> Assume it works perfectly accurately.
Well this is a silly assumption. Wake word false positives happen all the time. (“No Siri, I wasn’t talking to you…”)
> Assume it works perfectly accurately.
Well this is a silly assumption. Wake word false positives happen all the time. (“No Siri, I wasn’t talking to you…”)
Human wake word recognition isn't infallible, either. How often in your life did you respond because you thought somebody called your name and it wasn't actually the case?
I wrote that in to deter kinda-bad-faith responses, where someone tries to play at being an evil-genie, inserting unreasonable flaws into the gaps, like: "But what if it triggered all the time? On purpose!?"
The point is that ethical implementations do exist, and them working does not rely on anything close to perfection--so nitpicking that word isn't helpful.
Point taken. Let’s focus on the “ethical implementations do exist” part though. Let’s say a best possible implementation has 99% specificity. Then if it detects audio that has nothing to do with “LG” it mistakenly treats it as LG relevant 1% of the time. So if audio in my living room is 100x more likely to not be relevant for LG, then half of the audio data LG is receiving is not relevant. So what would an ethical specificity be? And what is actual state of the art?