Background and Vision

Background and goals
We are inviting contributions to this Summer School from students who are at the stage of preparing a master or a PhD thesis as well as young researchers and practitioners. The school is interactive in character, and is composed of plenary lectures and workshops based around Master/PhD students’ presentations. The principle is to encourage young academic and industry entrants to the privacy and identity management world to share their own ideas, build up a collegial relationship with others, gain experience in making presentations, and potentially publish a paper through the resulting book proceedings.

This Summer School is a joint effort between the IFIP Working Groups 9.2, 9.6/11.7, 11.6, and Special Interest Group 9.2.2 and different European and national research projects. The 2017 IFIP Summer School will bring together junior and senior researchers and practitioners from multiple disciplines to discuss important questions concerning privacy and identity management and related issues in a global environment subject to change. This Summer School is not a “taught course”: it does enable, however, students to gain credit points for presenting and attending, and their paper to be considered as a candidate for a Best Paper award.

Vision of the 2018 School

The world is in the throes of a revolution of big data and machine learning, affecting many technologies and society at large. Digital data is an essential resource for economic growth, competitiveness, innovation, job creation and societal progress in general. To be exploited, data needs to flow across borders and sectors, should be smartly aggregated and processed, and should be accessible and reusable by most stakeholders. A key aspect of these developments is the harvesting, storage, processing, (re)use and commodification of (personal) data, based on the ‘datafication’ in all areas of life. There is a need to critically assess from interdisciplinary perspective what this means for the (dis)empowerment of users/citizens/consumers as (not) being in control regarding identity, security, privacy and publicness. A lot of the data collection and processing happens in an opaque way behind the scenes. In particular the role of algorithms and their impact on selection is often opaque as (commercial) platforms tend to treat them as trade secrets, not open for inspection or discussion. In that sense a big part of the reasoning and decisions behind selection is black-boxed. Given the proliferation of these type of algorithms – often based on machine learning – in many spheres of life (communication, mobility, employment, finance, etc.) scholars, policy makers and society at large is demanding more transparency, fairness and accountability regarding these selection mechanisms.
In order to safeguard public values like privacy and diversity in these systems we need to investigate how to make data processing transparent and meaningful for people and other stakeholders in society. This requires ex ante accountable and diverse algorithm design and ex post scrutinising and auditing algorithms, to mitigate and avoid negative social, ethical and economic consequences for society (e.g. discrimination, social exclusion, disinformation, inequality,…). More broadly the question is also how society and citizens can take back control of these online platforms and ‘smart’ technologies. This requires efforts for data literacy by people but also inside private and public organisations. Data literacy refers to increasing awareness, building attitudes, enhancing capabilities and adjusting behaviour among users regarding (personal) data collection, processing and (re)use in the area of online platforms and digital technologies. It extends traditional media literacy by incorporating understandings of the material conditions and technological affordances of the proprietary control of personal data.

In addition to these technological and social interventions, also legal precautions are required. The European General Data Protection Regulation (GDPR) provides an overarching legislative framework that answers to the concerns regarding data protection. Simultaneously, a new Directive was adopted to protect personal data processed for the purpose of criminal law enforcement. While these legislative instruments define the “principles to be respected and enforced”, not a lot is said about the way in which these principles should be deployed technically in different industrial and societal sectors. Technological advances such as the use of open data, big data, algorithms, machine learning, blockchain and sensor development in the Internet of Everything are rapidly changing the societal landscape. Questions arise about who holds what data, and where and how that data may be used.  These advances challenge the way privacy and data protection should be provided, because current national regulatory mechanisms were not devised with these new technologies and possibilities in mind. What is also clear, from discussions in the general press, media and social media, there are also huge societal, social, and ethical concerns with regard to the implications of these emerging technologies both in theory and in their practical deployment.
Here, indeed, there lies a major scientific and social challenge: how to guarantee, in a homogeneous way, the preservation of privacy and other human rights in a completely heterogeneous and cross-sectoral world, without impairing the potentialities of big data, algorithms and machine learning. These questions, as well as many other current and general research issues surrounding privacy and identity management, will all be addressed by the 2018 IFIP Summer School on Privacy and Identity Management.

Further useful information

Credit Points
Students who actively participate, in particular those who present a paper, can receive a course certificate which awards 3 ECTS points at the PhD level. Students, whose papers are already at submission full length and of sufficient quality for a PhD seminar thesis can receive a course certificate which awards 6 ECTS points at the PhD level. Student attendees who do not present a paper will receive a course certificate, which awards 1.5 ECTS points at the PhD level. The certificate can state the topic of the paper contribution so as to demonstrate its relationship (or otherwise) to the student’s master or PhD thesis.

Best Student Paper Award
Every year, at the IFIP Summer School, a paper is chosen for the Best Paper Student Award. The award is made at the School, and this award success made public.
Papers written solely or primarily by students and presented by a student at the Summer School are eligible for this award. If the paper is co-authored with senior researchers, the authors have to state that the main work and contributions can be clearly attributed to the student author(s). The award will be selected based on the quality of the paper and the oral presentation.