Real-Time Collective Intelligence Decision System
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Solution Overview
Problem
Current portable computing devices lack tools and methods to enable real-time group-wise experiences that facilitate collaborative consciousness among networked individuals, failing to effectively allow groups to contribute their intent and express a collective will.
Innovation Solution
A method for real-time collaborative control of a graphical object, where individual users' computing devices exchange data with a collaboration server to determine the object's location and assign users to factions based on their input, enabling collective decision-making and group intent formation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If real-time collaborative control systems are implemented, then group decision-making capability is improved, but system complexity increases
Solution Approach 1:
A collaboration server acts as an intermediary between individual computing devices, coordinating user inputs and managing the graphical object control logic. This centralizes complexity in a dedicated mediator component rather than distributing it across all devices, enabling sophisticated group decision-making while keeping individual device implementations relatively simple.
Solution Approach 2:
Multiple individual user inputs are merged into a single collective control mechanism for the graphical object. The system combines disparate user intents into unified faction assignments and coordinated movements, enabling complex group intelligence to emerge from simple individual contributions.
2Stability of the object's composition
If real-time feedback mechanisms are implemented, then group cohesion is improved, but information processing requirements increase
Solution Approach 1:
The system provides real-time feedback through visual representation of faction assignments and graphical object positions, delivering sufficient information to maintain group cohesion without processing every possible data point. The feedback is partial but strategically selected to achieve the desired cohesive effect.
Solution Approach 2:
The system creates visual copies and representations of user inputs (user icons, faction assignments, graphical object positions) that can be displayed and processed without handling the full complexity of raw input data. These simplified representations enable real-time feedback while reducing information processing demands.
Data Source
AI summary
Systems and methods for real-time collaborative computing and collective intelligence are disclosed. A collaborative application runs on a collaborative server connected to a plurality of computing devices. Collaborative sessions are run wherein a group of independent users, networked over the internet, collaboratively answer questions in real-time, thereby harnessing their collective intelligence. Methods are disclosed for assigning users to factions during a collaborative decision process, wherein the collaborative server repeatedly checks the input of each user with respect to a plurality of proposed answers and assigns the user to the faction associated with the answer the user is trying to select. Furthermore, user assessments are made based on a stored time-history of faction associations for that user during a decision period. Such assessments include, but are not limited to, determining which users were entrenched, which were flexible, and which were fickle, during the collective intelligence decision making process.