Introduction: The importance of personal data protection in the digital age

The protection of personal data is extremely important for work and play in the digital environment. The ubiquitous use of information and communication technologies results in a constant flow of data and the transformation of social action into online quantified data that allows for real-time tracking and predictive analysis (Mayer-Schoenberger and Cukier, 2013). Many digital services seem free of charge to the users, but they are financed through the commodification of personal data, which has become a common business model for digital companies. Data is a regular currency for users to pay for ‘free’ services. As van Dijck (2014) remarked, this has become a trade-off nestled into the comfort zone of most people. This helps to fuel what Zuboff (2019) has defined as ‘surveillance capitalism’, a new economic industry deeply rooted in our society, which exploits users’ data to predict and control human behaviour.

With the development of greater computing power, huge amounts of data are collected and processed to obtain useful information and accurate profiles of individuals. In addition, the Internet of Things – the installation of sensors in a wide variety of objects interconnected through the Internet where the objects receive and send information autonomously – and the use of artificial intelligence will significantly increase the trend of personal data collection.

There are huge advantages to these technologies. For example, they can lead to better medical treatments, more efficient public transport systems, and better-managed stocks for companies. However, there is also a dark side to these advancements: there is a large amount of personal data at the disposal of governments and private businesses. Having access to this information consolidates power in the hands of these actors. This information has an enormous impact on the workplace, because all these data could be used to streamline procedures and assess productivity, but they can also be essential to the hiring or even the firing process, when they become automated (Jee, 2019). Cases have been reported in Japan in which companies analyse the data of their workers (including from their social networks) through algorithms to calculate the probability that they will steal from the business. Data are also used to analyse if employees are likely to share confidential information outside the company or to behave inappropriately at work (Fitzpatrick, 2015).