Keynote Speeches

Svetlana Bodrunova photo

Social media studies and post-Soviet public spheres

Svetlana Bodrunova, St. Petersburg State University

In my talk, I will elaborate on the necessity of contextual knowledge in doing automated research on social media texts. Drawing on the examples of mixed-method research projects in social media and user-generated content, I will try to show how context played the role in developing the research designs. Also, I will draw attention to key societal cleavages that constitute the shared context of the post-Soviet states and shape our today’s assessment of quality of national public spheres and political discussion online.




Krishna P. Gummadi photo

Discrimination in Machine Decision Making

Krishna P. Gummadi, Max Planck Institute for Software Systems

Machine (data-driven learning-based) decision making is increasingly being used to assist or replace human decision making in a variety of domains ranging from banking (rating user credit) and recruiting (ranking applicants) to judiciary (profiling criminals) and journalism (recommending news-stories). Recently concerns have been raised about the potential for discrimination and unfairness in such machine decisions.

Against this background, in this talk, I will pose and attempt to answer the following high-level questions: (a) How do machines learn to make discriminatory decision making? (b) How can we quantify discrimination in machine decision making? (c) How can we control machine discrimination? i.e., can we design learning mechanisms that avoid discriminatory decision making? (d) Is there a cost to non-discriminatory decision making?




Stavroula Maglavera photo

The DSI Manifesto

Stavroula Maglavera, University of Thessaly

The Digital Social Innovation Manifesto sets the priorities and identifies the measures to be put in place for digital innovation to be at the service of the whole civil society. This will give a stronger voice to the Digital Social Innovation communities in Europe; help in obtaining support for bottom-up initiatives; and raise the public and political awareness about the importance of digital social innovation and its impact. Its current version can be found at: www.dsimanifesto.eu/manifesto.




More abstracts coming soon



Panel on “Data as a new currency in Next Generation Internet”

Panel Chair: Jonathan Cave, University of Warwick, UK

The following topics will be discussed:

  • Points on data as the new cash: Data are potentially valuable for a range of reasons, such as (a) observations about individuals can be used to target them (or match offers to needs); (b) observations about groups (data analytics) can be used to understand behaviour – or target in a less privacy-infringing way); (c) exposures of individuals to selected data can be used to ‘nudge’ them to make different decisions or reveal different data; and (d) data analytics can be used to animate new service and mfg business models.
  • This value can be captured in a range of ways allowing data to be converted into money – but that’s not the same as cash. If the value is shared broadly among consumers, firms, policy makers and the research community, the result can be better data – but there are issues of: (a) selection bias; (b) incentive distortions (e.g. strategic manipulation of data ‘footprints’ or choice of cash vs. data-paid channels); (c) endogeneity – the use of data changes the quantity, coverage and quality of data available.
  • What are the essential functions of cash, that data might pick up? (a) Universal, low-trust acceptability; (b) Agreed value in exchange; (c) Anonymity as to a) identity of counterparties, and b) prior history
  • What kinds of data are we talking about, and what are their special characteristics? (a) Personal data (b) System/operational data (including anonymised data like use of NFC payments in a transport net) (b) Cryptographic data – DLT/blockchain
  • What are the research and policy problems this raises? What are US-EU ‘points of scientific contact’ – scope for joint or complementary research based on scientific differences or ways data are being produced, collected and used?
  • What are EU-US shared policy problems that might motivate collaboration? (a) Are existing special-purpose regulations (e.g. Law Enforcement and NIS Directives, GDPR, MIFIDII/MAR) the answer (b) (Related, but more specific) are there special opportunities regarding e.g. health, finance and net neutrality/QoS?

Confirmed panelists: Franco Bagnoli (University of Florence), Ioannis Kompatsiaris (CERTH), Latif Ladid (Chair at 5G World Alliance & President, IPv6 Forum), Stavroula Maglavera (University of Thessaly), Thanassis Tiropanis (University of Southampton)


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