"Integrating AI learning objectives into official school curricula is crucial for students globally to engage safely and meaningfully with AI. The UNESCO AI competency framework for students aims to help educators in this integration, outlining 12 competencies across four dimensions: Human-centred m
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indset, Ethics of AI, AI techniques and applications, and AI system design. These competencies span three progression levels: Understand, Apply, and Create. The framework details curricular goals and domain-specific pedagogical methodologies. Grounded in a vision of students as AI co-creators and responsible citizens, the framework emphasizes critical judgement of AI solutions, awareness of citizenship responsibilities in the era of AI, foundational AI knowledge for lifelong learning, and inclusive, sustainable AI design." (Short summary)
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"Social media platforms have become crucial channels for radical right populist leaders to broadcast anti-immigrant views. These politicians employ various rhetorical appeals, such as pathos (emotional language), logos (logical arguments), and ethos (speaker credibility), to sway public opinion. Thi
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s study considers the anti-immigrant rhetoric of prominent European populist radical right leaders across X, Instagram, and Facebook, analysing the prevalence of these rhetorical strategies across different platforms. From the perspective of mediatization theory, politicians can adjust their messages to fit with the design and formats of various social media platforms. Party leaders often resort to emotional appeals on X, with its limited space for communication, as well as on Facebook, where emotional interaction buttons and discussion features can encourage emotional rhetoric as well. Logical appeals (logos) are common on platforms such as Facebook and X, which offer options to easily share information in the form of texts and links. Additionally, ethos, associated with speaker’s credibility, is common in posts on platforms that facilitate closer engagement with the party leaders’ constituents, such as Facebook and Instagram. These findings underscore the importance of considering platform design when shaping political communication strategies." (Abstract)
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"The article builds on current research into the effects and harms of hate speech in the lives of its victims. It introduces the anthropological concept of everyday violence to focus on hate speech as an everyday experience as opposed to a sequence of separate hate speech acts. Methodologically, the
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study is based on a qualitative approach and analyses data collected via semi-structured interviews (N=33) with people who have experienced hate speech in four EU member states (Italy, Germany, the Czech Republic and Portugal). The analysis documents four overlapping themes of how hate speech manifests as the everyday experience of “living hated”—hate speech as a flow; its spatial dimension of moving across online and offline contexts; its long-term effects, leading to what we call “cumulative desensitization” (aggravated during the COVID-19 pandemic); and the role of support systems and their (in)effectiveness. The article concludes by suggesting possible applications as well as avenues for future research that could provide a deeper understanding of hate speech as the daily life experience of its targets." (Abstract)
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"This study contributes to research on digital inequalities in the context of artificial intelligence by examining user perceptions of deepfake technology. We focus on the stratification of deepfake knowledge and attitudes towards deepfakes as critical elements of technology access. Based on a surve
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y of 1,421 German internet users, we analyse the role of sociodemographic variables, digital skills, and personal innovativeness in predicting deepfake knowledge. We then examine the role of deepfake knowledge in users’ assessments of risks and potentials associated with the technology. Our results point to a generally low level of knowledge and a strong focus on risks in internet users’ perceptions of deepfakes. We find that age, gender and educational attainment predict knowledge about deepfakes. Digital skills, personal innovativeness, and social media use also positively relate to deepfake knowledge. This knowledge, in turn, is shown to play a role in users’ positive attitude towards the technology. While age plays only a minor role, female gender strongly relates to low knowledge and negative attitudes towards deepfakes. We thus find evidence of a sizeable gender divide in user access to the novel deepfake technology." (Abstract)
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"Artificial Intelligence (AI) is woven into a supply chain of capital, commodities and human labour that has been neglected in critical debates. Given the current surge in generative AI – which is estimated to drive up the extraction of natural resources such as minerals, fossil fuels or water –
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it is vital to investigate its entire production line from a critical infrastructural perspective. Drawing on the supply chain capitalism, a concept coined by Anna L. Tsing in 2009, this paper contributes to critical AI studies by investigating the structure of AI supply chains, taking into account the mining, electronics, digital and e-waste industry. This paper illustrates how the supply chain capitalism of AI is precipitating geographical asymmetries connected to contested struggles in México by focusing on a key element of these chains: data centres. In times of climate emergency, this paper calls to reconsider algorithmic harms and resistance by investigating the entire capitalist production line of the AI industry from critical and environmental lens." (Abstract)
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"Algorithms have risen to become one, if not the central technology for producing, circulating, and evaluating knowledge in multiple societal arenas. In this book, scholars from the social sciences, humanities, and computer science argue that this shift has, and will continue to have, profound impli
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cations for how knowledge is produced and what and whose knowledge is valued and deemed valid. To attend to this fundamental change, the authors propose the concept of algorithmic regimes and demonstrate how they transform the epistemological, methodological, and political foundations of knowledge production, sensemaking, and decision-making in contemporary societies. Across sixteen chapters, the volume offers a diverse collection of contributions along three perspectives on algorithmic regimes: the methods necessary to research and design algorithmic regimes, the ways in which algorithmic regimes reconfigure sociotechnical interactions, and the politics engrained in algorithmic regimes." (Publisher description)
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"Does the news media exacerbate or reduce misinformation problems? Although some news media deliberately try to counter misinformation, it has been suggested that they might also inadvertently, and sometimes purposefully, amplify it. We conducted a two-wave panel survey in Brazil, India, and the UK
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(N=4732) to investigate the effect of news and digital platform use on awareness of and belief in COVID-19 misinformation over time (January to February 2022). We find little support for the idea that the news exacerbates misinformation problems. News use broadened people’s awareness of false claims but did not increase belief in false claims—in some cases, news use actually weakened false belief acquisition, depending on access mode (online or offline) and outlet type. In line with previous research, we also find that news use strengthens political knowledge gain over time, again depending on outlets used. The effect of digital platforms was inconsistent across countries, and in most cases not significant—though some, like Twitter, were associated with positive outcomes while others were associated with negative outcomes. Overall, our findings challenge the notion that news media, by reporting on false and misleading claims, ultimately leave the public more misinformed, and support the idea that news helps people become more informed and, in some cases, more resilient to misinformation." (Abstract)
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"Online labour markets (OLMs) are a vital source of income for globally diverse and dispersed freelancers. Despite their promise of neutrality, OLMs are known to perpetuate hiring discrimination, vested in how OLMs are designed and what kinds of interactions they enable between freelancers and hirer
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s. In this study, we go beyond understanding mechanisms of hiring discrimination in OLMs, to identifying platform design features that can minimise hiring discrimination. To do so, we draw on a methodology guided by the design justice ethos. Drawing on a survey on UK-based freelancers and interviews with a purposefully drawn sub-sample, we collaboratively identify five platform design interventions to minimise hiring discrimination in OLMs: community composition, identity-signalling flairs, text only reviews, union membership, and an antidiscrimination prompt. The core of our study is an innovative experiment conducted on a purpose-built, mock OLM, Mock-Freelancer.com. On this mock OLM, we experimentally test mechanisms of discrimination, including how these mechanisms fare under the five altered platform design interventions through a discrete-choice experiment. We find that both community and flairs were important in encouraging the hiring of women and non-White freelancers. We also establish that anonymity universally disadvantages freelancers. We conclude with recommendations to design OLMs that minimise labour market discrimination." (Abstract)
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"The global food system is characterized by market concentration and oligopoly. In our article, we focus on the most powerful input supply and machinery companies and analyze how these firms create value, both economic and otherwise, from big data. In digital capitalism, data is valorized across sec
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tors; personal data is aggregated into large-scale datasets, a practice that feeds economic concentration and monopolization. Big data also has become central to the business model for agricultural companies; it is a claim made by the companies themselves. Yet, little is known about their specific strategies to do so. We aim to fill this gap, asking how is agricultural data transformed into value by the most powerful agribusinesses and ag-tech firms? Through the lens of assetization, we examine corporate strategies for transforming agricultural data into value. We draw on literature from food studies, specifically political economic analyses of the historical practices of agricultural corporations, as well as literature from critical data studies that investigates data as an asset. For our analysis, we rely on a variety of gray literature and public-facing documents: financial documents, sustainability and shareholder reports, terms of use, license agreements, and news articles. Our results contribute to the critical data studies literature on agricultural big data by identifying three main strategies of assetization: securing relationships and dependence, price-setting and data sharing, and product development and targeted marketing. The strategies have socio-ecological implications; our results indicate the reproduction of asymmetrical power relations in the agri-food system favoring corporations and the continuation of long-standing dynamics of inequalities." (Abstract)
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