METHOD AND SYSTEM FOR A PARALLEL DISTRIBUTED HYPER-SWARM FOR AMPLIFYING HUMAN INTELLIGENCE

• US 20190121529A1
• Filed: 12/21/2018
• Published: 04/25/2019
• Est. Priority Date: 03/26/2014
• Status: Active Grant

• Current Assignee: Unanimous A.I., Inc.
• Original Assignee: Unanimous A I Incorporated
• Inventors: ROSENBERG, LOUIS B., Willcox, Gregg
• Granted Patent: US 10,817,158 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06Q 10/101 Collaborative creation, e.g. joint development of products or services
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Abstract

Systems and methods for amplifying the intelligence of networked human populations, maximizing the accuracy of collaborative forecasts and group insights. This includes systems and methods for sending and presenting a forecasting query for a future event to a plurality of participants, each using a networked computing device, the forecasting query describing a future event to be collaboratively predicted by the population of human participants. An initial forecast response is collected from each participant and analyzed by a central server. A plurality of unique overlapping subsets of responses are determined by the server. Unique overlapping subsets of unique initial forecast responses are then displayed, at substantially the same time, on each computing device. A second forecast response is collected from each participant and a final forecast is determined.

Claims

1. A method for computer-moderated collaborative forecasting 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;

providing a local forecasting application on each networked computing device, the local forecasting application configured for displaying forecasting information to and collecting forecasting input from the one member associated with that networked computing device; and

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

send a forecasting query to the plurality of networked computing devices, the forecasting query describing a future event to be collaboratively predicted by the population of human participants;

present, at substantially the same time, a representation of the forecasting query to each member of the population of human participants on a display of the computing device associated with that member;

collect an initial forecast response from each member of the population of human participants via a user interface on the computing device associated with that member;

store a set of initial forecast responses from the population of human participants in a memory accessible by the collaboration server;

identify a plurality of unique overlapping subsets of initial forecast responses from the set of initial forecast responses, each overlapping subset sharing at least one data point with another overlapping subset;

display, at substantially the same time, a different unique overlapping subset of initial forecast responses to each member of the population of human participants on the computing device associated with that member, thereby enabling that member to consider the initial forecasts responses provided by a different unique subset of human participants from the full population of human participant;

collect an updated forecast response from each member of the population of human participants via a user interface on the computing device associated with that member;

store a set of updated forecast responses from the population of human participants in a memory accessible by the collaboration server; and

compute a final collaborative forecast based at least in part upon the set of initial forecast responses and the set of updated forecast responses, the collaborative forecast providing an answer to the forecasting query.

2. The method of claim 1 wherein computing the final collaborative forecasting includes assessing the change, for each member of the population of human participants, between the initial forecast response they provided and the final forecast response they provided.

3. The method of claim 1 further including the step of representing within in a computer memory accessible to the collaboration server, a plurality of overlapping sub-populations of human participants wherein each overlapping sub-population is a unique subset of the full population of networked human participants that shares at least one member with at least one other overlapping sub-population.

4. The method of claim 3 wherein the step of identifying a plurality of unique overlapping subsets of initial forecast responses in performed based on the representation within the computer memory of the plurality of overlapping sub-populations of human participants.

5. The method of claim 1 wherein the steps of displaying, collecting, and storing are repeated multiple times enabling the storage of a plurality of sets of updated forecast responses over a time period, and wherein the final collaborative forecast is based at least in part upon the plurality of sets of updated forecasts collected over a period of time.