In this chapter, we explore the intersection of data journalism practices with issues of (governance) transparency and accountability. We advance the argument that data journalism can be instrumental in helping journalists seek accountability in opaque regimes that have an uneasy relationship with watchdog journalism. We use the Zimbabwe’s post-coup regime to demonstrate that at the centre of political authoritarianism, is a refusal to account, and a culture of non-transparency. Faced with such, the media can utilise publicly available sources of data journalism to exercise their responsibility. Data journalism is, hence, critical as a media practice that provides avenues for journalists in semi-authoritarian regimes to continuously pursue their mandates as accountability seekers. Our chapter contributes to emerging literature on data journalism in Africa, especially in semi-authoritarian contests like that of Zimbabwe.
Category: 3/ Type
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Louvre Abu Dhabi as a State Project: A Museum, a New Ministry, and the Politics of Culture
As the first universal museum in the Arab world, Louvre Abu Dhabi (LAD) aims to cover all aspects of human history, promoting inclusivity and openness. Despite being hailed as a symbol of tolerance and intercultural dialogue, some shortcomings and valid criticisms are evident. This study explores LAD’s artistic and political roles, as well as its contribution to social cohesion and the United Arab Emirates’ (UAE’s) readiness to address broader issues in line with the UAE Centennial Plan 2071. The analysis also delves into the responsibilities of cultural initiatives, the challenges of operating within an authoritarian context, and the necessity for policy reconsideration to achieve the UAE’s ambitious visions. The fact that LAD has undoubtedly served state interests highlights its limitation in engaging with the broader mission of museums—to address often-unpleasant political and socioeconomic matters. Moreover, the article asserts that constructive exchanges about critical issues should be embraced as opportunities rather than threats; suppressing these discussions through censorship and fear undermines the potential for growth and understanding. Thus, the study calls for a balanced approach where cultural institutions like LAD can foster dialogue and contribute meaningfully to the social and political landscape of the UAE.
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Ceiba Law Firm Annual Retreat
We were pleased to be of service to Ceiba Law for their annual retreat this year. Our director Tammy Mackenzie joined the firm partners and associates to discuss the changes and opportunities of AI for lawyers in cybersecurity and corporate law. A huge shout out to partners Vanessa Henri, Elodie Meyer and Shawn Ford for an invigorating retreat and inspiring firm ethos. A law firm purpose built for the 21st century.
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Trainees’ perspectives and recommendations for catalyzing the next generation of NeuroAI researchers
At this critical juncture in the development of NeuroAI, we outline challenges and training needs of junior researchers working across AI and neuroscience. We also provide advice and resources to help trainees plan their NeuroAI careers.
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Evaluating Online AI Detection Tools: An Empirical Study Using Microsoft Copilot-Generated Content
Our findings reveal significant inconsistencies and limitations in AI detection tools, with many failing to accurately identify Copilotauthored text. Examining eight freely available online AI detection tools using text samples produced by Microsoft Copilot, we assess their accuracy and consistency. We feed a short sentence and a small paragraph and note the estimate of these tools. Our results suggest that educators should not rely on these tools to check for AI use.
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Explaining the Comparatively Less Robust Human Rights Impact of the ECOWAS Court on Legislative and Judicial Decision-making, Process, and Action in Nigeria
This article outlines and tackles two inter-related puzzles regarding the comparatively much less robust human rights impact that the ECOWAS Court (in effect, West Africa’s international human rights court) has had on the generally more democratic legislative/judicial branch of decision-making and action in Nigeria vis-à-vis the generally more authoritarian executive branch within Nigeria, the country that is the source of most of the cases filed before the court. The article then discusses and analyzes the examples and extent of the court’s human rights impact on legislative/judicial branch decision-making and action in that key country. This is followed by the development of a set of analytical, multi-factorial, explanations for the two inter-connected puzzles that animate the enquiry in this article. In the end, the article argues that several factors have combined to produce the comparatively much less robust human rights impact that the ECOWAS Court has had on domestic legislative and judicial decision-making, process, and action in Nigeria, through restricting the extent to which the latter could mobilize more robustly the court’s human rights-relevant processes and rulings.
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From Crisis Management to the crisis of management: Accountability and Liberal Democracies in the Outbreak of the Covid-19 Pandemic
The outbreak of the COVID-19 pandemic shocked societies around the world. In their efforts to tailor their responses to the crisis to their own conditions for survival, from the outset governments tended to resort to arguments that limited accountability before their populations. Liberal democracies were no exception to this approach. In this context, their leaders used the metaphor of war to describe their position as guarantors of the population’s survival in the face of the new threat. Caught between uncertainty and the need to predict the nature and evolution of the invisible enemy, their responses called into question the political, professional and personal responsibility of leaders. This article offers a reflection on the level of responsibility of governments in liberal democracies in managing the pandemic. During the crisis, decision-makers tended to be driven by the narratives that were most beneficial to them in order to escape their responsibilities, thereby underpinning their short-term political needs through the use of bellicose metaphors, the blame game, competition with other countries, and the dispersion of sources in the decision-making process. This reality now calls for reflection by social actors, including experts, intellectuals and the media, to transcend the prevailing rhetoric in management of the pandemic and the “new normal” that followed, so that the dynamics of constant alterations in the rules of the game and responsibilities can give way, in the future, to a scenario with less arbitrariness and more accountability.
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GenAI and Religion: Creation, Agency, and Meaning
This paper explores the parallels between Generative Artificial Intelligence (GenAI) and religious systems in three domains: creation, agency, and meaning-making. Both offer frameworks for human engagement but differ in intent, autonomy, and moral accountability. Despite these differences, GenAI and religion share roles as creators, influencers, and meaning facilitators. We address and counter rebuttals to these parallels, highlighting GenAI’s co-constructed outputs and its impact on modern meaning-making. The paper concludes with the societal implications of these parallels in shaping future thought and action.
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Qualitative Insights Tool (QualIT): LLM Enhanced Topic Modeling
Topic modeling is a widely used technique for uncovering thematic structures from large text corpora. However, most topic modeling approaches e.g. Latent Dirichlet Allocation (LDA) struggle to capture nuanced semantics and contextual understanding required to accurately model complex narratives. Recent advancements in this area include methods like BERTopic, which have demonstrated significantly improved topic coherence and thus established a new standard for benchmarking. In this paper, we present a novel approach, the Qualitative Insights Tool (QualIT) that integrates large language models (LLMs) with existing clustering-based topic modeling approaches. Our method leverages the deep contextual understanding and powerful language generation capabilities of LLMs to enrich the topic modeling process using clustering. We evaluate our approach on a large corpus of news articles and demonstrate substantial improvements in topic coherence and topic diversity compared to baseline topic modeling techniques. On the 20 ground-truth topics, our method shows 70% topic coherence (vs 65% & 57% benchmarks) and 95.5% topic diversity (vs 85% & 72% benchmarks). Our findings suggest that the integration of LLMs can unlock new opportunities for topic modeling of dynamic and complex text data, as is common in talent management research contexts.
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Generative AI through the Lens of Institutional Theory
This study examines the adoption of Generative AI (GenAI) systems through the lens of Institutional Theory. Using a mixed-methods approach, we analyze how coercive, normative, and mimetic pressures influence GenAI integration in organizations. Key findings reveal:(1) regulatory frameworks significantly shape GenAI adoption strategies, with variations across industries and regions;(2) organizations balance conformity to institutional norms with innovation, often through strategic decoupling;(3) GenAI’s unique capabilities challenge traditional institutional pressures, necessitating new governance models; and (4) early GenAI adopters emerge as new sources of mimetic pressure, accelerating industry-wide adoption. We propose a novel framework capturing the interplay between GenAI characteristics and institutional dynamics, contributing to both Institutional Theory and AI adoption literature.
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‘We Condemn the Sin, not the Sinner’: Understanding the Attitudes of Adventist and Baptist Believers in Montenegro towards Sexuality
Although we have seen studies on religion and sexuality in the West come to dominate the relevant scholarship, the postsocialist environment with a predominantly Orthodox population has received less attention. This paper fills the gap by examining the attitudes of Adventist and Baptist believers in Montenegro, with a particular focus on abortion, premarital sexual activities and non-heteronormative sexuality. Because we were dealing with a minority population, we opted for a qualitative methodology and conducted semistructured interviews with 17 Adventist and 15 Baptist believers. As observed, our research participants’ position towards sexuality is closely related to the teachings found in the Bible. However, it is possible to observe certain differences between the two groups; for example, the interviewed Adventists tend to be more conservative than the interviewed Baptists. In addition, the male Adventists seem slightly more liberal than female Adventists, whereas the situation is different among Baptists, where women come across as more liberal than men.
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Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems
Artificial Intelligence (AI) has paved the way for revolutionary decision-making processes, which if harnessed appropriately, can contribute to advancements in various sectors, from healthcare to economics. However, its black box nature presents significant ethical challenges related to bias and transparency. AI applications are hugely impacted by biases, presenting inconsistent and unreliable findings, leading to significant costs and consequences, highlighting and perpetuating inequalities and unequal access to resources. Hence, developing safe, reliable, ethical, and Trustworthy AI systems is essential. Our team of researchers working with Trustworthy and Responsible AI, part of the Transdisciplinary Scholarship Initiative within the University of Calgary, conducts research on Trustworthy and Responsible AI, including fairness, bias mitigation, reproducibility, generalization, interpretability, and authenticity. In this paper, we review and discuss the intricacies of AI biases, definitions, methods of detection and mitigation, and metrics for evaluating bias. We also discuss open challenges with regard to the trustworthiness and widespread application of AI across diverse domains of human-centric decision making, as well as guidelines to foster Responsible and Trustworthy AI models.