[acomjean]

I like the idea, but the stakes are really high in downing. At some point you want it to be helpful, but not to be so good as to make the human lifegaurd not pay full attention. Machine learning might not be the way to go here..

It definitely in the realm of possibilities. They're starting to do the camera assist in the checkout product theft prevention.

http://www.stoplift.com/how-it-works/

[Retra]

As a non-lifeguard, I would rather have a machine than trust myself. So ideally, you would have both a lifeguard and another independent monitoring system for non-lifeguards. They could be fail-safes for each other.

[jsprogrammer]

Anthropic fallacy. It seems like you are assuming a human is or will always be better than another solution.

There may be solutions that are vastly superior to a human lifeguard.

[dogecoinbase]

They're pretty clearly not saying that no solution could be better than a human. They're saying that a solution which isn't as good as a human, combined with a human, could be worse than a human without the inadequate solution, which is true.

[yellowapple]

We have some pretty good machine learning tech out there, but I'd reckon we're quite a ways off from the proposed startup focusing on replacing lifeguards with computers even at spotting functionality, let alone the other functions necessary (retrieval, resuscitation iff actually necessary, etc.).

Sure, someday we'll have robots do everything for us. We're not quite there yet.

[jsprogrammer]

A rectangular pool with a flat bottom (probably accounts for the majority of pool volume world-wide) would be pretty easy to have full camera coverage over with minimal image distortion. Each object could be easily tracked for time underwater, depth, etc. (and expanded to track fine motion as well) Objects that stay near the bottom are suspect. The system could alert lifeguards to the exact location of a victim.

You could even have an auto-drain feature if you desired.

[yellowapple]

Right, but my point is that we're not quite at the point where a computer can reasonably process that much visual input, determine whether or not something is exhibiting the signs of drowning, and alert a lifeguard with a minimum of errors. False positives will lead to personnel confusion, and false negatives will lead to dead swimmers.

This isn't to mention that automation does encourage complacency. One of the primary reasons for the recent Malaysia Air jet disappearances according to investigations is an excessive reliance upon automated systems to fly planes, and insufficient knowledge of flying without such tools. I reckon a similar situation could be a real danger here as well (if not amplified considerably; most lifeguards (at least where I've lived) were usually highschool students doing it as an extracurricular/volunteer activity, summer job, etc., and teenagers aren't exactly known for having an above-average attention span).

[chucksmash]

> False positives will lead to personnel confusion

False positives can lead to death too. This article talks about alert fatigue that contributed to a fatal medication error at UCSF:

https://medium.com/backchannel/beware-of-the-robot-pharmacis...

I'd be wary of giving a lifeguard who might be straining to pay attention to n things an n+1th thing to pay attention to.

[yellowapple]

That's what I meant by "personnel confusion", yes. A.k.a. the "cried 'wolf'" effect; how can a lifeguard be expected to treat this alarm seriously when all the other ones have been false positives?