BDAIR 18: Special Issue on: "Big Data, Artificial Intelligence and Digital Futures"
Dr. Indrani Lahiri, Dr. Simon Mills and Dr. Aladdin Ayesh, De Montfort University, United Kingdom
The aim of this special issue is to address the recent complex issues imposed by advances in AI and big data on our digital presence now and in the future.
How might algorithms and big data shape our digital futures? In what ways can the semantic web impact our everyday lives? 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 the day when technology induces behavioural changes, not only at cognitive level but also at conative levels? What of 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 becoming increasingly interpellated by algorithms and data. How does that then impact the ‘Logos-Pathos-Ethos’ of our lives? Sophia Bot froze on the question of corruption in Ukraine. On the other hand, we witnessed how the sentiment analysis tool was used ahead of the Brexit referendum campaign through the online conversation summarisation technology as part of the SENSEI European Project.
At the same time, big data poses challenges as it generates noise and that means data can often be indecipherable, bewildering and recherché. Disruptions are common when we deal with data in any subject area. Therefore, it is cardinal to address this technological complexity, not only through academic research, scholarship and pedagogic practice, but also through industry engagement. Furthermore, 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).
The aim of this special issue is to reach an international audience and to develop the critical conversation around the data paradigm to challenge conventions and propose innovative engagement to expand our boundaries. The focus is expected to be on technological answers to challenges of AI and big data advances. Papers reporting on research developed in multi-disciplinary projects or the results of multi-disciplinary collaborations are very welcome.
Cadwalladr, C. (2017). The great British Brexit robbery: how our democracy was hijacked. [online] the Guardian. Available at: https://www.theguardian.com/technology/2017/may/07/the-great-british-brexit-robbery-hijacked-democracy [Accessed 4 Jun. 2018].
Cadwalladr, C. (2016). Google, democracy and the truth about internet search. [online] the Guardian. Available at: https://www.theguardian.com/technology/2016/dec/04/google-democracy-truth-internet-search-facebook [Accessed 4 Jun. 2018].
Siapera, E. (2018). Understanding New Media. SAGE Publications Ltd.
Suitable topics include, but are not limited, to the following:
- Social media and big data
- Ethics, privacy and technology
- Data and sustainability
- Data mining
- Machine learning and personalisation
- Social bots and the management of sociality
- Internet of Things
- Anonymisation and de-anonymisation algorithms
- Data and surveillance
- Quantified self and data cultures
- Data and education
- Researching media and culture using data methods
- Data visualisation, art and design
- Data and health
- Mobile and locative media
- Cognitive systems
- Sentiment analysis
- Affective computing
- Computational linguistics
- Computational models for cyber psychology.
Notes for Prospective Authors
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).
All papers are refereed through a peer review process.
All papers must be submitted online. To submit a paper, please read our Submitting articles page.
Manuscripts due by: 20 September, 2018
Notification to authors: 20 November, 2018
Final versions due by: 30 January, 2019