IP Library › Granted Patent US 12,190,294
Granted Patent B2
US 12,190,294 · App. 18/367,089 · Granted Jan 7, 2025

Methods and systems for hyperchat and hypervideo conversations across networked human populations with collective intelligence amplification

Inventors: Louis B. Rosenberg (San Luis Obispo, CA); Gregg Willcox (Seattle, WA)
Assignee: Unanimous A. I., Inc.
G06Q10/103G06F40/35H04L51/04
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Quick Facts
Patent No.
US 12,190,294
App. No.
18/367,089
Granted
Jan 7, 2025
Kind
B2
Abstract

The present disclosure describes systems and methods for enabling real-time conversational dialog among a large population of networked human users while facilitating convergence on groupwise decisions, insights, and solutions, and amplifying collective intelligence. A collaboration server running a collaboration application is provided, wherein the collaboration server is in communication with the plurality of the networked computing devices and each computing device is associated with one user of the population of human participants. In some cases, the collaboration server defines a plurality of sub-groups of human participants. A local chat application configured for displaying a conversational prompt received from the collaboration server is provided on each networked computing device. The local chat application enables real-time communication with other users of a sub-group assigned by the collaboration server. According to some embodiments, the computer mediated collaboration is enabled through communication between the collaboration application and the local chat applications.

Claims (228)

1. A method for computer-moderated collaboration among a population of human participants using a plurality of networked computing devices, the method comprising:

providing a collaboration server running a collaboration application, the collaboration server in communication with the plurality of the networked computing devices, each computing device associated with one member of the population of human participants, the collaboration server defining a plurality of sub-groups of the population of human participants;

providing a local chat application on each networked computing device, the local chat application configured for displaying a conversational prompt received from the collaboration server, and for enabling real-time chat communication with other members of an assigned sub-group, said real-time chat communication including sending chat input collected from the one member associated with the networked computing device to other members of the assigned sub-group; and

enabling through communication between the collaboration application running on the collaboration server and the local chat applications running on each of the plurality of networked computing devices, comprising the following steps:

(a) divide the population of human participants into a first sub-group consisting of a first unique portion of the population, a second sub-group consisting of a second unique portion of the population, and a third sub-group consisting of a third unique portion of the population, wherein the first unique portion consists of a first plurality of members of the population of human participants, the second unique portion consists of a second plurality of members of the population of human participants and the third unique portion consists of a third plurality of members of the population of human participants,

(b) send the conversational prompt to the plurality of networked computing devices, the conversational prompt comprising a question, issue, or topic to be collaboratively discussed by the population of human participants,

(c) present a representation of the conversational prompt to each member of the population of human participants on a display of the computing device associated with that member,

(d) collect and store a first conversational dialogue in a first memory portion from members of the first sub-group during an interval via a user interface on the computing device associated with each member,

(e) collect and store a second conversational dialogue in a second memory portion from members of the second sub-group during the interval via a user interface on the computing device associated with each member,

(f) collect and store a third conversational dialogue in a third memory portion from members the third sub-group during an interval via a user interface on the computing device associated with each member,

(g) process the first conversational dialogue at the collaboration server using a large language model to identify a first conversational argument, wherein the first conversational argument comprises at least one assertion, viewpoint, position or claim in the first conversational dialogue,

(h) process the second conversational dialogue at the collaboration server using the large language model to identify a second conversational argument, wherein the second conversational argument comprises at least one assertion, viewpoint, position or claim in the second conversational dialogue,

(i) process the third conversational dialogue at the collaboration server using the large language model to identify a third conversational argument, wherein the third conversational argument comprises at least one assertion, viewpoint, position or claim in the third conversational dialogue,

(j) send the first conversational argument to each of the members of a first different sub-group, wherein the first different sub-group is not the first sub-group,

(k) send the second conversational argument to each of the members of a second different sub-group, wherein the second different sub-group is not the second sub-group,

(l) send the third conversational argument to each of the members of a third different sub-group, wherein the third different sub-group is not the third sub-group, and

(m) repeat steps (d) through (l) at least one time.

2. The method of claim 1 further comprising:

in step (j), sending the first conversational argument to each of the members of a first different sub-group expressed in first person conversational form, as if the first conversational argument were coming from a member of the first different sub-group of the population of human participants;

in step (k), sending the second conversational argument to each of the members of a second different sub-group expressed in first person conversational form, as if the second conversational argument were coming from a member of the second different sub-group of the population of human participants; and

in step (l), sending the third conversational argument to each of the members of a third different sub-group expressed in first person conversational form, as if the third conversational argument were coming from a member of the third different sub-group of the population of human participants.

3. The method of claim 1 further comprising:

(n) process the first conversational argument, the second conversational argument, and the third conversational argument using the large language model to generate a global conversational argument.

4. The method of claim 3 further comprising:

(o) send the global conversational argument to each of the members of the first sub-group, the second sub-group, and the third sub-group.

5. The method of claim 4 further comprising:

(p) expressing the global conversational argument to members of the first sub-group, the second sub-group, and the third sub-group in conversational form via visually displayed text or audibly displayed voice.

6. The method of claim 5 wherein the global conversational argument is expressed in first person.

7. The method of claim 1 wherein said first conversational argument, second conversational argument, and third conversational argument each comprises at least one assertion, viewpoint, position, or claim supported by evidence or reasoning.

8. The method of claim 1 further comprising:

said processing said first conversational dialogue in step (g) further comprising determining a sentiment indicator for each conversational argument entered by the first sub-group, wherein the sentiment indicator represents a level of support for the associated conversational argument in the first sub-group;

said processing said second conversational dialogue in step (h) further comprising determining a sentiment indicator for each conversational argument entered by the second sub-group, wherein the sentiment indicator represents a level of support for the associated conversational argument in the second sub-group; and

said processing said third conversational dialogue in step (i) further comprises determining a sentiment indicator for each conversational argument entered by the third sub-group, wherein the sentiment indicator provides represents a level of support for the associated conversational argument in the third sub-group.

9. The method of claim 1 further comprising:

said processing said first conversational dialogue in step (g) further comprising determining a conviction indicator for each conversational argument entered by the first sub-group, wherein the conviction indicator represents a level of conviction for the associated conversational argument in the first sub-group;

said processing said second conversational dialogue in step (h) further comprising determining a conviction indicator for each conversational argument entered by the second sub-group, wherein the conviction indicator represents a level of conviction for the associated conversational argument in the second sub-group; and

said processing said third conversational dialogue in step (i) further comprises determining a conviction indicator for each conversational argument entered by the third sub-group, wherein the conviction indicator represents a level of conviction for the associated conversational argument in the third sub-group.

10. The method of claim 1 wherein the each unique portion consists of no more than ten members of the population of human participants.

11. The method of claim 1 wherein said first conversational dialogue comprises verbal content extracted from audio or video signals captured by one or more computing devices of the first sub-group.

12. The method of claim 11 wherein said verbal content extracted from said audio or video signals includes words spoken by one or more members of the first sub-group.

13. The method of claim 12 wherein said verbal content extracted from said audio or video signals includes sentiment information derived from vocal inflections.

14. The method of claim 12 wherein said verbal content extracted from said video signals includes sentiment content derived from facial expressions.

15. The method of claim 1 wherein each of said repeating steps occurs after expiration of an interval.

16. The method of claim 15 wherein said interval is a time interval.

17. The method of claim 15 wherein said intervals is a number of conversational interactions.

18. The method of claim 1 wherein the first different sub-group is the second sub-group, and the second different sub-group is the third sub-group.

19. The method of claim 1 wherein the first different sub-group is a first randomly selected sub-group, the second different sub-group is a second randomly selected sub-group, and the third different sub-group is a third randomly selected sub-group, wherein the first randomly selected sub-group, the second randomly selected sub-group and the third randomly selected sub-group are not the same sub-group.

20. The method of claim 1 further comprising:

(g) said sending the first conversational argument to members of a first different subgroup in response to a determination by the collaboration server that said first conversational argument has not been identified in the conversational dialog of said first different sub-group;

(h) said sending the second conversational argument to members of a second different subgroup in response to a determination by the collaboration server that said second conversational argument has not been identified in said second different sub-group; and

(i) said sending the third conversational argument to members of a third different subgroup in response to a determination by the collaboration server that said third conversational argument has not been identified in said third different sub-group.

21. A system for computer-moderated collaboration among a population of human participants using a plurality of networked computing devices, the system comprising:

a collaboration server running a collaboration application, the collaboration server in communication with the plurality of the networked computing devices, each computing device associated with one member of the population of human participants, the collaboration server defining a plurality of sub-groups of the population of human participants;

a local chat application on each networked computing device, the local chat application configured for displaying a conversational prompt received from the collaboration server, and for enabling real-time chat communication with other members of an assigned sub-group, said real-time chat communication including sending chat input collected from the one member associated with the networked computing device to other members of the assigned sub-group; and

software components executed by the collaboration server and the local chat application for enabling through communication between the collaboration application running on the collaboration server and the local chat applications running on each of the plurality of networked computing devices, comprising the following steps:

(a) divide the population of human participants into a first sub-group consisting of a first unique portion of the population, a second sub-group consisting of a second unique portion of the population, and a third sub-group consisting of a third unique portion of the population, wherein the first unique portion consists of a first plurality of members of the population of human participants, the second unique portion consists of a second plurality of members of the population of human participants and the third unique portion consists of a third plurality of members of the population of human participants,

(b) send the conversational prompt to the plurality of networked computing devices, the conversational prompt comprising a question, issue, or topic to be collaboratively discussed by the population of human participants,

(c) present a representation of the conversational prompt to each member of the population of human participants on a display of the computing device associated with that member,

(d) collect and store a first conversational dialogue in a first memory portion from members of the first sub-group during an interval via a user interface on the computing device associated with each member,

(e) collect and store a second conversational dialogue in a second memory portion from members the second sub-group during the interval via a user interface on the computing device associated with each member,

(f) collect and store a third conversational dialogue in a third memory portion from members of the third sub-group during an interval via a user interface on the computing device associated with each member,

(g) process the first conversational dialogue at the collaboration server using a large language model to identify a first conversational argument, wherein the first conversational argument comprises at least one assertion, viewpoint, position or claim in the first conversational dialogue,

(h) process the second conversational dialogue at the collaboration server using the large language model to identify a second conversational argument, wherein the second conversational argument comprises at least one assertion, viewpoint, position or claim in the second conversational dialogue,

(i) process the third conversational dialogue at the collaboration server using the large language model to identify a third conversational argument, wherein the third conversational argument comprises at least one assertion, viewpoint, position or claim in the third conversational dialogue,

(j) send the first conversational argument to each of the members of a first different sub-group, wherein the first different sub-group is not the first sub-group,

(k) send the second conversational argument to each of the members of a second different sub-group, wherein the second different sub-group is not the second sub-group,

(l) send the third conversational argument to each of the members of a third different sub-group, wherein the third different sub-group is not the third sub-group, and

(m) repeat steps (d) through (l) at least one time.

22. The system of claim 21 further comprising:

in step (j), sending the first conversational argument to each of the members of a first different sub-group expressed in first person conversational form, as if coming from a member of the first different sub-group of the population of human participants;

in step (k), sending the second conversational argument to each of the members of a second different sub-group expressed in first person conversational form, as if coming from a member of the second different sub-group of the population of human participants; and

in step (l), sending the third conversational argument to each of the members of a third different sub-group expressed in first person conversational form, as if coming from a member of the third different sub-group of the population of human participants.

23. The system of claim 21 further comprising:

(n) process the first conversational argument, the second conversational argument, and the third conversational argument using the large language model to generate a global conversational argument.

24. The system of claim 23 further comprising:

(o) send the global conversational argument to each of the members of the first sub-group, the second sub-group, and the third sub-group.

25. The system of claim 24 further comprising:

(p) expressing the global conversational argument to members of the first sub-group, the second sub-group, and the third sub-group in conversational form via visually displayed text or audibly displayed voice.

26. The system of claim 25 wherein the global conversational argument is expressed in first person.

27. The system of claim 21 wherein the first conversational argument, the second conversational argument, and the third conversational argument each comprises at least one assertion, viewpoint, position or claim supported by evidence or reasoning.

28. The system of claim 21 further comprising:

said processing said first conversational dialogue in step (g) further comprising determining a sentiment indicator for each conversational argument entered by the first sub-group, wherein the sentiment indicator represents a level of support for the associated conversational argument in the first sub-group;

said processing said second conversational dialogue in step (h) further comprising determining a sentiment indicator for each conversational argument entered by the second sub-group, wherein the sentiment indicator represents a level of support for the associated conversational argument in the second sub-group; and

said processing said third conversational dialogue in step (i) further comprises determining a sentiment indicator for each conversational argument entered by the third sub-group, wherein the sentiment indicator represents a level of support for the associated conversational argument in the third sub-group.

29. The system of claim 21 further comprising:

said processing said first conversational dialogue in step (g) further comprising determining a conviction indicator for each conversational argument entered by the first sub-group, wherein the conviction indicator represents a level of conviction for the associated conversational argument in the first sub-group;

said processing said second conversational dialogue in step (h) further comprising determining a conviction indicator for each conversational argument entered by the second sub-group, wherein the conviction indicator represents a level of conviction for the associated conversational argument in the second sub-group; and

said processing said third conversational dialogue in step (i) further comprises determining a conviction indicator for each conversational argument entered by the third sub-group, wherein the conviction indicator represents a level of conviction for the associated conversational argument in the third sub-group.

30. The system of claim 21 wherein each unique portion consists of no more than ten members of the population of human participants.

31. The system of claim 21 wherein said first conversational dialogue comprises verbal content extracted from audio or video signals captured by one or more computing devices of the first sub-group.

32. The system of claim 31 wherein said verbal content extracted from said audio or video signals includes words spoken by one or more members of the first sub-group.

33. The system of claim 32 wherein said verbal content extracted from said audio or video signals includes sentiment information derived from vocal inflections.

34. The system of claim 32 wherein said verbal content extracted from said video signals includes sentiment content derived from facial expressions.

35. The system of claim 21 wherein each of said repeating steps occurs after expiration of an interval.

36. The system of claim 35 wherein said interval is a time interval.

37. The system of claim 35 wherein said intervals is a number of conversational interactions.

38. The system of claim 21 wherein the first different sub-group is the second sub-group, and the second different sub-group is the third sub-group.

39. The system of claim 21 wherein the first different sub-group is a first randomly selected sub-group, the second different sub-group is a second randomly selected sub-group, and the third different sub-group is a third randomly selected sub-group, wherein the first randomly selected sub-group, the second randomly selected sub-group and the third randomly selected sub-group are not the same sub-group.

40. The system of claim 21 further comprising:

(g) said sending the first conversational argument to members of the first different subgroup in response to a determination by the collaboration server that said first conversational argument has not been identified in said first different sub-group;

(h) said sending the second conversational argument to members of the second different subgroup in response to a determination by the collaboration server that said second conversational argument has not been identified in said second different sub-group; and

(i) said sending the third conversational argument to members of the third different subgroup in response to a determination by the collaboration server that said third conversational argument has not been identified in said third different sub-group.

41. A method for computer-moderated collaboration among a population of human participants using a plurality of networked computing devices, the method comprising:

providing a collaboration server running a collaboration application, the collaboration server in communication with the plurality of the networked computing devices, each computing device associated with one member of the population of human participants, the collaboration server defining a plurality of sub-groups of the population of human participants;

providing a local chat application on each networked computing device, the local chat application configured for enabling real-time chat communication with other members of a sub-group assigned by the collaboration server;

enabling through communication between the collaboration application running on the collaboration server and the local chat applications running on each of the plurality of networked computing devices, the following steps:

(a) divide the population of human participants into a first sub-group, second sub-group, and third sub-group, wherein each sub-group consists of a different plurality of members of the population;

(b) collect and store an interval of first conversational dialogue from members of the first sub-group, an interval of second conversational dialogue from members of the second sub-group, and an interval of third conversational dialogue from members of the third sub-group,

(c) process using a large language model, the interval of first conversational dialogue to generate and store a first conversational summary,

(d) process using a large language model, the interval of second conversational dialogue to generate and store a second conversational summary,

(e) process using a large language model, the interval of third conversational dialogue to generate and store a third conversational summary,

(f) send and display the first conversational summary to each of the members of a first different sub-group, wherein the first different sub-group is not the first sub-group,

(g) send and display the second conversational summary to each of the members of a second different sub-group, wherein the second different sub-group is not the second sub-group,

(h) send and display the third conversational summary to each of the members of a third different sub-group, wherein the third different sub-group is not the third sub-group,

(i) repeat steps (b) through (h) at least one time, thereby generating and storing at least two first conversational summaries, second conversational summaries, and third conversational summaries,

(j) process, using a large language model, the at least two stored first conversational summaries, the at least two second conversational summaries, and the at least two third second conversational summaries, to generate a global conversational summary, and

(k) send and display the global conversational summary to the members of the first, second, and third sub-groups.

42. The method of claim 41 where the first conversational summary is displayed in first person conversational form to each of the members of the first different sub-group as if the first conversational summary were coming from an additional member (simulated) of the first different sub-group.

43. The method of claim 41 wherein said generating of the global conversational summary is performed by weighting more recent conversational summaries more heavily than less recent conversational summaries.

44. The method of claim 41 wherein said first conversational dialogue, said second conversational dialogue and said third conversational dialogue each comprise a set of ordered chat messages comprising text.

45. The method of claim 44 wherein said first conversational dialogue, said second conversational dialogue and said third conversational dialogue each further comprise a respective member identifier for the member of the population of human participants who entered each chat message.

46. The method of claim 45 wherein said first conversational dialogue, said second conversational dialogue and said third conversational dialogue each further comprises a respective timestamp identifier for a time of day when each chat message is entered.

47. The method of claim 44 further comprising determining a sentiment indicator for each chat message entered by the first sub-group, the second sub-group, and the third sub-group, the sentiment indicator representing a level of support for an assertion, viewpoint, position or claim made in the chat message.

48. The method of claim 44 further comprising determining a conviction indicator for each chat message entered by the first sub-group, the second sub-group, and the third sub-group, the conviction indicator representing a level of conviction in an assertion, viewpoint, position or claim made in the chat message.

49. The method of claim 41 wherein said collecting and storing an interval of first conversational dialogue includes capturing through a microphone, a spoken verbalization of at least one member of the first sub-group and converting the spoken verbalization to a text representation.

50. The method of claim 49 wherein said collecting and storing an interval of first conversational dialogue includes capturing through a microphone, the spoken verbalization of at least one member and assessing at least one component indicative of emotional value in vocal inflections.

51. The method of claim 41 wherein each of said repeating steps occurs after expiration of an interval.

52. The method of claim 51 wherein said interval is a time interval.

53. The method of claim 51 wherein said intervals is a number of conversational interactions.

54. The method of claim 41 wherein said real-time chat communication is comprised as a video conference.

55. The method of claim 41 wherein said first conversational summary that is displayed in first person conversational form is output to members of said first sub-group as simulated audible human speech.

56. The method of claim 55 wherein said first conversational summary that is displayed in first person conversational form is output to members of said first sub-group as simulated audible human speech expressed by a simulated visual representation of a speaking human or other character.

57. A system for computer-moderated collaboration among a population of human participants using a plurality of networked computing devices, the system comprising:

a collaboration server running a collaboration application, the collaboration server in communication with the plurality of the networked computing devices, each computing device associated with one member of the population of human participants, the collaboration server defining a plurality of sub-groups of the population of human participants;

a local chat application on each networked computing device, the local chat application configured for enabling real-time chat communication with other members of a sub-group assigned by the collaboration server;

software components executed by the collaboration server and the local chat applications running on each of the plurality of networked computing devices for enabling thorough communication between the collaboration application running on the collaboration server and the local chat applications running on each of the plurality of networked computing devices, the following steps:

(a) divide the population of human participants into a first sub-group, second sub-group, and third sub-group, wherein each sub-group consists of a different plurality of members of the population;

(b) collect and store an interval of first conversational dialogue from members of the first sub-group, an interval of second conversational dialogue from members of the second sub-group, and an interval of third conversational dialogue from members of the third sub-group,

(c) process using a large language model, the interval of first conversational dialogue to generate and store a first conversational summary,

(d) process using a large language model, the interval of second conversational dialogue to generate and store a second conversational summary,

(e) process using a large language model, the interval of third conversational dialogue to generate and store a third conversational summary,

(f) send and display the first conversational summary to each of the members of a first different sub-group, wherein the first different sub-group is not the first sub-group,

(g) send and display the second conversational summary to each of the members of a second different sub-group, wherein the second different sub-group is not the second sub-group,

(h) send and display the third conversational summary to each of the members of a third different sub-group, wherein the third different sub-group is not the third sub-group,

(i) repeat steps (b) through (h) at least one time, thereby generating and storing at least two first conversational summaries, second conversational summaries, and third conversational summaries,

(j) process, using a large language model, the at least two stored first conversational summaries, the at least two second conversational summaries, and the at least two third second conversational summaries, to generate a global conversational summary, and

(k) send and display the global conversational summary to the members of the first, second, and third sub-groups.

58. A system for computer-moderated collaboration among a population of human participants using a plurality of networked computing devices, the system comprising:

a collaboration server running a collaboration application, the collaboration server in communication with the plurality of the networked computing devices, each computing device associated with one member of the population of human participants, the collaboration server defining a plurality of sub-groups of the population of human participants;

a local chat application on each networked computing device, the local chat application configured for displaying a conversational prompt received from the collaboration server, and for enabling real-time chat communication with other members of a sub-group assigned by the collaboration server, said real-time chat communication including sending chat input collected from the one member associated with the networked computing device to other members of the assigned sub-group; and

software components executed by the collaboration server and the local chat applications running on each of the plurality of networked computing devices for enabling through communication between the collaboration application running on the collaboration server and the local chat applications running on each of the plurality of networked computing devices, comprising the following steps:

(a) divide the population of human participants into a first sub-group, a second sub-group, and a third sub-group, wherein the first, second, and third sub-groups consists of different members of the population of human participants,

(b) send the conversational prompt to the plurality of networked computing devices, the conversational prompt comprising a question, issue, or topic to be collaboratively discussed by the population of human participants,

(c) present a representation of the conversational prompt to each member of the population of human participants via a display of the computing device associated with that member,

(d) collect and store a first conversational dialogue from members of the population of human participants in the first sub-group during an interval via a user interface on the computing device associated with each member of the first sub-group,

(e) collect and store a second conversational dialogue from members of the population of human participants in the second sub-group during the interval via a user interface on the computing device associated with each member of second sub-group,

(f) collect and store a third conversational dialogue from members of the population of human participants in the third sub-group during the interval via a user interface on the computing device associated with each member of the third sub-group,

(g) process the first conversational dialogue at the collaboration server using a large language model to generate a first conversational summary in conversational form,

(h) process the second conversational dialogue at the collaboration server using the large language model to generate a second conversational summary in conversational form,

(i) process the third conversational dialogue at the collaboration server using the large language model to generate a third conversational summary in conversational form,

(j) send the first conversational summary expressed in conversational form to each of the members of a first different sub-group, wherein the first different sub-group is not the first sub-group,

(k) send the second conversational summary expressed in conversational form to each of the members of a second different sub-group, wherein the second different sub-group is not the second sub-group,

(l) send the third conversational summary expressed in conversational form to each of the members of a third different sub-group, wherein the third different sub-group is not the third sub-group,

(m) repeat steps (d) through (l) at least one time;

(n) monitoring the first conversational dialogue for a first assertion, viewpoint, position or claim not supported by first reasoning or evidence,

(o) sending, in response to monitoring the first conversational dialogue, a first conversational question to the first sub-group requesting first reasoning or evidence in support of the first assertion viewpoint, position or claim,

(p) monitoring the second conversational dialogue for a second assertion, viewpoint, position or claim not supported by second reasoning or evidence,

(q) sending, in response to monitoring the second conversational dialogue, a second conversational question to the second sub-group requesting second reasoning or evidence in support of the second viewpoint, position or claim,

(r) monitoring the third conversational dialogue for a third assertion, viewpoint, position or claim not supported by third reasoning or evidence, and

(s) sending, in response to monitoring the third conversational dialogue, a third conversational question to the third sub-group requesting third reasoning or evidence in support of the third viewpoint, position or claim.

59. The system of claim 58 further comprising:

in step (j), sending the first conversational summary expressed in conversational form to each of the members of a first different sub-group expressed in first person as if the first conversational summary were coming from an additional member (simulated) of the first different sub-group of the population of human participants;

in step (k), sending the second conversational summary expressed in conversational form to each of the members of a second different sub-group expressed in first person as if the as if the second conversational summary were coming from an additional member (simulated) of the second different sub-group of the population of human participants; and

in step (l), sending the third conversational summary expressed in conversational form to each of the members of a third different sub-group expressed in first person as if the third conversational summary were coming from an additional member (simulated) of the third different sub-group of the population of human participants.

60. The system of claim 58 further comprising:

(n) process the first conversational summary, the second conversational summary, and the third conversational summary using the large language model to generate a global conversational summary expressed in conversational form.

61. The system of claim 60 further comprising:

(o) send the global conversational summary expressed in conversational form to each of the members of the first sub-group, the second sub-group, and the third sub-group.

62. A method for computer-moderated collaboration among a population of human participants using a plurality of networked computing devices, the method comprising:

providing a collaboration server running a collaboration application, the collaboration server in communication with the plurality of the networked computing devices, each computing device associated with one member of the population of human participants, the collaboration server defining a plurality of sub-groups of the population of human participants;

providing a local chat application on each networked computing device, the local chat application configured for displaying a conversational prompt received from the collaboration server, and for enabling real-time chat communication with other members of a sub-group assigned by the collaboration server, said real-time chat communication including sending chat input collected from the one member associated with the networked computing device to other members of the assigned sub-group; and

enabling through communication between the collaboration application running on the collaboration server and the local chat applications running on each of the plurality of networked computing devices, comprising the following steps:

(a) send the conversational prompt to the plurality of networked computing devices, the conversational prompt comprising a question, issue, or topic to be collaboratively discussed by the population of human participants,

(b) present a representation of the conversational prompt to each member of the population of human participants via a display of the computing device associated with that member,

(c) divide the population of human participants into a first sub-group, a second sub-group, and a third sub-group wherein said first, second, and third sub-groups consist of different members of the population of human participants,

(d) collect and store a first conversational dialogue from members of the population of human participants in the first sub-group during an interval via a user interface on the computing device associated with each member of the population of human participants in the first sub-group,

(e) collect and store a second conversational dialogue from members of the population of human participants in the second sub-group during the interval via a user interface on the computing device associated with each member of the population of human participants in the second sub-group,

(f) collect and store a third conversational dialogue from members of the population of human participants in the third sub-group during the interval via a user interface on the computing device associated with each member of the population of human participants in the third sub-group,

(g) process the first conversational dialogue at the collaboration server using a large language model to generate a first conversational summary in conversational form,

(h) process the second conversational dialogue at the collaboration server using the large language model to generate a second conversational summary in conversational form,

(i) process the third conversational dialogue at the collaboration server using the large language model to generate a third conversational summary in conversational form,

(j) send the first conversational summary expressed in conversational form to each of the members of a first different sub-group, wherein the first different sub-group is not the first sub-group,

(k) send the second conversational summary expressed in conversational form to each of the members of a second different sub-group, wherein the second different sub-group is not the second sub-group,

(l) send the third conversational summary expressed in conversational form to each of the members of a third different sub-group, wherein the third different sub-group is not the third sub-group,

(m) repeat steps (d) through (l) at least one time,

(n) monitoring the first conversational dialogue for a first assertion, viewpoint, position or claim supported by first reasoning or evidence,

(o) sending, in response to monitoring the first conversational dialogue, a first conversational challenge to the first sub-group questioning the first reasoning or evidence in support of the first assertion, viewpoint, position or claim,

(p) monitoring the second conversational dialogue for a second assertion, viewpoint, position or claim supported by second reasoning or evidence,

(q) sending, in response to monitoring the second conversational dialogue, a second conversational challenge to the second sub-group questioning second reasoning or evidence in support of the second assertion viewpoint, position or claim,

(r) monitoring the third conversational dialogue for a third assertion, viewpoint, position or claim supported by third reasoning or evidence, and

(s) sending, in response to monitoring the third conversational dialogue, a third conversational challenge to the third sub-group questioning third reasoning or evidence in support of the third assertion, viewpoint, position or claim.

63. The method of claim 62 further comprising:

in step (b), sending the first conversational challenge to the first sub-group questioning the first reasoning or evidence in support of the first assertion, viewpoint, position, or claim, wherein the questioning the first reasoning or evidence includes an assertion, viewpoint, position, or claim collected from the second different sub-group or the third different sub-group.

64. A system for computer-moderated collaboration among a population of human participants using a plurality of networked computing devices, the system comprising:

a collaboration server running a collaboration application, the collaboration server in communication with the plurality of the networked computing devices, each computing device associated with one member of the population of human participants, the collaboration server defining a plurality of sub-groups of the population of human participants, the collaboration server comprising:

a local chat application on each networked computing device, the local chat application configured for displaying a conversational prompt received from the collaboration server, and for enabling real-time chat communication with other members of a sub-group assigned by the collaboration server, said real-time chat communication including sending chat input collected from the one member associated with the networked computing device to other members of the assigned sub-group; and

software components executed by the collaboration server and the local chat application for enabling through communication between the collaboration application running on the collaboration server and the local chat applications running on each of the plurality of networked computing devices, comprising the following steps:

(a) send the conversational prompt to the plurality of networked computing devices, the conversational prompt comprising a question, issue, or topic to be collaboratively discussed by the population of human participants,

(b) present a representation of the conversational prompt to each member of the population of human participants on a display of the computing device associated with that member,

(c) divide the population of human participants into a first sub-group, a second sub-group, and a third sub-group wherein each sub-group consists of different members of the population of human participants,

(d) collect and store a first conversational dialogue from members of the population of human participants in the first sub-group during an interval via a user interface on the computing device associated with each member of the population of human participants in the first sub-group,

(e) collect and store a second conversational dialogue from members of the population of human participants in the second sub-group during the interval via a user interface on the computing device associated with each member of the population of human participants in the second sub-group,

(f) collect and store a third conversational dialogue from members of the population of human participants in the third sub-group during the interval via a user interface on the computing device associated with each member of the population of human participants in the third sub-group,

(g) process the first conversational dialogue at the collaboration server using a large language model to express a first conversational summary in conversational form,

(h) process the second conversational dialogue at the collaboration server using the large language model to express a second conversational summary in conversational form,

(i) process the third conversational dialogue at the collaboration server using the large language model to express a third conversational summary in conversational form,

(j) send the first conversational summary expressed in conversational form to each of the members of a first different sub-group, wherein the first different sub-group is not the first sub-group,

(k) send the second conversational summary expressed in conversational form to each of the members of a second different sub-group, wherein the second different sub-group is not the second sub-group,

(l) send the third conversational summary expressed in conversational form to each of the members of a third different sub-group, wherein the third different sub-group is not the third sub-group,

(m) repeat steps (d) through (l) at least one time,

(n) monitoring the first conversational dialogue for a first assertion, viewpoint, position or claim that is not supported by first reasoning or evidence,

(o) sending, in response to monitoring the first conversational dialogue, a first conversational request to the first sub-group asking for reasoning or evidence in support of the first assertion, viewpoint, position or claim,

(p) monitoring the second conversational dialogue for a second assertion, viewpoint, position or claim that is not supported by second reasoning or evidence,

(q) sending, in response to monitoring the second conversational dialogue, a second conversational request to the second sub-group asking for reasoning or evidence in support of the second assertion viewpoint, position or claim,

(r) monitoring the third conversational dialogue for a third viewpoint, position or claim supported by third reasoning or evidence, and

(s) sending, in response to monitoring the third conversational dialogue, a third conversational request to the third sub-group asking for reasoning or evidence in support of the third viewpoint, position or claim.

65. The system of claim 64 further comprising:

in step (b), sending the first conversational request to the first sub-group asking for reasoning or evidence in support of the first assertion, viewpoint, position, or claim, wherein the asking for reasoning or evidence is expressed in first person as if coming from another member (simulated) of the first sub-group.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 6, 2023
From: ROSENBERG, LOUIS B.; WILLCOX, GREGG
To: UNANIMOUS A.I., INC.
Reel/Frame 065151/0981 →
Continuity (5)
Continuation In Part 18240286 · Aug 30, 2023
Provisional Application 63456483 · Apr 1, 2023
Provisional Application 63451614 · Mar 12, 2023
Provisional Application 63449986 · Mar 4, 2023
Related Publication 20240296420A1 · Sep 5, 2024
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