As part of a small project I’m working on, I need to have at least a rough description of how a given number of decibans translates into a subjective level of confidence, described in a way that can be understood by people who’ve never come across the idea before.
Some previous discussion has involved the practical maximum number of decibans, that imaginary and complex decibans aren’t relevant here, a quick reference table, and another reference table.
Here’s my first attempt an an approach: list some of the more memorable numbers of decibans, and give a rough description of that confidence level (being applied to identity verification, where possible). I’m open to any alternate approaches, and/or ways to improve this one.
While people tend to be very bad at assigning accurate confidence levels (eg, when people claim to be 90% sure of something, they’re often wrong 50% of the time), their initial estimates of their confidence levels can be used as the inputs for more sophisticated Bayesian algorithms. Until such time as more accurate estimates are available, here are some possible sample confidence levels:
0 decibans: 50%: You’re not sure whether the last digit of the phone number is a 3 or a 5.
1 decibans: 55% Just slightly more likely than not; a business card handed to you by a stranger.
Up to 10 decibans: to 90%: Someone you’ve chatted to for an evening.
Up to 20 decibans: to 99%: A distant acquaintance, who you talk to once a year.
Up to 30 decibans: to 99.9%: A co-worker who might have been re-organized into a new email since you last heard from them.
Up to 40 decibans: to 99.99%: A family member, who you might accidentally have mis-spelled the email address of.
Around 100 decibans: Your own personal information, closely checked. (There’s still a theoretical chance that you’re wrong, just as there’s a theoretical chance that you’re the star of something like the Truman Show.)
127 decibans: Data which relies on yourself alone, thoroughly re-checked and confirmed by others.
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