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 . Claims 1-21 are pending.
Claim Rejections - 35 USC § 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.
Claim 8-14 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.
Claim 8 recites the limitation "delivering said response via said user interface to said end user" in the third paragraph of the claim. There is insufficient antecedent basis for this limitation in the claim.
The rest of the claims are rejected by virtue of their dependency.
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 1-21 are rejected under 35 USC § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 (The Statutory Categories): Is the claim to a process, machine, manufacture or composition of matter? MPEP 2106.03.
Per Step 1, claim 1 is directed to a system (i.e., a machine), claim 8 is directed to a method (i.e., a process), and claim 15 is directed to a non-transitory computer readable medium (i.e., a machine or manufacture) Thus, the claims are directed to statutory categories of invention. However, the claims are rejected under 35 USC § 101 because they are directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application.
The analysis proceeds to Step 2A Prong One.
Step 2A Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon? MPEP 2106.04.
The abstract idea from claim 1 is:
an artificial intelligence agent, configured to communicate with end user;
storing end user specific information; and
when receiving a prompt, generating a response based on said stored end user specific information.
The abstract idea from claims 8 and 15 is (claim 8 being representative):
collecting end user specific information;
said user information;
receiving a prompt from said end user to terminate subscription of a service; generating response to said prompt,
wherein said response is at least partially correlated to said end user specific information; and
delivering said response to said end user.
The recited abstract idea steps italicized above cover managing relationships between a business and its customers, which constitutes a process that, under its broadest reasonable interpretation (BRI), covers commercial activity. This is further supported by paragraphs [0008] – [0010] of applicant’s specification as filed. If a claim limitation, under its BRI, covers commercial interactions, including contracts, legal obligations, advertising, marketing, sales activities or behaviors, and/or business relations, then it falls within the Certain Methods of Organizing Human Activity – Commercial or Legal Interactions grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A, Prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application? MPEP §2106.04.
This judicial exception is not integrated into a practical application because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP §2106.05(f).
Claim 1 recites the following additional elements: A system; a user interface, configured to interact with end user and communicate with an artificial intelligence agent; via said user interface and to be connected with at least one database.
Claim 8 recites the following additional elements: artificial intelligence agent; training said artificial intelligence agent; user interface.
Claim 15 recites the following additional elements: A non-transitory computer readable medium including a set of instructions that are executable by one or more processors of a computer; by an artificial intelligence agent via a user interface; training said artificial intelligence agent with.
These elements are merely instructions to apply the abstract idea to a computer, per MPEP §2106.05(f). Applicant has only described generic computing elements in their specification, as seen in paragraphs [0043] – [0048] of applicant’s specification as filed, for example. Further, the combination of these elements is nothing more than a generic computing system.
Accordingly, these additional elements, alone and in combination, do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea.
Step 2B (The Inventive Concept): Does the claim recite additional elements that amount to significantly more than the judicial exception? MPEP §2106.05.
Step 2B involves evaluating the additional elements to determine whether they amount to significantly more than the judicial exception itself.
The examination process involves carrying over identification of the additional element(s) in the claim from Step 2A Prong Two and carrying over conclusions from Step 2A Prong Two on the considerations discussed in MPEP §2106.05(f).
The additional elements and their analysis are therefore carried over: applicant has merely recited elements that facilitates the tasks of the abstract idea, as described in MPEP §2106.05(f).
Further, the combination of these elements is nothing more than a generic computing system. When the claim elements above are considered, alone and in combination, they do not amount to significantly more.
Therefore, per Step 2B, the additional elements, alone and in combination, are not significantly more. The claims are not patent eligible.
Further, the analysis takes into consideration all dependent claims as well:
Claims 2-5 further narrow the abstract idea with additional steps and/or description, in addition to including additional element: second database. Examiner notes that this is an example of “apply it” and is simply being used to facilitate the tasks of the abstract idea. This further narrowing of the abstract idea, along with the elements alone and in combination, is not enough to demonstrate integration into practical and is not significantly more. See MPEP §2106.05(f).
Regarding claims 6-7, 13-14, and 20-21, applicant further narrows the abstract idea with additional step(s). There are no further additional elements to consider, beyond those highlighted above. This further narrowing of the abstract idea, similar to above, is also not patent eligible.
Claims 9-12, and 16-19 further narrow the abstract idea with additional steps and/or description, in addition to including additional element: training said artificial intelligence agent. Examiner notes that this is an example of “apply it” and is simply being used to facilitate the tasks of the abstract idea. This further narrowing of the abstract idea, along with the elements alone and in combination, is not enough to demonstrate integration into practical and is not significantly more. See MPEP §2106.05(f).
Accordingly, claims 1-21 are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, and 5-7 are rejected under 35 U.S.C. § 102(a)1 and (a)(2) as being anticipated by Sivasubramanian (US 20210158805).
Claim 1
Sivasubramanian discloses:
A system of customer retention, comprising: {“Techniques described herein may be utilized to implement systems and methods to analyze contacts data. Contacts data may refer to various types of communications that occur within the context of a contact center. A contact center may refer to a physical or logical unit of an organization that manages customer interactions.” [0031]}
a user interface, configured to interact with end user and communicate with an artificial intelligence agent; {The system includes agent and supervisor interfaces that interact with users and receive AI assistance during customer interactions. [0036]}
an artificial intelligence agent, configured to communicate with end user via said user interface and to be connected with at least one database, {The contacts analytics service operates as an AI service that communicates responses to users and accesses stored contact data and other content repositories. [0036], [0062]}
wherein said database storing end user specific information; and {The system stores customer contact data, transcripts, an interaction metadata. [0031], [0062].}
said artificial intelligence agent, further configured to, when receiving a prompt from said user interface, generating a response based on said stored end user specific information. {During customer interactions, the AI service processes live interaction context and stored customer data to generate responses or assistance, where the live interaction functions as the prompt. [0035] – [0036], [0193]}
Claim 2
Sivasubramanian further discloses:
a second database, configured to store policy information including cancellation policy and promotion policy information. {The system includes a policy repository (e.g., cancellation and/or promotion related) that may be a database queried to obtain policies applicable to a request [0093], [0153]. Further, policies are stored in a database service as structured documents. [0206], [0207]}
Claim 3
Sivasubramanian further discloses:
a second database, configured to store workflow information. {Structured information that defines actions, triggers, and operational flows is stored for handling interactions in persistent storage and repositories. [0036], 0153], [0227]}
Claim 5
Sivasubramanian further discloses:
a second database, configured to store service specific information. {The system allows for searching and storing organization specific content to answer customer interactions and integrating with additional systems to obtain information related to customer interactions (i.e., service specific information). [0054], [0087]}
Claim 6
Sivasubramanian further discloses:
wherein said user specific information comprises user's subscription information. {The system obtains and uses customer specific information (e.g., subscription information) from integrated internal and third party systems during customer interactions. [0031], [0054], [0164]}
Claim 7
Sivasubramanian further discloses:
wherein said user specific information comprises user's prior usage of a subscribed service. {The system obtains and uses customer specific information (e.g., subscription usage information) from integrated internal and third party systems during customer interactions. [0031], [0054], [0164]}
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 4 is rejected under 35 U.S.C. § 103 as being unpatentable over Sivasubramanian (US 20210158805) in view of Coman (US 20210125612).
Claim 4
While Sivasubramanian teaches the limitations set forth above, it does not explicitly disclose:
a second database, configured to store application programming interface information.
However, Coman, in a similar field of endeavor directed to autonomously determining and responding to a perceived discrepancy during an automated customer service interaction, teaches:
a second database, configured to store application programming interface information. {“The API server 122 may include one or more processors 162 and one or more API databases 164, which may be any suitable repository of API data.” [0043]}
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the contacts data management features of Sivasubramanian to include the automated problem resolution features of Coman, to improve customer relations and expectations when solving discrepancies. (See paragraph [0104] of Coman).
Claims 8-21 are rejected under 35 U.S.C. § 103 as being unpatentable over Sivasubramanian (US 20210158805) in view of Yuan (US 20200005117).
Claims 8 and 15
Sivasubramanian discloses (claim 8 being representative):
(claim 8) A method for retaining end user of a service, comprising: {“Techniques described herein may be utilized to implement systems and methods to analyze contacts data. Contacts data may refer to various types of communications that occur within the context of a contact center. A contact center may refer to a physical or logical unit of an organization that manages customer interactions.” [0031]}
(claim 15) A non-transitory computer readable medium including a set of instructions that are executable by one or more processors of a computer to cause the computer to perform a method for retaining end user of a service, the method comprising: {“Techniques described herein may be utilized to implement systems and methods to analyze contacts data. Contacts data may refer to various types of communications that occur within the context of a contact center. A contact center may refer to a physical or logical unit of an organization that manages customer interactions.” [0031] One or more processes are carried out using a non-transitory computer readable medium. [0181], [0184], [0186]}
collecting end user specific information by an artificial intelligence agent; {Customer contact data is collected and is ingested and processed by AI analytics components. The collected information is specific to individual end users. [0038], [0058], [0062], [0074]}
training said artificial intelligence agent with said end user specific information; {An AI agent is trained using client training data in a system that stores and analyzes end user contact data such as customer transcripts and metadata. [0038], [0076]}
wherein said response is at least partially correlated to said end user specific information; and {The system generates analytics outputs and insights based on analysis of customer contacts data and associated interaction metadata, such that any response produced by the system is at least partially correlated to end user information derived from those customer interactions. [0031], [0034] – [0035], [0039]}
Sivasubramanian does not disclose:
receiving a prompt from said end user to terminate subscription of a service;
generating response by said artificial intelligence agent to said prompt; and
delivering said response via said user interface to said end user.
However, Yuan, in a similar field of endeavor directed to perform content authoring for chatbots and other types of automated agents, teaches:
receiving a prompt from said end user to terminate subscription of a service; {“Canceling a subscription” is used as an example intent that may be classified from user input. [0030], [0034]}
generating response by said artificial intelligence agent to said prompt, {The conversation engine decides the bot response (ask questions or deliver solutions) and outputs responses to the user via the interface. [0031] – [0032], [0045]}
delivering said response via said user interface to said end user. {Responses are delivered in a human-agent I/O setting via interface devices and a bot framework interface. [0030] – [0031], [0045]}
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the contacts data management features of Sivasubramanian to include the enhanced data analysis features of Yuan, for improved responsiveness and interaction sequences involving automated agents. (See paragraph [0028] of Yuan).
Claims 9 and 16
The combination of Sivasubramanian and Yuan teaches the limitations set forth above. Sivasubramanian further discloses:
training said artificial intelligence agent with policy information including cancellation policy and promotion policy information. {An NP AI agent is trained using client training data, and that agent is deployed to analyze customer contacts and automatically search organizational content to generate guidance during customer interactions. [0053], [0076], [0087]}
Claims 10 and 17
The combination of Sivasubramanian and Yuan teaches the limitations set forth above. Sivasubramanian further discloses:
training said artificial intelligence agent with workflow information. {An AI agent uses training data supplied by the client which is deployed to provide suggestions, next best actions, and real-time assistance during customer interactions (i.e., relies on knowledge of contact center workflows). [0036], [0053], [0076]}
Claims 11 and 18
The combination of Sivasubramanian and Yuan teaches the limitations set forth above. Sivasubramanian further discloses:
training said artificial intelligence agent with application programming interface information. {An AI agent uses training data supplied by the client which is operated within a system that integrates with and automatically searches organizational systems and content during live customers interactions via API. [0054], [0076], [0087]}
Claims 12 and 19
The combination of Sivasubramanian and Yuan teaches the limitations set forth above. Sivasubramanian further discloses:
training said artificial intelligence agent with service specific information. { An AI agent uses training data supplied by the client which is deployed to analyze contact center communications and provide real-time assistance, suggestions, and answers that are specific to the services offered by the organization. [0031], [0053], [0076], [0086] – [0087]}
Claims 13 and 20
The combination of Sivasubramanian and Yuan teaches the limitations set forth above. Sivasubramanian further discloses:
wherein said user specific information comprises user's subscription information. {The system obtains and uses customer specific information (e.g., subscription information) from integrated internal and third party systems during customer interactions. [0031], [0054], [0164]}
Claims 14 and 21
The combination of Sivasubramanian and Yuan teaches the limitations set forth above. Sivasubramanian further discloses:
wherein said user specific information comprises user's prior usage of a subscribed service. {The system obtains and uses customer specific information (e.g., subscription usage information) from integrated internal and third party systems during customer interactions. [0031], [0054], [0164]}
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure (additional pertinent references can be found on attached form PTO-892):
US 20200143386, which teaches: A support assessment system and method generate metrics to assess the quality, effectiveness, process adherence, or the like of customer support interactions. These metrics may be generated based at least in part on one or more support assessment models to provide objective measures of the customer support interactions. The support assessment models may be trained on training data based on a set of support conversations and indication of the metrics that are to result from those support conversations. The support assessment models may be any variety of machine learning models, such as neural network models. The objective measures generated by the support assessment models may further be used to recommend process changes, add or discontinue products or services, make assessments of customer support resources, and/or generate customer support training materials.
US 20220394348, which teaches: Contextual information for an ecosystem that includes a consumer electronic device is used by a virtual agent to speed up the process by which the virtual agent provides technical support related to the consumer electronic device. The contextual information is used to reduce the amount of information the virtual agent requires from the consumer. Whilst collecting information from the consumer, the virtual agent also functions to determines if a hand-off of the consumer to a further agent is needed.
“Investigating the user experience of customer service chatbot interaction: a framework for qualitative analysis of chatbot dialogues” (NPL attached), which teaches: The uptake of chatbots for customer service depends on the user experience. For such chatbots, user experience in particular concerns whether the user is provided relevant answers to their queries and the chatbot interaction brings them closer to resolving their problem. Dialogue data from interactions between users and chatbots represents a potentially valuable source of insight into user experience. However, there is a need for knowledge of how to make use of these data. Motivated by this, we present a framework for qualitative analysis of chatbot dialogues in the customer service domain. The framework has been developed across several studies involving two chatbots for customer service, in collaboration with the chatbot hosts. We present the framework and illustrate its application with insights from three case examples. Through the case findings, we show how the framework may provide insight into key drivers of user experience, including response relevance and dialogue helpfulness (Case 1), insight to drive chatbot improvement in practice (Case 2), and insight of theoretical and practical relevance for understanding chatbot user types and interaction patterns (Case 3). On the basis of the findings, we discuss the strengths and limitations of the framework, its theoretical and practical implications, and directions for future work.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CARLOS F MONTALVO whose telephone number is (703)756-5863. The examiner can normally be reached Monday - Friday 8:00AM - 5:30PM; First Fridays OOO.
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/C.F.M./Examiner, Art Unit 3629 /SARAH M MONFELDT/Supervisory Patent Examiner, Art Unit 3629