment preference of the user.” As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses configuring a chatbot using a generated parameter. This would be seen as a mental process because a person having ordinary skill of the art would be able to configure the chatbot using the previously generated parameter.
Step 2A, Prong 2 analysis:
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
There are no additional elements that individually or in combination integrate the judicial element into practical application.
Step 2B analysis:
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
There are no additional elements that individually or in combination amount to significantly more than the judicial exception
Claim 7:
Step 2A, Prong 2 analysis:
The additional elements of “continuing to monitor user interactions and responses, using data gleaned from the interactions and responses to refine the determined appropriate communication style to maximize a likelihood of the user accepting the AI driven decision.” which is recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
The additional elements of “continuing to monitor user interactions and responses, using data gleaned from the interactions and responses to refine the determined appropriate communication style to maximize a likelihood of the user accepting the AI driven decision.” which is recited at a high level of generality and amounts to extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Claim 8:
Step 2A, Prong 1 analysis:
Claim 8 recites the same abstract ideas as claim 1, therefore it is rejected under the same basis.
Step 2A, Prong 2 analysis:
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of:
• “A system” which is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(g).
• “one or more memory storing executable instructions” which is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(g).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
• “A system” This limitation is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicia I exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
• “one or more memory storing executable instructions” This limitation is recited at a high level of generality and amount to adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). As explained by the Supreme Court; in order to make a claim directed to a judicia I exception patent-eligible, the additional element or combination of elements must do '"more than simply state the judicial exception] while adding the words 'apply it"'. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, limitations that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not amount to significantly more than the exception itself and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Claim 17:
Step 2A, Prong 1 analysis:
The claim(s) recite(s) in part:
• “create an AI model to accurately predict the at least one of the behaviors and the choice of the user, and.” As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses creating an Ai model to predict a user’s behavior and choices. This would be seen as a mental process because a person having ordinary skill of the art would be able to create Ai model that will be able to predict a user’s choices and behaviors.
• “pursuant to creating the AI model, use one or more classifications, clustering, decision trees, and reinforcement learning techniques to predict the at least one of the behavior and the choice of the user.”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses using different methods to predict a user’s decisions and behavior. This would be seen as a mental process because a person having ordinary skill of the art would be able to implement the different methods mentioned and use them to create an Ai model that predicts a user’s decisions and behaviors.
Claims 9 and 16:
Claims 9 and 16 recites the same abstract ideas as claim 2, therefore they are rejected under the same basis.
Claim 10:
Claims 10 recites the same abstract ideas as claim 3, therefore it is rejected under the same basis.
Claims 11:
Claims 11 recites the same abstract ideas as claim 4, therefore it is rejected under the same basis.
Claims 12 and 18:
Claims 12 and 18 recites the same abstract ideas as claim 5, therefore they are rejected under the same basis.
Claim 13:
Claim 13 recites the same abstract ideas as claim 6, therefore it is rejected under the same basis.
Claims 14 and 20:
Claims 14 and 20 recites the same abstract ideas as claim 7, therefore they are rejected under the same basis.
Claim 15:
Claim 15 recites the same abstract ideas as claim 1, therefore it is rejected under the same basis.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-3,7-10, 14-16, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Galitsky et, al. (US20210064827A1 referred to as Galitsky hereinafter)
Regarding claim 1:
Galitsky teaches:
A computer-implemented method for optimizing Robotic Process Automation (RPA), comprising: (Galitsky)[0003]” computer-enabled analysis of language discourse facilitates numerous applications such as automated agents that can answer questions from users. The use of “chatbots” and agents to answer questions, facilitate discussion, manage dialogues, and provide social promotion is increasingly popular.” Galitsky teaches a computer-implemented chatbot that automates user-facing question-answering and dialogue management, routine task-automation function that teaches robotic process automation.
analyzing, by one or more processors, a conversation of a user in real-time utilizing at least one of natural language processing (NLP) and machine learning, wherein the analyzing identifies one or more personality traits of the user; (Galitsky)[0048]” At block 603, a personality trait of the user may be determined based at least in part on the query… As another example, the discourse tree generated from the query may be provided as input to a personality trait model (e.g., an example of the classification model 202 of FIG. 2). The personality trait model may be previously trained to identify one or more personality traits of a user based on a discourse tree provided as input and corresponding to a query.” Galitsky teaches taking each incoming user utterance, parsing it into a discourse tree, feeding the tree to a trained machine learning classifier and outputting one or more personality traits performed at the moment of each utterance.
determining, by the one or more processors, an appropriate communication style for an RPA chatbot to use when persuading the user to accept an Artificial Intelligence (AI) driven decision by leveraging the identified one or more personality traits; and (Galitsky)[0015] An experienced agent should be able to manage the proper sentiment tonality and language in conversation, empathizing and otherwise pacing and leading the user to create and maintain a state of confidence that the user's problem will be resolved or that their question will be answered… The disclosed autonomous agents can manage the dialog provided to a user by ascertaining one or more personality traits of the user… such that an agent can match and/or complement the emotion and/or personality of the user with the dialog it provides. Galitsky teaches an agent that selects sentiment tonality and language calibrated to the user’s identified personality i.e. communication style for the express purpose of maintaining ‘a state of confidence that the user's problem will be resolved or that their question will be answered’ as taught by Galitsky.
configuring, by the one or more processors, the RPA chatbot to use the determined appropriate communication style for the user. (Galitsky)[0053]” At block 608, output dialog may be presented to the user device based at least in part on the candidate answer selected. In some embodiments, the output dialog may provide a response to the query that complements the emotion with which the query was expressed and the personality trait of the user.” Galitsky teaches block 608 that emits chatbot output that is conditioned on the user’s personality traits.
Regarding claims 2, 9, 16:
Galitsky teaches:
storing, by the one or more processors, a decision-making history of the user in a database; (Galitsky)[0048]” It should be appreciated that a user's personality traits may be identified, not just with a current query, but based on past communications” Galitsky teaches storing a user’s past communications, being a user’s past decision making history, as taught by the claim.
retrieving, by the one or more processors, the decision-making history from the database; and (Galitsky)[0048]“the personality traits determined for past communications may be stored and used to determine personality traits for the user with respect to subsequent queries.” Galitsky teaches pulling stored personality trait data from past communications back out to inform handling of new queries.
utilizing, by the one or more processors, the decision-making history to analyze the conversation and a plurality of subsequent conversations inclusive of at least one of a behavior and a choice of the user over time, wherein a customized persuasive strategy of the RPA chatbot is generated for the user and additional users. (Galitsky)[0048]” It should be appreciated that a user's personality traits may be identified, not just with a current query, but based on past communications (e.g., return requests, complaints, other service requests, other queries, etc.) as well. Thus, in some embodiments, the personality traits determined for past communications may be stored and used to determine personality traits for the user with respect to subsequent queries.” Galitsky teaches utilizing stored history to determine personality traits “with respect to subsequent queries” i.e. across multiple later conversations. The personality determination then feeds the complementary trait selection scheme which is a per-user customized persuasive strategy, as taught by Galitsky. Users get their own version of the same process, thus teaching the limitation “for the user and additional users.”
Regarding claim 9
Claim 9 recites similar limitations to claim 2, therefore it is rejected under the same basis.
Claim 16:
Claim 16 recites the same limitations as claim 2, therefore it is rejected under the same basis.
Regarding claims 3, 10:
Claim 3:
Galitsky teaches:
further comprising creating an AI model to accurately predict the at least one of the behaviors and the choice of the user. (Galitsky)[0026]”the classification model 202 may be generated based at least in part on executing a machine-learning algorithm on the training data set 206…By executing the supervised learning algorithm on the training data set 206, the classification model 202 may be trained to identify one or more answers (e.g., outputs 1-N) from a query provided as subsequent input.” Galitsky teaches running a supervised machine learning algorithm on a training set of historical query/answer pairs to generate classification model. The trained model takes a new query as input and predicts which answer the user will accept, a prediction of the user’s choice.
Regarding claim 10:
Claim 10 recites similar functionality to claim 3, therefore it is rejected under the same basis.
Regarding claims 7, 14, 20:
Claim 7:
Galitsky teaches;
further comprising continuing to monitor user interactions and responses, (Galitsky)[0028]” It should be appreciated that, as the classification model 202 is used, subsequent examples provided as input and the corresponding output produced by the classification model 202 may be added to the training data set 206, which can improve the accuracy of the classification model 202 over time. In some embodiments, the accuracy of the example and the corresponding output of the model may be confirmed by a user before it is added to the training data set 206.” Galitsky teaches a classification model captures “subsequent examples provided as input and the corresponding output” each time is runs. It continuously monitors what the user does and what the chatbot answered in response.
using data gleaned from the interactions and responses to refine the determined appropriate communication style to maximize a likelihood of the user accepting the AI driven decision. (Galitsky)[0028]” It should be appreciated that, as the classification model 202 is used, subsequent examples provided as input and the corresponding output produced by the classification model 202 may be added to the training data set 206, which can improve the accuracy of the classification model 202 over time. In some embodiments, the accuracy of the example and the corresponding output of the model may be confirmed by a user before it is added to the training data set 206.” Galitsky adds the input/output pairs to the training set and retrains the model, which “improves the accuracy of the classification model 202 over time.” Because that model drives the communication style selection, improving it refines the determined communication style. Galitsky also teaches [0015]” pacing and leading the user to create and maintain a state of confidence that the user's problem will be resolved or that their question will be answered.” Which would be obvious to a person having ordinary skill of the art to be seen as maximizing the acceptance.
Claims 14 and 20:
Claims 14 and 20 recite the same functionality as claim 7, therefore they are rejected under the same basis.
Regarding claim 8:
Galitsky teaches:
system for optimizing Robotic Process Automation (RPA) in a computing environment, comprising: one or more processors; and one or more memory storing executable instructions, wherein the executable instructions, when executed, cause the one or more processors to (Galitsky)[0102]” Computer system 900 may comprise a storage subsystem 918 that comprises software elements, shown as being currently located within a system memory 910. System memory 910 may store program instructions that are loadable and executable on processing unit 904,” Galitsky teaches a processing unit and system memory that stores executable program instructions. Galitsky teaches the recited processor and memory hardware that are used to execute the same process.
The remaining limitations of claim 8 recite similar to claim 1, therefore they are rejected under the same basis.
Regarding claim 15:
The remaining limitations of claim 15 recite similar to claim 1, therefore they are rejected under the same basis.
Claim Rejections - 35 USC § 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 4-6, 11-13, and 17-19 are rejected over Galitsky as set forth above, and in view of Gustafson et, Al. (US9847084B2, referred to as Gustafson hereinafter.)
Regarding claims 4,11:
Claim 4:
Galitsky teaches:
wherein creating the AI model further includes using one or more classifications, clustering,
(Galitsky)[0026]” At 212, the classification model 202 may be generated based at least in part on executing a machine-learning algorithm on the training data set 206. Any suitable portion of the training data set 206… the classification model 202 may be trained to identify one or more answers (e.g., outputs 1-N) from a query provided as subsequent input.” Galitsky teaches a classification model that is generated via a supervised classification machine learning algorithm, directly teaching the classification taught by the claim. Although not explicitly taught, it would be obvious to a person having ordinary skill of the art to add clustering, a well-known/ textbook machine learning category. As previously mentioned, Galitsky teaches a user personality-classification pipeline that groups users with similar personality profiles to share persuasion strategies, it would be obvious to a person having ordinary skill of the art that this is the same functionality of clustering.
decision trees, (Galitsky)[0035]” FIG. 3 depicts a binary decision tree 300 for identifying a personality trait, in accordance with at least one embodiment. As depicted in FIG. 3, binary decision tree 300 may be utilized to identify whether a query or response is indicative of a speaker that is an extrovert or an introvert.” Galitsky teaches a binary decision tree that walks attributes of the user’s inputs to classify the user’s personality, directly teaching a functional decision tree as taught by the claim.
However, Galitsky fails to teach:
and reinforcement learning techniques to predict the at least one of the behaviors and the choice of the user.
However, Gustafson teaches:
and reinforcement learning techniques to predict the at least one of the behaviors and the choice of the user. (Gustafson)[col. 12, lines 29-37]” the interaction module 122 evaluates the user 102 responses to the proposed outputs and uses that feedback to refine future outputs. For example, the interaction module 122 can determine if the user 102 takes a suggested action. A suggested action can include calling the suggested number, clicking on the suggested webpage, emailing the suggested contact, etc. In another embodiment, the interaction module 122 determines if the output results in a decrease in the user's 102 distress or an increase in the user's 102 engagement. In various embodiments, the scoring module 144 weights that selected personality response for future interactions.” Gustafson teaches a trial and error learning reinforcement process that evaluates the users output to refine future responses.
It would be obvious to a person having ordinary skill of the art before the effective filing date of the claimed invention, to combine the use of different data-driven techniques as taught by Galitsky, with reinforcement learning techniques as taught by Gustafson. A person having ordinary skill of the art would be motivated to do so to determine a distress level or engagement level of the user. (Galitsky)[Abstract]
Regarding claim 11:
Claim 11 recites similar to claim 4, therefore it is rejected under the same basis.
Regarding claim 5, 12, 18:
Claim 5:
Galitsky fails to teach:
further comprising using the AI model to develop at least one parameter to be used by the RPA chatbot.
However, Gustafson teaches:
further comprising using the AI model to develop at least one parameter to be used by the RPA chatbot.
(Gustafson)[col. 1, lines 57-65]”instructions that, when executed, retrieve or determine a personality type of the user from three or more personality types… instructions that, when executed, determine a set of outputs based on the user communication; instruction that, when executed, rank outputs based on the user's personality;” Gustafson teaches taking the model’s personality-type output and turning it into an output-ranking parameter that the chatbot then uses to select its response.
It would be obvious to a person having ordinary skill of the art to combine the use of different data-driven techniques as taught by Galitsky, with generating a parameter using an Ai model to be used by a chatbot as taught by Gustafson. A person having ordinary skill of the art would be motivated to do so to determine a distress level or engagement level of the user. (Gustafson)[Abstract]
Claims 12 and 18:
Claim 5 recites similar limitations to claims 12 and 18, therefore they are rejected under the same basis.
Regarding claims 6, 13, 19:
Claim 6:
Galitsky fails to teach:
further comprising configuring the RPA chatbot with the at least one parameter, including at least one of a user language
and a sentiment preference of the user.
However, Gustafson teaches:
further comprising configuring the RPA chatbot with the at least one parameter, including at least one of a user language (Gustafson)[col. 9, lines 30-45]” In various embodiments, the scoring module 144 determines or extracts communication attributes from the input… Such communication attributes include one or more of tone, tempo, pattern of speech, syntax, and grammar,… the communication style of the output received by the user 102 is adapted to be similar to the communication style of the user 102.” Gustafson teaches extracting the user’s tone, tempo, pattern of speech, syntax, and grammar, all language-style attributes, and adapts the chatbot’s output to be similar to the user’s language style. Those extracted attributes being the user-language parameters.
and a sentiment preference of the user. (Gustafson)[col. 8, lines 40-44]” In one embodiment, the linguistic algorithm(s) leverage statistical and linguistic approaches and aim to take into account the many dimensions of the user 102, including, but not limited to engagement, distress, mental state, and personality type.” Gustafson independently extracts the user’s engagement, distress, and mental state attributes, i.e. sentiment dimensions, and uses them to drive output selection.
It would be obvious to a person having ordinary skill of the art to combine the use of different data-driven techniques as taught by Galitsky, with configuring a chatbot using a user’s language and sentiment as taught by Gustafson. A person having ordinary skill of the art would be motivated to do so to determine a distress level or engagement level of the user. (Gustafson)[Abstract]
Claim 13:
Claim 13 recites similar limitations to claim 6, therefore it is rejected under the same basis.
Regarding claim 17:
Galitsky teaches:
create an AI model to accurately predict the at least one of the behaviors and the choice of the user. (Galitsky)[0026]”the classification model 202 may be generated based at least in part on executing a machine-learning algorithm on the training data set 206…By executing the supervised learning algorithm on the training data set 206, the classification model 202 may be trained to identify one or more answers (e.g., outputs 1-N) from a query provided as subsequent input.” Galitsky teaches running a supervised machine learning algorithm on a training set of historical query/answer pairs to generate classification model. The trained model takes a new query as input and predicts which answer the user will accept, a prediction of the user’s choice.
Galitsky teaches:
wherein creating the AI model further includes using one or more classifications, clustering,
(Galitsky)[0026]” At 212, the classification model 202 may be generated based at least in part on executing a machine-learning algorithm on the training data set 206. Any suitable portion of the training data set 206… the classification model 202 may be trained to identify one or more answers (e.g., outputs 1-N) from a query provided as subsequent input.” Galitsky teaches a classification model that is generated via a supervised classification machine learning algorithm, directly teaching the classification taught by the claim. Although not explicitly taught, it would be obvious to a person having ordinary skill of the art to add clustering, a well-known/ textbook machine learning category. As previously mentioned, Galitsky teaches a user personality-classification pipeline that groups users with similar personality profiles to share persuasion strategies, it would be obvious to a person having ordinary skill of the art that this is the same functionality of clustering.
decision trees, (Galitsky)[0035]” FIG. 3 depicts a binary decision tree 300 for identifying a personality trait, in accordance with at least one embodiment. As depicted in FIG. 3, binary decision tree 300 may be utilized to identify whether a query or response is indicative of a speaker that is an extrovert or an introvert.” Galitsky teaches a binary decision tree that walks attributes of the user’s inputs to classify the user’s personality, directly teaching a functional decision tree as taught by the claim.
However, Galitsky fails to teach:
and reinforcement learning techniques to predict the at least one of the behaviors and the choice of the user.
However, Gustafson teaches:
and reinforcement learning techniques to predict the at least one of the behaviors and the choice of the user. (Gustafson)[col. 11, lines 15-25]” the personality type of the user 102 is updated over time. The scoring module 144 analyzes and evaluates the most recent inputs from the user 102 to determine the personality type of the user 102. The updating allows the personality exhibited by the client device 120 to adapt to the user's 102 personality type, based on what the client device 120 learns about the user 102 and the interactions between the client device 120 and the user 102.” Gustafson teaches updating its personality determination over time based on what it learns from user interactions, the operational structure of reinforcement learning, thus teaching the limitation of the claim.
It would be obvious to a person having ordinary skill of the art to combine the creating of an Ai model and use of different data-driven techniques as taught by Galitsky, with reinforcement learning techniques as taught by Gustafson. A person having ordinary skill of the art would be motivated to do so to determine a distress level or engagement level of the user. (Gustafson)[Abstract]
Claim 19:
Claim 19 recites similar limitations to claim 6, therefore it is rejected under the same basis.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AYAAN AYAZ SHEIKH whose telephone number is (571)272-4643. The examiner can normally be reached MON-FRI 7:30-5pm.
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/AYAAN AYAZ SHEIKH/Examiner, Art Unit 2128
/OMAR F FERNANDEZ RIVAS/Supervisory Patent Examiner, Art Unit 2128
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