Widespread use of Artificial Intelligence in all areas of today’s society creates a unique problem: algorithms used in decision-making are generally not understandable to those without a background in data science. Thus, those who use out-of-the-box Machine Learning (ML) approaches in their work and those affected by these approaches are often not in a position to analyse their outcomes and applicability. Our paper describes and evaluates our undergraduate course at the University of Minnesota Morris, which fosters understanding of the main ideas behind ML. With Communication, Media & Rhetoric and Computer Science faculty expertise, students from a variety of majors, most with no prior background in data science or computing, reviewed the scope of applicability of algorithms and became aware of possible biases, ‘politics’ and pitfalls. After discussing articles on societal attitudes towards technology, explaining key concepts behind ML algorithms (training and dependence on data), and constructing a decision tree as an example of an algorithm, we attempted to develop guidelines for ‘best practices’ for use of algorithms. Students presented a ‘case analysis’ capstone paper on an application of machine learning in society. Paper topics included: use of algorithms by child protection s ervices, ‘deepfake’ videos, genetic testing. The level of papers was indicative of students’ strong interest in the subject and their ability to understand key terms and ideas behind algorithms, societal perception and misconceptions of use of algorithms, and their ability to identify good and problematic practices in use of algorithms.
The proliferation of textual data in the form of online news articles and social media feeds has had an impact on the text analytics developments in recent years. Some of the challenges of natural language processing, understanding and generation have been successfully resolved and the results are applications such as AI personal assistants and bots. Word embeddings are an example of these successful solutions where unsupervised data-driven algorithms are used to understand concepts and relationships between words. This paper presents a description of word embedding algorithms, and a discussion on how bias in the training data can be captured, reproduced and even amplified by the algorithms.
The conflict between Israel and Palestine has lasted over half a century, with both sides enduring military and political turmoil. This paper explores how Twitter is being used as a medium to portray identities in the conflict. We examine the tweets contained in the @IDFspokesperson and @ISMPalestine Twitter accounts between late 2015 and early 2016. Using textual analysis, we gain an insight into how these Twitter accounts, defined by the conflict, are used in portraying the self and the other.
Recent years have seen a number of changes and developments in Ireland’s third-level education sector. Increasing concerns about student literacy issues have been accompanied by an apparent institutional logic in which generic ‘one size fits all’ modules are privileged on the basis of their expediency in the context of an underfunded, neoliberal educational landscape. While these modules may offer efficiencies at an administrative, teaching and practical level, there is little research that investigates their impacts and effectiveness on students in terms of disciplinary identity and knowledge, grades or quality assurance. As a contribution towards this topic, this exploratory paper discusses data and experiences gathered during the implementation of a discipline-specific ‘Film and Media Literacy’ module, delivered to a first year cohort of Film and Broadcasting BA students in Dublin Institute of Technology. On the basis of the experiences described herein, the paper makes a case for a disciplinary, rather than generic, approach to the teaching of a ‘literacy’ module in the context of media studies. After one year, the module discussed in this paper was found to be a flexible and effective teaching and learning model, permitting also identification of and engagement with student barriers to learning at first year level. However, the paper also argues for a more expansive and considered understanding of ‘disciplinarity’ in this specific context in order to more coherently address the perceived disciplinary literacy issues which were the instigation for the module. Irish Communications Review vol 16 (2018)
The global news flow of the Syrian conflict has been characterised by citizen journalism since its outset. In the absence of professional journalists on the ground, collaborative newsgathering with citizen activists has posed challenges for newsrooms seeking to align this practice with professional norms and values in journalism. This research investigates the sourcing of news content from the Aleppo offensive in November 2016. Quantitative content analysis and textual analysis of news texts by BBC World Service, France 24 English and Al Jazeera English examines how professional sourcing routines were adapted to a news context dominated by citizen activists and how these sources were framed as authoritative.
Despite three decades of research, the field of quantum computation has yet to build a quantum computer that can perform a task beyond the capability of any classical computer – an event known as computational supremacy. Yet this multibillion dollar research industry persists in its efforts to construct such a machine. Based on the counter-intuitive principles of quantum physics, these devices are fundamentally different from the computers we know. It is theorised that largescale quantum computers will have the ability to perform some remarkably powerful computations, even if the extent of their capabilities remains disputed. One application, however, the factoring of large numbers into their constituent primes, has already been demonstrated using Shor’s quantum algorithm. This capability has far reaching implications for cybersecurity as it poses an unprecedented threat to the public key encryption that forms an important component of the security of all digital communications. This paper outlines the nature of the threat that quantum computation is believed to pose to digital communications and investigates how this emerging technology, coupled with the threat of Adversarial Artificial Intelligence, may result in large technology companies gaining unacceptable political leverage; and it proposes measures that might be implemented to mitigate this eventuality. Irish Communications Review vol 16 (2018)
