How to find consensus within a group
Focus groups and town hall sessions are familiar methods of conducting qualitative research that relies on consumers and stakeholders. Both methods are susceptible to shortcomings that include lack of participation or unwillingness to share in a group setting. They may also reflect bias and the halo effect, as well as reliance on the researcher to draw accurate conclusions from the group feedback. When using the Swarm AI® platform to generate insights from human groups, we are able to effectively counter these shortcomings. We also present results that are more comprehensive than the data collected from focus groups or town halls.
In contrast to surveys and polls, focus groups and town halls rely on small groups of participants. They bring with them their collective knowledge, beliefs, values and morals, but there is no requirement they share this information. Focus group participants can be influenced by the “group effect”, resulting in self-censoring and conforming behaviors. This is a result of the social situation created by the setting 1. The same social dynamic is found in town hall style sessions where strong personalities control the conversation and alter the opinions of others. Focus groups and town halls both provide a setting in which the halo effect can have undue influence. Research indicates other participants are unaware that their assessments have been altered 2. Swarms are able to maintain the benefits of focus groups and town halls while offsetting the disadvantages. Since participants engage in a virtual setting, they observe and react to the input of others, but in the absence of social pressures or halo effects.
Focus groups and town halls are dependent on moderators and observers to draw conclusions that summarize the opinions and beliefs articulated by participants. They are reliant on the willingness of each member to contribute to the discussion. Those who opt not to speak, regardless of their reason, will not have their opinions considered in the data collection. As qualitative research methods, the data produced by focus groups and town halls is subject to interpretation by the research team, who may bring their own bias into the evaluation.
In contrast, the Swarm AI® platform processes the user input without bias. It allows participants to interact in a virtual setting that removes social pressures; each participant’s contribution is measured. The platform is designed to identify consensus, an objective which is often impossible in focus groups or town halls. This consensus is provided with a probability ranking when making forecasts and a conviction measurement when asking for participant sentiment. These measurements cannot be provided by traditional methods and are a key differentiator of Swarm AI®.
Swarming is a unique and powerful method for harnessing the collective knowledge, wisdom, intuition, and insights of human groups. It enables diverse participants to quickly converge on optimized solutions with the support of real-time intelligence algorithms. While it’s tempting to compare the process to polls, surveys, and focus groups, the relationship is tenuous. Swarming provides participants equal opportunity to contribute in a real-time control system. It removes the social aspects that can hinder participation in focus groups or town halls. The Swarm® platform evokes more authentic sentiments from individuals as they act, react, and interact with other participants. It allows the group to discover those solutions that best represent their collective conviction.