The overall goal of PROTECT is to grow a new generation of 14 Early Stage Researchers (ESRs), as PhDs graduated via a unique multidisciplinary, inter-sectoral and international European Training Network. The network will investigate the protection of rights and interests of individuals and groups impacted by the continuous large-scale analysis of personal data, while still enabling the economy and society to benefit from rapid innovation in digital applications that collect and use this data. The PROTECT ESRs each implement a Personal Career Development Plan (PCDP) that enables them to integrate and apply arguments, analyses and tools from across the fields of law, ethics and knowledge engineering, so that they can take on leading research and governance roles within digital services industry and public policy sectors to address challenges of data protection, data ethics and data governance.
The rate of technological innovation, now accelerated by big data and machine learning, increasingly outpaces public policy debate and the development of new regulation for the protection of personal data. This comes as the scale and social impact of data analysis is rapidly increasing. Tech companies, especially SMEs, face complex legal and ethical implications resulting from the collection of personal data from users. The pace of change and its complex technical nature serves to overload individuals and enterprises in considering the impact of use of their personal information, especially when this use also delivers attractive personalisation of services. PROTECT ESRs will develop new ways of empowering users of digital services, individually and collectively, to understand the risks they take with their rights and interests when they go online.
PROTECT has successfully started its ESRs on career paths where they are able to navigate the complex legal and ethical challenges of fast moving data-driven AI technologies in the new era of digital regulation that the EU has entered over the duration of the project. This is evidenced via the collaborative and individual peer review publications generated and by the collaborative development of open semantic models for capturing and comparing issues around group data protection in data spaces, ethical assessment of AI and data processing technologies and AI and data processing risk assessments. It is also evidenced through the impact already achieved through dissemination targeting standardisation and policy development activities, including: mapping of the AI Act to international standards, open semantic models to GDPR compliance and management of data sharing; data protection policy and AI ethics policy.
