The purpose of this article is to offer a view on different aspects related to privacy and big data management and how this is seen on our every daily activities.
17 applications on my iPhone have access to the camera. My concern comes because this access can be done with the application open or closed, in background mode. This makes it easier for them to sell private information to third parties or use it for purposes other than those stated.
Apple is offering an update to show when an app is accesing phone sensors to make owner aware at least.
Our photos have a significant amount of metadata embedded that could be read by any application that has access to our galleries (geolocation, time, ...). This combines with the artificial vision techniques which are able to extract even more information from the photographs.
How is this going to evolve with IoT and 5G?
Any document, photograph, sound file, email contains additional information about the place where it was taken, time, creator and many other data can be embedded in these objects.
Those ones could be connected to our internet router and have access to internet to share the contents with companies out from European Union and even worse, with an upgrade policy than could make then vulnerable to a number of attacks.
The reasons for concern are clear, our devices can profile our habits, routes, who we have been with or even involvement in documents that according to the content can put us in trouble.
5G networks will speed up the capacity to share this information in real-time and the amount of data that could be traceable due to the increase of network bandwith.
Moreover, to avoid cloud servers overload, the Fog computing (also known as Edge computing) will support aggregating and operating over the data collected by devices to only send a very valuable portion of the data to the final servers.
A commercial usage
Marketing campaigns optimisation go with using user data for segmentation and knowledge about behavior helps showing the contents at the most relevant moments for the users, convincing them about purchase actions or about opinion, interest about a brand.
In the case of Cambridge Analytica, they used the information collected by Facebook, to know the citizens (more than 50 million) and show them specific contents to change their voting opinion. Some relevant information managed by Facebook at first glance:
0.- Email address
1.- profile photo
2.- Place of residence
3.- Place of birth
4.- Ideological and religious beliefs (in the North American market it is possible to segment whether liberals or democrats are buying ads; in Spain they are not)
7.- Marital status and sentimental situation as well as if you have children
8.- Interests (in men, women...)
9.- Company in which you work
10.- History of worked companies
11.- Training (school, college, university...)
12.- Professional skills
13.- From there, it crosses contact data to feed the profile automatically
14 .- Geolocation, since if accessed primarily from a mobile Facebook knows if you have activated the GPS where you are at all times
15.- The algorithm also crosses other parameters such as important events in your country, based on your "likes" it returns adaptive advertising and shows you some publications or others
16 .- It does not stay there alone, since all the photographs that are uploaded, many of them provide additional information, are passed through an image recognition system and many aspects are known (place of the photo, people who are in it ...)
17.- Of course, Facebook knows the phone you have and the apps you have (WhatsApp, Instagram, AirBnB...)
Data points are a discrete unit of information that is derived from a measurement by an app or is investigated by algorithms or bots.
The data broker is a company that collects information itself or buys it from other companies.
According to a ELPAIS article, we have an example of personal data at 7.5 cents (https://elpais.com/tecnologia/2017/05/03/actualidad/1493835469_309268.html).
There are other companies like Experian, which create models on the data they buy from data brokers and sell to access the results of those models for insurance or banking evaluation. ExactData.com is the example of data brokers quoted in this article. There are about 50 data brokers in Europe.
But we need to massively use apps to collect data
Systems based on variable rewards are based on Skinner's experiments in the 1950s on the effects of random rewards on certain actions. In psychology, it explains the addiction of gamblers to slot machines due to their action on a neurotransmitter: dopamine.
The key to increasing dopamine and encouraging behavior is uncertainty. Examples of the application of the results of these studies are the book Hooked: How to Build Habit-Forming Products.
Notification systems such as the one that once showed the Blackberry with a dot, a vibration and a sound, the reception of a message, already made it one of the most used phones for the work environment.
Those same notifications are used at the browser or mobile level for all applications today. This has increased the engagement time of a user to the mobile, trying to anticipate actions that happen in their favorite social networks.
Within the application design, there are several elements that simulate the leverage of Skinner's experiments:
- Pull to refresh: touch to refresh and see if there is something new.
- Infinite scroll: that makes us read more and it is more expensive to leave the application.
- Autoplay from Youtube or Netfix.
- Algorithms: that constantly offer us information related to our interests.
As for mechanics in the applications, there are systems such as those used by running applications:
- Badges, trophies, awards, levels
- Unlocking functionality
- Priority access for early adopters
- Likes, views and followers (how many visits your profile has, statistics)
- Intrinsic rewards: A Harvard study showed that sharing information with each other or even our thoughts and opinions with others produces even more activity in the reward region if we do it publicly than even if we do it privately.
This coupled with the immediacy that gets the LTE/4G or broadband internet, increased on a 5G environment.
Beyond the commercial usage
The Chinese social credit system is based on a system that indiscriminately and without permission, the information collected from all citizens by different means: artificial vision in surveillance cameras, spying through access to Internet access records and cell phone use. This puts the citizen in different categories of permissions. Specifically, 169 people lost the right to travel inside and outside the country due to low scores in 2018 (https://www.scmp.com/news/china/policies-politics/article/2148980/china-names-169-people-banned-taking-flights-or-trains).
This constitutes a direct attack on the freedoms and individual rights of its citizens, as a form of segregation against potential threats to official doctrines.