Is there a "catch" to wisdom of the crowd methods like Flashcast?
Published Aug 12, 2019 by Ben Schachter
We’ve written about the years of research and recognition surrounding collective intelligence or “wisdom of the crowds” before. Especially when it comes to the accuracy of crowdsourcing predictions like in Flashcast, the methodology is tried and true.
More recently, an article in HBR makes this point, refuting skepticism that the wisdom of the crowd is susceptible to “groupthink” -- when people’s decisions are influenced by the opinions of those around them. It turns out that the wisdom of the crowds is not nearly that fragile.
There is one catch. The article explains that “groupthink” has a negative impact on crowdsourcing accuracy, typically, in “centralized” networks, where the flow of information is centered around a few “opinion leaders”. The good news is that if your goal in using Flashcast is to get quality predictions from your audiences in meetings, conferences, or the classroom -- the features make it so you don’t need to worry about much of this.
How does Flashcast solve the “centralized” network problem?
The solution to a “centralized” network is to create an environment in which each person’s voice is heard or seen equally (a “decentralized” network). This type of environment prevents one or two voices from having a disproportionate impact on the predictions of others.
Here’s how we believe Flashcast creates equality and promotes a decentralized network:
- Anonymous predictions - Predictions on Flashcast are collected anonymously. Participants are asked to enter a username of their choice to submit their prediction to keep identities private.
- Just-in-time response - Because participants will generally not take more than a few minutes to submit their prediction in Flashcast, there is little opportunity for any external persuasion by a dominant voice.
- Independent critical thinking - Even if the person sitting next to you as a Flashcast participant is vocalizing their opinion to you, anonymity in the app supports free thinking, and promotes independent analysis in asking you to quantify your belief.
- Mobile application - Audience participants will need a mobile phone or device to use the app, which also creates a separate, independent space.
Beware of when Flashcast can’t save you
Although Flashcast assists in creating the right environment for you to get the most from your crowd, be careful of two barriers beyond the app that are in your (the presenter’s) control.
As the person in front of the room, you can be an “opinion leader” who influences your audiences’ prediction, even if not intentionally.
If you have framed an issue you’re asking for predictions on in a biased way, or provided the audience with limited information on the topic when they already may not have much context, then Flashcast results are likely to reflect that. Getting accurate results starts with the information provided to accompany the presentation. By making a conscious effort when creating and introducing the Flashcast, presenters can make sure they’re not the problem.
How you frame a sensitive Flashcast question matters -- audiences will react to emotionally or politically charged content.
Crowdsourced results are more resistant to “cognitive biases” than once thought. But even so, asking emotionally and politically charged questions does not lend itself to the most accurate results. While it’s unrealistic and unproductive to avoid these questions altogether, always consider if you are framing a question as objectively as possible to minimize the influence of emotion in a response.
Ultimately, new research is on our side, proving yet again that crowdsourcing methods like Flashcast are nearly bulletproof for obtaining insightful and highly intelligent results. But, it’s still important to understand nuances that enhance the experience. When you know the limits of crowdsourcing practices, you can get the best results from your Flashcast session, especially if one of your main objectives is accurate real-time crowd predictions.
By Vanessa Pineda and Ben Schachter
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