There’s a sort of built-in compensation for “response rates” or “perception rates” - in my industry we trend customer complaints and act according to the data we receive, but we also know that for every complaint we receive there are typically 30 similar events that go unreported. We also know that certain “responders” are outliers and will report every single instance they experience (and sometimes embellish and create additional instances for dramatic effect) but these are exceedingly rare and usually “adjusted” to normal responder levels once identified.
Now, when people create AI agents to file the complaints for them… that’s a new level of response rates. 25 years ago I came close to doing this for airport flyover noise complaints - our local (international) airport had an obscure portal for local residents to complain when they were bothered by jet flyovers - and our neighborhood would get dozens of events per month where the noise was so loud you couldn’t hear the other side of a phone call INSIDE your house with the windows shut. Thousands of homes were impacted by this, often 4 or 5 times in a row within an hour or two. But, the complaint channel was so obscure and the reporting process inconvenient enough that very few complaints were recorded, and they loved to point out that 40% of their complaints came from a single resident. Smart phones weren’t a widespread thing yet, if they were I would have “made an app for that” where anytime you were “impacted” by a jet flyover all you would have to do is pull out your phone and tap the app to file a report. (I considered developing it for Palm Pilot, but I doubt even 10 residents would have carried Palm Pilots for the purpose of filing reports…) If we got a couple hundred residents across the neighborhood reporting even 10% of the troublesome flyovers, we might have changed the conversation - as it was the airport used the lack of complaints to justify no change in flight patterns.
There’s a sort of built-in compensation for “response rates” or “perception rates” - in my industry we trend customer complaints and act according to the data we receive, but we also know that for every complaint we receive there are typically 30 similar events that go unreported. We also know that certain “responders” are outliers and will report every single instance they experience (and sometimes embellish and create additional instances for dramatic effect) but these are exceedingly rare and usually “adjusted” to normal responder levels once identified.
Now, when people create AI agents to file the complaints for them… that’s a new level of response rates. 25 years ago I came close to doing this for airport flyover noise complaints - our local (international) airport had an obscure portal for local residents to complain when they were bothered by jet flyovers - and our neighborhood would get dozens of events per month where the noise was so loud you couldn’t hear the other side of a phone call INSIDE your house with the windows shut. Thousands of homes were impacted by this, often 4 or 5 times in a row within an hour or two. But, the complaint channel was so obscure and the reporting process inconvenient enough that very few complaints were recorded, and they loved to point out that 40% of their complaints came from a single resident. Smart phones weren’t a widespread thing yet, if they were I would have “made an app for that” where anytime you were “impacted” by a jet flyover all you would have to do is pull out your phone and tap the app to file a report. (I considered developing it for Palm Pilot, but I doubt even 10 residents would have carried Palm Pilots for the purpose of filing reports…) If we got a couple hundred residents across the neighborhood reporting even 10% of the troublesome flyovers, we might have changed the conversation - as it was the airport used the lack of complaints to justify no change in flight patterns.