This data may sometimes be enough to know a lot about the user without having to listen to his conversations.
One of the most common ideas is the belief that the phone listens to conversations to show ads related to what the user is saying. But more sophisticated tracking mechanisms don’t necessarily need a microphone. For example, it can know how quickly the user scrolls pages, the network he is connected to, the way he accessed the content, and what applications and websites he interacts with.
When these signals are taken together, a relatively accurate profile can be built about his interests and the products that might catch his attention.
Phones and electronic devices have tools and sensors that can be used to link advertising activity to user behavior across various applications.
These tools differ between Android and iOS, as Apple’s system allows applications to request the user’s permission before accessing advertising tracking tools, while Android provides settings that allow the user to reset these tools.
On iPhone devices, the user can go to the privacy and security settings, then the Tracking section, and disable allowing applications to request tracking, in addition to reducing personalized ads.
The permissions granted by apps to access location, camera, or microphone provide a large amount of data.
While Maps may need location to perform its core function, location data can also be used for advertising purposes.
Some apps may request access to the camera for legitimate reasons, while images or information extracted from them may be used to analyze content and personalize ads.
But what’s even more worrying is that location isn’t always based on GPS alone. A device’s location can be inferred from nearby Wi-Fi networks, cell towers, and even Bluetooth devices.
Tracking technologies reach more sophisticated levels by using sensor data. The accelerometer sensor in the phone, for example, can provide information about how the device is used.
Research suggests that nuances in sensor data can be used to infer information about a user’s behavior, activity, and even some characteristics of their mood.
The way the phone is held or the movement while walking can also be analyzed to help identify the user. Even writing style may provide additional signals, such as writing speed, number of errors, and hesitation before entering certain words. (Erm News)
