Remote Group Decision-Making via Iterative Device Group Consensus
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Solution Overview
Problem
Existing videoconferencing tools struggle to manage large group discussions efficiently, leading to unmanageable data exchange and increased time required to reach decisions as the number of participants grows.
Innovation Solution
A computer-implemented method involving a server that establishes device groups and master groups, allowing participants to vote on options within their groups, with the server automatically determining a consensus option and iteratively refining the options until a single decision is reached.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If all users communicate in a single large group via videoconferencing tools, then everyone can share information directly, but the time required to discuss all information increases linearly with the number of users and the conversation becomes unmanageable
Solution Approach 1:
The system segments the large group of users into multiple smaller device groups, each discussing a subset of options. This segmentation allows parallel processing of discussions across groups while maintaining manageable conversation sizes, thereby reducing the overall time to reach a decision without sacrificing ease of management.
Solution Approach 2:
The system merges the results from multiple segmented device groups by having each group vote on their preferred options, then iteratively refining the combined results across groups. This merging process allows the system to aggregate insights from all users efficiently, achieving comprehensive decision-making without the linear time cost of a single large-group discussion.
2Adaptability or versatility
If videoconferencing tools are used to facilitate discussions among large numbers of users, then remote communication is enabled, but data exchange becomes unmanageable and difficult to follow
Solution Approach 1:
The system segments data exchange into smaller, controlled units by restricting communication within device groups rather than allowing all-to-all communication. This segmentation reduces the complexity of data exchange management while preserving the ability to facilitate remote group discussions through structured, scalable groupings.
Solution Approach 2:
The system introduces an intermediary mechanism where the server coordinates data exchange between device groups, managing the complexity of remote communication. This intermediary approach enables scalable remote group discussion by mediating data flow, preventing unmanageable direct peer-to-peer exchange among all users.
3Reliability
If traditional videoconferencing methods are used for deliberative meetings, then all users can present information, but the time required to discuss all information scales linearly with the number of users
Solution Approach 1:
The system segments the information discussion process into parallel device group discussions, each evaluating specific options. This segmentation maintains reliability by ensuring all information is discussed across the distributed groups while dramatically improving productivity by eliminating the linear time scaling inherent in sequential large-group discussions.
Solution Approach 2:
The system enables continuous useful action by having multiple device groups discuss different options simultaneously in parallel rather than sequentially. This continuous parallel processing maintains completeness of information discussion while significantly accelerating the decision-making process, breaking the linear time scaling constraint.
Data Source
AI summary
A computer-implemented method of collaborative decision making between a plurality of participant devices is described. The method comprises: establishing a connection between a server and each of the participant devices, wherein the participant devices are remote from the server: assigning to each of the participant devices connected to the server one of a plurality of options; and (a) establishing, by the server, a plurality of device groups and assigning each of the participant devices to one of the device groups such that there are two or more differing assigned options across the participant devices of each device group, the set of assigned options across a device group being defined as an option set; and establishing, by the server, one or more master groups, each master group comprising one or more device groups which are assigned the same option set. Then, the method further comprises (b) within each device group: (b1) transmitting to each of the respective plurality of the participant devices data comprising the option set assigned to the device group; (b2) establishing a communications link, via the server, between the participant devices of the device group, allowing communications between all devices within the device group for a set time period; (b3) receiving, at the server, a selection from each of the respective plurality of the participant devices of one of the options of the option set transmitted to it in step (b1), where the option that received the most selections within the device group is defined as the device group selection; and (c) assigning, by the server, the consensus option of each master group to each of the participant devices within the master group, thereby replacing the option previously assigned to each participant device. The consensus option comprises either: the option that received the most selections across all participant devices within the master group; or the option that received the most device group selections across all device groups of the master group. The method then comprises (d) closing the device groups; performing at least one further iteration of steps (a) to (d) and outputting a decision result comprising the one or more remaining options assigned across the participant devices.