Abstract: Systems and methods for amplifying the collective intelligence of networked human groups engaged in collaborative forecasting of future events having two possible outcomes. During a real-time session a computing device for each user displays a forecasting prompt and a dynamic user interface which includes a user-manipulatable marker moved by the user between a first limit and a second limit, where the position of the marker defines a forecasted probability of each possible outcome. The display also includes a first reward value and a second reward value, both of which are interactively responsive to the marker position. During a first time period, users manipulate the markers. After the first time period, a perturbation stimulus is displayed. During a second time period, users again manipulate the markers. After the second time period, a final group forecast is calculated based on the data collected during the first and second time periods.

Abstract: Systems and methods for computer-moderated collaboration, communication, and collective intelligence among a large population of human participants using a plurality of networked computing devices. This includes systems and methods for sending and presenting a query to a plurality of participants, each participant using a networked computing device, the query describing a question to be collaboratively answered by the population of human participants. A plurality of unique overlapping sub-populations of participants are determined by the server. Unique overlapping subpopulations are used to propagate information across the full population of human participants, facilitating collaboration, communication, and collective intelligence.

Abstract: Systems and methods for amplifying the accuracy of group forecasts and insights through interactive behavioral polling with perturbation analysis. During a first time period the system collects behavioral data of the user interaction with the dynamic user interface and a first displayed prompt, and then performs a perturbation analysis using the data collected during the first time period. A perturbation stimulus is displayed to the user, and during a second time period the user may additionally interact with the dynamic interface during a second time period, during which the system collects behavioral data of the user interaction during the second time period. The system determines a prediction based on data collected during at least one of the time periods from each of a plurality of users.

Abstract: The present disclosure describes systems and methods for computer-moderated collaborative estimation among a population of human participants using a plurality of networked computing devices. A query (e.g., estimation prompt) may be presented to participants for collecting collaborative responses. The population of users may each set an initial estimation response to the prompt during an initial estimation time period, which is then followed by a collaborative estimation time period (during which all users are asked to produce an updated estimation response to the same prompt). A forbidden deadband region defines an area around each participant’s initial estimation that the participant must move their variable slider out of in order for their slider to register as part of the collaborative real-time process. In some embodiments, a participant is not shown initial estimation responses of other participants until the participant has moved their slider out of the forbidden deadband region.

Abstract: System and method for amplifying the accuracy of forecasts generated by software systems that harness the collective intelligence of human populations by curating optimized sub-populations through an intelligent selection process. Participants predict event outcomes and/or provide evaluations of their confidence in their predictions. The system determines a score wherein the alignment score indicates how well that participant's prediction aligns with the predictions given by the baseline population. Participants can then be selected from the population based on the participant alignment scores.

Abstract: System and method for amplifying the accuracy of forecasts generated by software systems that harness the collective intelligence of human populations by curating optimized sub-populations through an intelligent selection process. Participants predict event outcomes and/or provide evaluations of their confidence in their predictions. The system determines a score wherein the alignment score indicates how well that participant's prediction aligns with the predictions given by the baseline population. Participants can then be selected from the population based on the participant alignment scores.

Abstract: Systems and methods for amplifying the collective intelligence of networked human groups engaged in collaborative forecasting of future events having two possible outcomes. During a real-time session a computing device for each user displays a forecasting prompt and a dynamic user interface which includes a user-manipulatable marker moved by the user between a first limit and a second limit, where the position of the marker defines a forecasted probability of each possible outcome. The display also includes a first reward value and a second reward value, both of which are interactively responsive to the marker position. During a first time period, users manipulate the markers. After the first time period, a perturbation stimulus is displayed. During a second time period, users again manipulate the markers. After the second time period, a final group forecast is calculated based on the data collected during the first and second time periods.

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.

Abstract: Systems and methods for amplifying the collective intelligence of networked human groups engaged in collaborative forecasting of future events having two possible outcomes. During a real-time session a computing device for each user displays a forecasting prompt and a dynamic user interface which includes a user-manipulatable marker moved by the user between a first limit and a second limit, where the position of the marker defines a forecasted probability of each possible outcome. The display also includes a first reward value and a second reward value, both of which are interactively responsive to the marker position. During a first time period, users manipulate the markers. After the first time period, a perturbation stimulus is displayed. During a second time period, users again manipulate the markers. After the second time period, a final group forecast is calculated based on the data collected during the first and second time periods.

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.

Abstract: Systems and methods for amplifying the accuracy of group forecasts and insights through interactive behavioral polling with perturbation analysis. During a first time period the system collects behavioral data of the user interaction with the dynamic user interface and a first displayed prompt, and then performs a perturbation analysis using the data collected during the first time period. A perturbation stimulus is displayed to the user, and during a second time period the user may additionally interact with the dynamic interface during a second time period, during which the system collects behavioral data of the user interaction during the second time period. The system determines a prediction based on data collected during at least one of the time periods from each of a plurality of users.

Abstract: Systems and methods for obtaining dynamic behavioral data from a plurality of users of a plurality of computing devices in response to a stimuli, and using the dynamic behavioral data to make an optimized forecast regarding the outcome of a future event. During a first time period the system collects behavioral data of the user interaction with the dynamic user interface and a first displayed prompt, and then performs a perturbation analysis using the data collected during the first time period. A perturbation stimulus is displayed to the user, and during a second time period the user may additionally interact with the dynamic interface during a second time period, during which the system collects behavioral data of the user interaction during the second time period. The system determines a prediction based on data collected during at least one of the time periods from each of a plurality of users.

Abstract: System and method amplifying the accuracy of forecasts generated by software systems that harness the collective intelligence of human populations by curating optimized sub-populations through an intelligent selection process. Participants predict event outcomes and/or provide evaluations of their confidence in their predictions. The system determines an outlier score for each participant based on the participant's responses and the relation of the participant's responses to the predictions of the population as a whole. Participants can then be selected from the population based on the participant outlier scores.

Abstract: System and method for amplifying the accuracy of forecasts generated by software systems that harness the collective intelligence of human populations by curating optimized sub-populations through an intelligent selection process. Participants predict event outcomes and/or provide evaluations of their confidence in their predictions. The system determines a score wherein the alignment score indicates how well that participant's prediction aligns with the predictions given by the baseline population. Participants can then be selected from the population based on the participant alignment scores.

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.

Abstract: Systems and methods for amplifying the collective intelligence of networked human groups engaged in collaborative forecasting of future events having two possible outcomes. During a real-time session a computing device for each user displays a forecasting prompt and a dynamic user interface which includes a user-manipulatable marker moved by the user between a first limit and a second limit, where the position of the marker defines a forecasted probability of each possible outcome. The display also includes a first reward value and a second reward value, both of which are interactively responsive to the marker position. During a first time period, users manipulate the markers. After the first time period, a perturbation stimulus is displayed. During a second time period, users again manipulate the markers. After the second time period, a final group forecast is calculated based on the data collected during the first and second time periods.

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.

Abstract: Systems and methods for eliciting from a user a probabilistic indication of the likelihood of two possible outcomes of a future event. During a session a user manipulates a wager marker on a graphical user interface displayed on a display, where the wager marker is moveable between two limits. Probabilities for each of the two limits are determined based on the position of the marker. Values representing the probabilities are updated on the interface in real time.

Abstract: Systems and methods for eliciting from a user a probabilistic indication of the likelihood of two possible outcomes of a future event. During a session a user manipulates a wager marker on a graphical user interface displayed on a display, where the wager marker is moveable between two limits. Probabilities for each of the two limits are determined based on the position of the marker. Values representing the probabilities are updated on the interface in real time.

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.