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Exploring trust in a conversational news recommender through perceived enjoyment and personalisation external link
Abstract
Conversational Agents (CAs) are transforming how news is distributed, offering a more dialogic and personalised approach for users. This transformation may help news organisations reach new audiences and hold the potential not only for them to engage with a new public, but also to enhance trust in their news recommenders. Despite the growing use of CAs for news recommendations, there is a limited understanding of how CAs in comparison to websites affect trust in the news recommender. To fill this gap, we assess the influence of various potential antecedents of trust (i.e. perceived ease of use, enjoyment, personalisation, and privacy concerns) through an online experiment. The experiment (N = 595) compared a news recommender in either a traditional news website or a CA. The results showed that participants had lower levels of trust in CAs compared to websites mediated by perceived enjoyment. This finding suggests that the dialogic nature of CAs does not inherently enhance enjoyment in the news context. Additionally, perceived personalisation was found to be an important antecedent influencing trust in the news recommender. Overall, these findings suggest that news organisations offering conversational news should prioritise enjoyable interactions with relevant content for the users to enhance trust.
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news personalisation, news recommenders, trust
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Legal Annex: CommonsDB as European Copyright Infrastructure external link
Europa gaat de AI-race nooit winnen. Tijd om slim te jatten external link
Abstract
Om AI-soeverein te worden zet de Europese Unie alles op alles voor reusachtige, peperdure, niet onomstreden AI-fabrieken. Maar terwijl politici bouwen aan technologie die over een paar jaar pas af is, draait de echte innovatie al op de laptop op je schoot.
Artificial intelligence
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From a Registry to a Registry Ecosystem: CommonsDB and the future of EU copyright infrastructure external link
Rethinking digital justice download
Abstract
Digital technology redefines the way that justice is delivered and received. This observation led to a number of insights on how to describe this still developing field of what is often referred to as digital justice. But what exactly is digital
justice? What is included and what is not? Academic literature and policy documents have dealt with digital justice in both civil and criminal justice by roughly using two approaches: a more restrictive approach using technology and the focal
point and a wider approach using technology as the starting point for a further analysis of its impact on human rights. Both approaches have their merits. Yet, since the topic of digitalisation and justice is an ever-evolving theme, it is necessary
to study what both approaches consist of and whether they stand the test of time. For that reason, this paper first unpacks how academia and policy have defined digital justice thus far and second, how digital justice could be defined. The goal is to conclude in a comprehensive definition of digital justice.
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Schrödinger’s Data: Rethinking the Binary Distinction Between Personal and Non- Personal Data in the Age of Synthetic Information. external link
Abstract
One might wonder what the Austrian physicist’s famous thought experiment and data classification have in common. In fact, the paradoxical dual state of simultaneous aliveness and death of Schrödinger’s cat, could be used as a practical foundation to exemplify a similar behaviour when distinguishing between personal and non-personal data in the context of synthetic information. The European data protection framework has at its core the binary distinction between personal and non-personal data. However, the current increase in the implementation of synthetic data, meaning algorithmically generated information, poses a challenge to this rigid classification. This is mainly because while synthetic data is often seen as a privacy-enhancing technology, not all synthetic information is the same and the risk of reidentification makes its classification legally ambiguous. Hence, as it will be further illustrated, and much like Schrödinger’s hypothetical cat sealed inside a box – which results both death and alive until the box is opened, data’s categorisation may require a more fluid approach. This opinion paper examines whether the binary model under the GDPR is sufficient to mitigate the adverse impacts of synthetic data. The first chapter exemplifies the nature of this kind of data, as well as the methodologies utilised to generate it, and possible legal challenges related to its use. Next, the limitations of the current EU data protection law framework are highlighted, particularly focusing on its applicability on synthetic data and dynamic data flows. Finally, the paper introduces alternative perspectives to the risk-based approach and binary divide between personal and non-personal data, drawing also from quantum mechanics notions. By critiquing the inadequacy of the current framework considering synthetic data through a critical, and interdisciplinary technology-focused legal lens, this paper argues data protection law must evolve beyond static classification, focusing instead on the ever-evolving status of data. At the same time, it recognises further discussion is still needed within a field that is relatively novel.
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One gate leads to many doors, a case study of MyGate in India download
Abstract
This chapter argues for why sector transgressions are not just a phenomenon of big tech, but equally present in small platforms. Through an analysis of the MyGate application, which focuses on community management in residential associations, she demonstrates how the company leverages its dominance in the sector by diversifying its offerings to move from a focus on identity verification to aspects such as payments. In doing so, this chapter argues that, much like big tech, these platforms place an emphasis on increasing the services on offer before focusing on profits, and in this particular case, see the road to growth as being shaped by super-app ambitions.
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Loss of judicial sight? The impact of assistive AI technologies on judicial perception — beyond the question of discretion
Abstract
Recent scholarship and judicial guidelines for the ethical use of technology have devoted considerable attention to the question of how the use of assistive AI technologies may impact – and potentially constrain or degrade – judicial discretion as an inherent factor characterising the human element of the judicial process. Drawing on perception-centred approaches to morality, this article addresses the largely overlooked question of how the use of these technologies may affect judges’ arguably more foundational and pervasive capacity for judicial perception. Judicial perception is an intrinsically valuable, multifaceted legal-ethical capacity that enables judges to register and value the salient facts of the cases that come before them. We develop our argument through an analysis of three hypothetical cases in which judges make use of three different AI tools to support some aspect of their decision-making. After interrogating potential opportunities for their use to support or enhance judicial perception, we conclude that these technologies are more likely to systematically steer judges’ attention away from the particulars of each case, distort their legal-ethical vision, or further entrench their already biased vision. This could lead to failures in – or the gradual degradation of – judicial sight, with consequences for the way in which judges exercise their discretion. To the extent that this loss of judicial sight occurs across the judiciary and over time, we anticipate three potential impacts on the justice system more broadly: a less-discussed form of judicial deskilling; diminished public perceptions of procedural fairness; and a loss of legal-ethical meaning.