Eye tracking technology – User profiling and privacy concerns


eye tracking

Staring is like clicking.

Eye tracking technology is starting to be used in virtual reality (VR) systems and it could be used in smartphones or notebooks in the near future.

If you are a smart web user, you think twice before clicking on a link with an alluring bait. But what if you just linger on that link with your eyes?

By clicking on an advertisement, your ad provider acquires your interests and creates a profile on you. So it will send you other relevant commercials and potentially sell those information to commercial partners. But eye tracking adds subtle capabilities to marketing profiling.

For example, you may reveal your sexual preferences, a sensitive information, just by looking a web page. By measuring the time you stare at persons of each gender or the degree of your pupils dilation, you are inadvertently revealing that information.

It’s easy to avoid clicking on a commercial if you recognize it, but avoiding to look at an image is another story. It’s about your instinct, something you cannot and don’t want to give up.

In the same way, your eye movements may reveal sensitive information about your health status, like alcohol and drug use or some diseases.

Furthermore, eye tracking systems could be used everywhere, for example integrated within billboards, to gather people preferences about products, color variants, body shapes, facial expressions and so on. But hopefully, in such cases, they cannot be matched with your identity.

Commercials may also be easily embedded in a free VR game. If you are required to log in to play that game, then you are profiled. The same holds true for other VR applications like, for example, roaming in a virtual urban scenario with some strategically placed advertisements.

We should be prepared to this next privacy invasion even though often we will be aware of that. Better to pay attention and when those boring privacy policies are available, don’t skip reading them to be aware of the consequences of using such products and services.

IoT meets Big Data and Artificial Intelligence

data streamIoT is the inter-networking of any physical device, while Big Data refers to storage and analysis of large amounts of data.

So, every time an IoT device produces a lot of data, these two technologies meet. Artificial Intelligence algorithms can use that quantity of data to train algorithms and achieve an high efficiency.

An infrastructure may contain many IoT devices and the quantity of data that each of them produce may be huge.

To store and retrieve such amount of data, often in a constrained time frame, non-relational database are used. Those systems basically drop functionalities in favor of speed and flexibility.

Scenarios of convergence and sectors where those technologies can be used are countless: economy, finance, medicine, agriculture, robotics, traffic shaping in data networks and in transports, social networks, marketing, and so on.

For example, consider many meteorological buoys scattered on a wide area, each of them sending data at relatively high frequency. The amount of data collected over time will be huge and Big Data analysis may be used to improve weather forecasts and climate models.

Another example of IoT objects could be autonomous cars or robots. Many sensors are used to send data at a very fast pace to react to environment changes and to assess vehicle or robot position and dynamic status. Those data need to be analyzed in real-time. Big Data techniques are necessary to process an enormous quantity of data in fractions of a second and AI algorithms decide the next actions of the car or the robot.

Wearable sensors may be used to detect when you are walking, running, sitting or sleeping, measure your hearth rate or values of blood indicators. Those data can be analyzed to understand if and when your do physical exercise and what you eat and drink. So AI algorithms can be trained to suggest you to do some work out in your spare time or to improve your diet.

There’s a lot of talk and work about those subjects. Those technologies and algorithms will have a big impact in many aspects of our lives in the near future.

A new era for road transport is on the way

autonomous drivingThe world is approaching a revolution in road transport. There will be tremendous changes in many aspects:

  • autonomous driving
  • propulsion using clean energy sources
  • smart infrastructures and communication systems

Autonomous driving

Soon vehicles will be able to drive without human intervention. A increasing number of companies is investing in self-driving and in the related Artificial Intelligence (AI) algorithms, mostly automakers and technology providers.

But apart from technical difficulties, there are also legal and ethical problems. Lawmakers seem to gain awareness of this big change. For example, who is responsible in case of an accident? The owner, the human “emergency” driver (if any) or the producer? And also, if a vehicle cannot safely stop before hitting a pedestrian, should it choose to hit him anyway or steer and crash its passengers against a wall?

Especially in cities, cars will be more a public service than a private good because they could be requested on call instead of needing one constantly out of the door, waiting to be used. That will change people daily habits and family budget plannings.

Propulsion using clean energy sources

Electric cars are not a news but there are not so many on the roads. Now electricity storage is improving and that involves lower costs and shorter and less frequent recharges, so that electric cars will be more attractive.
Due to those improvements, also trucks are starting to use electricity for their propulsion.
Energy can be obtained from several sources but it is essential to get it in a clean way to fight pollution and global warming.

Smart infrastructures and communication systems

Self-driving associated with smart infrastructures and communication system will allow an overall control of traffic and emergency signalling. We will achieve rerouting because of a closed road or traffic congestion, optimization of traffic lights, statistics collection for future planning of public transport or new roads.

Let’s consider an unfortunate scenario. A car detects it just had an accident by reading peak values from its accelerometers. Immediately it sends an alert to the vehicle behind for an emergency brake. Then it scans the vital signs of the occupants and tries to verbally communicate with them. After this investigation phase, it may decide to call for help to a central system. That one in turn sends an ambulance and reroutes the traffic to avoid the accident area. The ambulance transmits its position along the way and the central system diverts again the traffic to free the path of the ambulance.

In the initial phase, manned and autonomous vehicles will coexist but when all vehicles will be autonomous, road infrastructures like streetlights and road signs will not be needed anymore, thus saving energy, raw materials and maintenance costs.

No more time and energy wasted searching for a parking place, because the car will know where one is available.

Without a driver, cars will be like small offices or rest rooms. Time spent in a car will be more useful than today. There will be advanced interfaces and entertainment systems.

The saying “It’s not about the destination;¬†it’s about the journey.” is going to be even more true.