The post's arguments can basically be summed up in three categories: 1) "Doing this wouldn't be technically feasible or would require a technical effort wildly out of proportion" 2) "There are lots of psychological biases that lead people to believe something like this happened even if it didn't actually happen" 3) "Apple is such a nice and honest company, they would never do such a thing..." As for 1), there is enou…
Did that tech exist prior to 2017 when this conspiracy theory was already widely circulating?
Absolutely caught red handed - but I dont think Apple paid out 100m because "eh its easier this way".
If you look at the court filings, the only part where they were "caught red handed" was that they knew they were recording audio for inadvertent activations, but didn't take steps to stop it. There's remotely close to proving that they were using it for advertising.
Every time I read some technical description about why this isn't happening, the technical description seems convincing. However... A friend tested the theory a few years ago. He doesn't own a swimming pool, doesn't want to, and has never expressed any desire to. He put his and his wife's phone on the table and said to the wife (loudly), "Why don't we look into pool fencing?". She agreed with him. Shortly after, on b…
Think about what this implies. If your phone is listening, it’s listening all the time, right? So like 12-18 hours of continuous audio every day. That’s a lot of ad triggers. Way too many to actually be served with ads during your browsing time, which is a strict subset of your total audible proximity to your phone (plus ad inventory is a strict subset of what you view on your phone). So how does the phone + ad netwo…
The system knows to serve you ads about the new topic because it's new. You're already getting ads for the stuff you're normally talking about. The new topic stands out easily.
It doesn't have to be your phone. Could be your TV or any other device.
Most importantly there's just patterns of behavior. Companies are absolutely desperate for every scrap of data they can get on you. Why would they not capture audio from your mic?
Your voice is unique and can be fingerprinted to ID you (see Alexa devices). Add in things like positive sentiment analysis, changes in vocal inflection/intonation and context surrounding spoken products like purchase inference/intent and you can probably triangulate a threshold for showing products with high likelihood of purchasing intent. Really smart people have been working on these things at Google for decades…
I guess my question to this is, what are the estimates on energy required to do this on a continuous timeframe?
Embedded Audio ML engineer here (albeit mostly outside of speech). A modern MEMS microphone uses typically 0.8 mA in full performance mode at 1.8V. Doing basic voice activity detection, which is the first step of a continuous listening pipeline, can be done in under 1 mA. Doing basic keyword spotting is likey doable in 10 mA. But this is only done on the part that the voice activity module triggered on. Lets say that is 4 hours per day. Then basic speech recognition, for buying phrases and categorization, would maybe cost 100 mA. But say only 10% of the 4 hours = 0.4 hours have keywords triggered.
That would give a total power budget of (1.824)+(104)+(100*0.4) = 123 mAh per day. A typical mobile phone battery is 4000 mAh. People do not expect it to last many days anymore... So I would say that this is a actually in the feasible range. And this is before considering the very latest in low power hardware. Like MEMS mics with 0.3 mA power consumption or lower, MEMS microphones with built-in voice activity detection, or low power neural processing units (NPU) that some microcontrollers now have.
1) App stores the trailing two minutes of speech in memory. 2) If the app detects a consumption-related trigger word, the related conversation is flagged for transmission to the server. 3) Flagged audio block is converted to text. Consumption related verbs ("buy", "purchase", etc) are identified. The syntax of the sentence clearly indicates which noun is the target of a given consumption-related verb ("new car", "poo…
Where's the proof that this is happening? Lots of people run network traffic sniffers to see what apps are doing. Lots of people decompile apps. Lots of people at companies leak details of bad things they are doing. Why has nobody been able to demonstrate this beyond anecdotes about talking about swimming pools and then getting adverts for swimming pool stuff?
I don't know - where is the proof it's not? It's not like I can look at the source to the ad SDKs and figure out what they're doing.
It's much better and safer to assume they are than they're not, especially because I've seen many many results which indicate they are.
With what credibility does the author of this piece speak? Are they in all of the ad platforms on mobile/tablet?
I have nothing to do with ad tech, or selling mobile phones or anything like that.
I don't like seeing people fall for obvious conspiracy theories, and I have used my own deductive reasoning to decide that this is an untrue conspiracy theory.
Where's the proof that this is happening? Lots of people run network traffic sniffers to see what apps are doing. Lots of people decompile apps. Lots of people at companies leak details of bad things they are doing. Why has nobody been able to demonstrate this beyond anecdotes about talking about swimming pools and then getting adverts for swimming pool stuff?
I don't know - where is the proof it's not? It's not like I can look at the source to the ad SDKs and figure out what they're doing. It's much better and safer to assume they are than they're not, especially because I've seen many many results which indicate they are.
You may not be able to disassemble binaries or intercept network traffic but there are plenty of privacy researchers who can, and none of them have found anything.
Where's the proof that this is happening? Lots of people run network traffic sniffers to see what apps are doing. Lots of people decompile apps. Lots of people at companies leak details of bad things they are doing. Why has nobody been able to demonstrate this beyond anecdotes about talking about swimming pools and then getting adverts for swimming pool stuff?
I have a suspicion it’s not Facebook or Google listening in, but rather other third party apps. In fact it’s not even the third party apps but the libraries/frameworks they use to show ads.
Facebook Android app used to 10+ years ago I'm pretty sure
Every time I read some technical description about why this isn't happening, the technical description seems convincing. However... A friend tested the theory a few years ago. He doesn't own a swimming pool, doesn't want to, and has never expressed any desire to. He put his and his wife's phone on the table and said to the wife (loudly), "Why don't we look into pool fencing?". She agreed with him. Shortly after, on b…
Why did they pick a swimming pool? Did they see people in their area installing pools? I think that's often people's best guess, is that the "random" thing people use to test this actually isn't random and subconsciously they already had this topic seeded to them.
using multiple high value advertising targets would be best. like specific brands of mattresses or industrial equipment.