Crowd think is an omnipresent problem. You want a rational decision, not a popular one. TruthSift lays out a rational plan and the proofs for and challenges against. Crowd think occurs because crowds jump to conclusions based on arguments with appealing images and story-lines, even when there are holes in the reasoning. The first appealing idea gains a following and crowds out others. Dissenters are dissuaded from raising their objections, even when they are valid, by unpopularity, and even when they raise them, they can't make themselves heard above the flow. TruthSift allows the dissenters with rational arguments to attach them exactly where they apply, and shows the consequences for the overall conclusion. Check out the results of some of the diagrams on TruthSift so far. We expect to reveal a staggering level of crowd think afflicting society.
Big organizations have various additional systemic problems. Only good news tends to flow upwards, causing severe management problems. "Information Flow in Fisheries Management: Systemic Distortion within Agency Hierarchies" Kiira Siitaria, Jim Martinb & William W. Taylor http://dx.doi.org/10.1080/03632415.2014.915814 Even scientists are confused about what the scientific literature says because of citation bias. S. A. Greenberg, "How citation distortions create unfounded authority: analysis of a citation network", BMJ 2009;339:b2680 http://www.bmj.com/content/339/bmj.b2680.full
Last Updated: 07 Dec 2018
All your members can have a distinct log-in associated with their name, but you can support an anonymous login as well so that members can make points they may not be willing to in meetings. The rationality or not of the point will be transparent on the diagram. You can compensate members who make good points under their own name.
Last Updated: 07 Dec 2018
TruthSift supports the rapid construction (and criticism and/or improvement) of sophisticated probabilistic models.
When Probability Mode is turned on for a diagram in the Settings panel (or if it has previously been turned on and saved) TruthSift estimates the probability of each statement, marginalizing over all probability parameters in the statements of the diagram, and over probabilities in Test statements. Test statements may be of the form:
a reported observation would have likelihood LET of happening if the target statement were true, and likelihood LEF of happening if the target statement were false.
This supports the rapid construction of
We have recently issued a new more user-friendly truthsift, which is what you are looking at, and in the process we dropped the probability graphs until we perfect this one. However we are planning to bring them back.