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bradland t1_j6jgeoi wrote

Replying to you because this seems like a good injection point, but these comments aren't necessarily meant as a rebuttal to anything you said :)

There's definitely a larger scope to assess here, but it extends even beyond a basic analysis of call volume. The analysis of systems designed to make automated calls to emergency services not only requires assessment of false-report calls, but also an analysis of the positive-report calls, as well as outcomes.

Ultimately, the objective is to save lives. A small-to-moderate increase in false-report calls is acceptable if there is a significant increase in the number of positive-report calls that wouldn't have otherwise been made in time. That analysis is way more complicated than simply looking at call volume though. You need to know:

  • How many false report calls were placed.
  • How many positive-report calls were placed.
  • The percentage of the positive-report calls that were duplicates.
  • The temporal proximity of the duplicative calls.
  • The ultimate outcome of the positive-report calls.

Using this data (and likely more), you'd want to build a complete picture of the correlation between automated reports and the desired outcome: lives saved in cases where other options would have failed. For example, consider two scenarios:

Your tire blows while driving home from your shift that ended at 2am and you veer into a ditch. You're knocked out on impact, but your iPhone calls 911 and emergency services can tell where you are from the GPS coordinates transmitted by your phone. They arrive and find you badly injured, but are ultimately able to save your life.

Here, the automated call to 911 was critical, and because it was so late, and because you were in a ditch out of sight, the automated call clearly saved your life.

You are texting while driving and rear-end a car that has come to a stop in front of you. Your phone goes flying out of your hand as the airbag deploys and is out of reach. The automated call is made to 911, but four other people who saw the accident have also called in within 60 seconds of seeing the accident.

Here, the automated call was superfluous. There's no way for the device to know, but it results in an extra call to 911 that was unecessary.

There will always be a cost associated with emergency response. It will also be impossible to optimize any automated system to achieve a 0% false-report rate, but that's not a license to be cavalier with the approach taken.

The iPhone isn't the only device designed to make automated calls to emergency services. For example, seniors who are at risk for falls will often buy a device with a remote that they wear around their neck or on their wrist that will call emergency services when a button is pressed.

These systems don't call 911 directly though. Instead, they call a call center. The call center agent answers and inquires about the individual's status. If the person is unable to respond, the agent initiates the pass through call to 911. If the person is able to respond, they assess whether emergency services are needed.

The systems work this way because 911 operators around the world are often short-staffed and cannot handle a deluge of false-report calls. As the number of iPhones in use grows, Apple will be forced to make closer evaluations of the usage data to determine what changes are required. I'd be surprised if this isn't a net positive for public safety though. It's just going to require some tweaks.

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Sp3llbind3r t1_j6mbdbk wrote

I think the point you are missing is that it‘s not just the call center.

If an ambulance or a fire brigade goes out, those are occupied until they found out it was a false call. And that is way worse, because they will not be at an other place where they would be needed, someone could die because of that.

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Drachefly t1_j6n33xo wrote

That seems like a part of the analysis they said would have to be done, so it's merely something they didn't mention, rather than actually missing.

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ConciselyVerbose t1_j6p3jlu wrote

Let’s say, hypothetically, that it was as bad as 50% false calls, 50% calls that wouldn’t have been made, and that every false call is missing a real call. That’s break even. That means 1 person loses access to emergency services and 1 person gains.

Any better than that and you’re helping more people than you hurt. Obviously the ideal is perfection, and not having any false calls, especially ones that take resources from real people. But it doesn’t take amazing accuracy to improve the net outcome.

If you get data that they’re more likely to be incorrect than a normal call, you can change your prioritization to prioritize a human speaking. Apple can continue to improve their accuracy to minimize false positives. But those improvements are from a situation that’s already better than it not existing.

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