Is It True That Cellphones Can Eavesdrop On Our Chats Or Chats? Here's The Explanation

Targeted Advertising Illustrations (Glints)

JAKARTA - Have you ever talked about a certain product with your friends via chat, then found an advertisement for that product on social media or websites? If you have, you must have also pondered whether cell phones can 'eavesdrop' on conversations?

Of course it is not a coincidence if we see the advertisement of the product that has just been discussed. But, that doesn't mean the phone is really 'listening' to your chats. In fact, it is not necessary. The reason is, there is a possibility that you yourself have provided all the information needed by the cellphone to display ads.

So that you can be clear about this phenomenon, the VOI team has compiled from Science Alert the ability to 'eavesdrop' on mobile phones and targeted ads. Here is the description.

Can HP Eavesdrop?

Most mobile phone users, including those of us in Indonesia, have access to personal information on a number of websites and applications. This access is obtained when we give permission for some information, or allow 'cookies' to track our online activities.

The so-called 'first party cookies' enable the website to remember certain information regarding our interactions on the site. For example, login cookies allow you to store login information, so you don't have to bother re-typing your ID or password when you want to access it again at another time.

Meanwhile, third party cookies, created by outside (third) parties from the platform or site that you open. Usually, what is meant by third parties such as marketing companies that work with certain sites or applications.

Third parties generally collect user data through advertisements in the form of pop-ups or cookies that you consent to. Generally you are asked to tap on the 'Agree' or 'OK' button on the page that suddenly appears fulfilling smoothly.

From these activities, advertisers can design a picture of the user's life; e.g. routines, wants, and needs.

This advertising company always takes measurements to determine the level of popularity of the advertised product. And take into account more detailed variables such as age, gender, height, weight, occupation, and hobbies.

By classifying the information they have, advertisers can improve their recommendation algorithm. It uses a mechanism called System-to-Target Recommendations to generate the right ads for the right consumers.

Behind-the-scenes Computing Performance

There are a number of machine learning-based techniques from Artificial Intelligence technology that assist the system in sorting and analyzing user data. Such as clustering, classification, association, and Reinforcement Learning (RL) techniques.

An RL agent can train itself based on the feedback it gets during user interactions. The concept of this method is similar to that of a child who learns to repeat a certain activity if he gets a reward.

By viewing or tapping the 'Like' button on a social media post, you also send a gift signal to an RL agent confirming that you are interested in the post – or perhaps interested in the account that uploaded it.

That is, messages sent to RL agents relate to personal interests and preferences.

For example, you click the 'Like' button on a post about 'Focus' on a social media platform. The system will also start sending ads from companies that offer related products or content.