Poking Holes: Distributed Ambivalence and Aesthetics in Sound Networks

Amid the current pandemic (COVID-19) disembodied presence has emerged as the new norm, revealing a world increasingly entangled with the technological and conceptual paradigm of the network. In this scenario, it is crucial to reconsider core axioms of the pervasive connectionist credo, acknowledging the empty space that a network subtends, the hollowness of its lattice, […]

Mapping and understanding human factors in effective cybersecurity: a finance-sector organisation case study

The role of human factors in cybersecurity has gained increasing interest in the past decade. Social science research methods can provide a unique avenue for obtaining a holistic overview of how cybersecurity is both implemented and perceived within an organisation. One-to-one semi-structured interviews were conducted with 17 participants from a finance sector organisation. Five themes […]

Designing the (data)Hive: Principles-based decentralised architectures

Decentralised architectures and networks are slowly embedding themselves into the technological and societal landscape, empowered by communities of like-minded people who strive to alter the existing socio-economic order by leveraging peer-to-peer (P2P) technologies. In this article, we discuss one such initiative, Swarm, by drawing relations between its developed set of community-centred, bottom-up Fair Data Principles […]

How to Conduct an Ethics Assessment of AI in Policing

Crucially, ethical scrutiny must engage all aspects of the policing context. The context for adopting AI is neither solely technical nor solely societal in importance; it is a socio-technical interaction whereby technological systems (law enforcement or safeguarding) are designed by humans (developers) for humans (police) with an impact on individuals (citizens, residents, suspects, victims) and […]

Data augmentation for fairness-aware machine learning: Preventing algorithmic bias in law enforcement systems

Researchers and practitioners in the fairness community have highlighted the ethical and legal challenges of using biased datasets in data-driven systems, with algorithmic bias being a major concern. Despite the rapidly growing body of literature on fairness in algorithmic decision-making, there remains a paucity of fairness scholarship on machine learning algorithms for the real-time detection […]

A survey of AI risk assessment methodologies

In recognition of both the increasing importance of AI in our digital society and the wide diversity of use cases, policymakers across the globe are seeking to better understand the risks that these new AI systems might pose to society. A growing consensus is emerging in favor of risk-based approaches to regulating the use of […]

Operationalising Human Security in the Contemporary Operating Environment: Proposing Population Intelligence (POPINT)

Drawing upon primary research funded by the UK Defence and Security Accelerator (DASA), researchers from Trilateral Research explore the use of data analytics and artificial intelligence (AI) for operationalising human security in the contemporary operating environment. The idea of human security has gained much traction in the international community since its introduction in a 1994 […]