Digital Futures Symposium

Call for papers We invite contributions to a Special Issue on Big Data, AI and Digital Futures: Challenges, changes and continuities, to be published by the AI & Society Journal of Culture, Knowledge and Communication (Springer) http://link.springer.com/journal/146. This special issue arises from the Big Data, AI and Robotics (BDAIR 18) Research Symposium at the De Montfort University (DMU). The main objective of this special issue is to encourage cross-disciplinary, interdisciplinary research and international research collaboration. ============================= SPECIAL ISSUE THEMES ============================= Aims: The aim of this special issue is to address the societal complex issues emerging from the recent advances in AI. As we look for answers to address new challenges, we look at the impact of AI and big data on our futures in the context of society. Content How might algorithms and big data shape our digital futures? In what ways can the semantic web impact our everyday life? Are there ways of envisioning a structure for managing data in a meaningful way, which may offer a transformational experience? We are witnessing a shift in political, social, cultural and technical relations which are increasingly driven by big data and algorithms. Our external environment is being codified leading to an increased level of surveillance both at personal and professional levels. This in itself is a challenge to privacy and data protection. We are already experiencing self-monitoring and tracking with the devices we wear that prompt us to engage in certain behaviours. Are we far from a day when technology will induce behavioural changes, not only at cognitive level but also at conative levels? What for claims that Big Data will make theory redundant? What ontological and epistemological issues arise in relation to these technologies? Our thoughts, emotions and actions are increasingly getting interpellated by algorithms and data. How does that then impact on the ‘Logos-Pathos-Ethos’ of our lives? Sophia bot froze on the question of corruption in Ukraine. On the other hand, we witnessed “the great British Brexit robbery” (Guardian, 2017) that proved whoever owns the data actually wins the campaign, election and the world. Cambridge Analytics Brexit has been one of the popular searches on the internet. At the same time, big data pose challenges as they generate noise and that means data often can be indecipherable, bewildering and recherché. Disruptions are common when we deal with data in any subject area. Therefore, it is cardinal to address the technological complexity, not only through academic research, scholarship and pedagogic practice but also industry engagement. On the other hand, big data and algorithms embed innovation and we encounter technologies in a transformational way, where conversations and dialogic interventions are rapid. Perhaps due to the contrasting ways in which we engage with big data and algorithms, the need for well-defined theoretical frameworks and methodological tools are increasingly in demand Siapera, 2018). Readership National and International We will invite experts both nationally and internationally to contribute to this special issue Goal Our goal is to offer an interdisciplinary coverage of the area explored, by bringing together perspectives from different domains such as computer science, design studies, business, cultural anthropology, arts and humanities and social sciences. In particular, we welcome contributions that explore the following themes: Themes Topics include, but are not limited to, the following: Media datafication and neoliberalism Data and business Social media and big data Big data, PR and Advertising Big data and politics Ethics, privacy and technology Data and sustainability Personalisation, Machine learning and AI Social bots and the management of sociality Quantified self and data cultures Data and education Researching media and culture using data methods Data visualisation, art and design Social responsibility and innovation Data and health Mobile and locative media Data and surveillance Using Big Data to test social theories Social data collection and novelt