Browsing by Author "Ahmad, Mian"

Ambient Intelligence (AmI) was a vision intended to help humans in their day to day life. The AmI environment works by using different technologies, such as ubiquitous computers, networks, sensors and Machine Learning (ML) or Artificial Intelligence (AI). These technologies in AmI environment brings many benefits to the organizations to be used at workplaces to increase the productivity of employees, for example, using AmI technologies to make automated Human Resources decisions. However, using technologies associated with the AmI carries different privacy and data protection issues of the employees. In the European Union (EU), currently, the legislation that regulates the data protection of EU data subjects is the General Data Protection Regulation (GDPR). The GDPR replaced the Data Protection Directive (DPD) and increased the protection and rights of the individuals within the EU and EEA. To increase the level of protection the GDPR made changes to the fundamental principles of the data protection, including the principles of lawfulness and transparency. This led to the research question of this thesis i.e. Does AmI’s environments and its technologies are compatible with the GDPR’s principles of lawfulness and transparency at workplaces? In order to analyze the compatibility issues of the GDPR’s principles of the lawfulness and transparency with AmI technologies, this thesis used three different scenarios as case studies at workplaces. The conclusion is that, since the GDPR have elevated the requirements of lawfulness of processing and transparency, the consequences are that, the employers or organizations using AmI technologies or environments for employee’s productivity might not be able to fulfil the new conditions. As a result of this incompatibility between the GDPR’s principle of lawfulness and transparency and AmI technologies at workplaces, will possibly limit the employers to embrace technology at their workplaces. Finally, such demanding data protection rules will result in the trade-off between innovation and the right to data protection at workplaces.