Current pandemic phenomenon is changing the society and its economy. Governments and citizens are carrying out all control measures in order to reduce contagion risks. In this uncertain context, artificial intelligence algorithms and computerised information protocols have been successfully used to reduce contagion risks. For instance, Alibaba Research Development has experimented a new method for COVID-19 testing that implements artificial intelligence algorithms.

In such context, technology has been implemented to help to reduce contagion risks. In particular, it is important to track infected people in order to control virus spread. Subsequently, such contact tracing is a process that helps contacts to get care and treatment, and will prevent further transmission of the virus. Contact tracing is a monitoring process that can be divided in three main stages:

·      Contract Identification: Once an infected has been identified, his/her contacts are identified. After that, they will be asked about activities of the infected individual and its role around them and their life. Contacts can be anyone who has been in contact with an infected person.

·      Contact Listing: People considered to have contact with the infected individuals will be listed as contacts. Contacts should also be provided with a prevention plain in order to reduce risks and prevent further contagion. In some cases, quarantine or isolation is required for high-risk contacts, either at home, or in hospital.

·      Contact follow-up: Regular follow-up shall be implemented with all listed contacts.

In this scenario, individuals’ privacy protection is fundamental. In fact, digital contact tracing will probably fail unless governments build the right technology that respects user’s privacy. In particular, Contact Tracing apps might be repurposed to enable unwarranted discrimination and surveillance over society. Trust is the paramount element within the user-technology relationship and it is important that such important tool for reducing pandemic risks may be reconverted to enable large-scale of data collection.