Back up: can users sue platforms to reinstate deleted content?

Matthias C. Kettemann, Leibniz Institute for Media Research | Hans-Bredow-Institut
Anna Sophia Tiedeke, Leibniz Institute for Media Research | Hans-Bredow-Institut
PUBLISHED ON: 4 Jun 2020 DOI: 10.14763/2020.2.1484

Can platforms delete whatever content they want? Not everywhere, say the authors of this paper, which shows why certain social networks ‘must carry’ some content – and how users in some jurisdictions can force the companies to allow them into their communicative space.

Data citizenship: rethinking data literacy in the age of disinformation, misinformation, and malinformation

Elinor Carmi, University of Liverpool
Simeon J. Yates, University of Liverpool
Eleanor Lockley, Sheffield Hallam University
Alicja Pawluczuk, United Nations University
PUBLISHED ON: 28 May 2020 DOI: 10.14763/2020.2.1481

In this paper we examine what data literacy means in the age of dis-/mis-/mal-information. We examine theoretical and methodological challenges researchers face when examining these two fields and how we can move forward by sharing our own experience in designing a survey to understand UK citizens data literacies.

A situated approach to digital exclusion based on life courses

Laura Faure, Fondation Travail-Université
Patricia Vendramin, Université catholique de Louvain (UCLouvain)
Dana Schurmans, Université catholique de Louvain (UCLouvain)
PUBLISHED ON: 27 May 2020 DOI: 10.14763/2020.2.1475

An analysis of digital exclusion risks around the transitions and ruptures that shape the life courses.

What do digital inclusion and data literacy mean today? Digital inclusion and data literacy

Elinor Carmi, University of Liverpool
Simeon J. Yates, University of Liverpool
PUBLISHED ON: 27 May 2020 DOI: 10.14763/2020.2.1474

This special issue is examining the different layers of digital inclusion and data literacy by drawing on research, policy, and practice developments around literacies in various regions and contexts. It highlights the politics around them so as to propose policies that are needed to include more people in datafied societies, and what types of literacies they should learn.

Transparency in artificial intelligence

Stefan Larsson, Lund University
Fredrik Heintz, Linköping University
PUBLISHED ON: 5 May 2020 DOI: 10.14763/2020.2.1469

Introduction: transparency in AI Transparency is indeed a multifaceted concept used by various disciplines (Margetts, 2011; Hood, 2006). Recently, it has gone through a resurgence with regards to contemporary discourses around artificial intelligence (AI). For example, the ethical guidelines published by the EU Commission’s High-Level Expert Group on AI (AI HLEG) in April 2019 states transparency as one of seven key requirements for the realisation of ‘trustworthy AI’, which also has made its clear mark in the Commission’s white paper on AI, published in February 2020. In fact, “transparency” is the single most common, and one of the key five principles emphasised in the vast number – a …