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DTSTART;TZID=Europe/Oslo:20251204T100000
DTEND;TZID=Europe/Oslo:20251204T120000
DTSTAMP:20260510T112258
CREATED:20251201T084826Z
LAST-MODIFIED:20251201T085050Z
UID:22036-1764842400-1764849600@mediafutures.no
SUMMARY:UiB AI #17 Open Artificial Intelligence
DESCRIPTION:This UiB AI seminar is organized by the Faculty of Law and raises the question: Can AI models be open in the same way as open-source software\, and should they be? \nOpen artificial intelligence refers to AI systems whose underlying programs and infrastructure\, training data\, model architecture\, and model weights are wholly or partly openly available\, allowing anyone to study\, modify\, and redistribute them. Large models such as ChatGPT\, Claude\, and Gemini offer access to their models\, but this access is limited to using the model. Other actors\, such as Meta’s Llama and the Chinese model DeepSeek\, present themselves as open\, but in reality provide only access to model weights and the ability to run the model locally. Their use is also subject to license terms that restrict both further distribution and commercial use. \nBut what does it actually mean for an AI model to be open? Can there be limitations on the use of open AI models? And should such models really be open\, given that openness may also make misuse easier? \nThe seminar will be streamed and recorded and given in Norwegian. \nPROGRAM: \n10:00 Coffee/tea and mingling  \n10:15–11:30 Presentations \n\n\nTorger Kielland\, Professor at the Faculty of Law \n\n\nPål Grønås Drange\, Associate Professor at the Department of Informatics\, Faculty of Science and Technology \n\n\n11:30 Light lunch and mingling
URL:https://mediafutures.no/event/uib-ai-17-open-artificial-intelligence/
CATEGORIES:Events
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DTSTART;TZID=Europe/Oslo:20251209T091500
DTEND;TZID=Europe/Oslo:20251209T143000
DTSTAMP:20260510T112258
CREATED:20251107T113353Z
LAST-MODIFIED:20251112T100750Z
UID:21948-1765271700-1765290600@mediafutures.no
SUMMARY:News experience: Understanding why and how audiences interact with news beyond audience metrics
DESCRIPTION:We are pleased to invite you to the trial lecture and public defence of Marianne Borchgrevink-Brækhus\, PhD candidate at SFI MediaFutures. \nDate: 9 DecemberVenue:  Ulrikes Aula\, Ulrike Pihls hus \nTime: The trial lecture starts at 09:15 and the defense begins at 10:30. \nPhD Thesis:News experience: Understanding why and how audiences interact with news beyond audience metrics \nThesis Summary: \nThis thesis explores how we can understand news use as experience. While audiences have become increasingly central to professional journalism and journalism studies\, understandings of audience practices and behaviors are predominantly shaped by digital trace data. Yet\, despite this growing attention to audiences\, news practitioners and scholars continue to talk more about audiences than with them. As a result\, our knowledge about people’s interactions with news\, and what these practices actually mean\, remains limited. Against this backdrop\, I approach news use as experience. I ask how we can further a more nuanced understanding of why and how audiences use news\, starting from the vantage point of the audience. \nTo address these questions\, I employ a multi-method research design\, combining recurring interviews and media diaries\, supplemented with video-ethnography and data donations. Drawing on the empirical insights provided by this multi-method approach\, I refine the concept of news experience\, emphasizing the importance of contextualizing understandings of news use within people’s everyday lives. By studying news use from an audience-centric perspective – bridging traditional qualitative methods with innovative digital ethnographic approaches across different media formats and platforms – I identify different experiences with news that both shape people’s practices and behaviors. \nThe empirical material is analyzed through four articles. The first article explores why young adults are reluctant to subscribe to digital news. I do this by analyzing experiences of young non-subscribers. The article provides insights into their considerations of why they do not subscribe as well as how they maneuver around paid news content. The second article offers a conceptualization of media experience\, demonstrating how this concept is well-attuned to grasp the ingrained position and meaning media hold in people’s lives. Applying conceptual principles from the second article\, the third article refines news experience as an analytical lens to understanding why and how people interact with news in everyday life\, empirically grounded in six distinct forms of experience shaping people’s practices. Finally\, the fourth article critically assesses the metric of “time spent” by analyzing how people navigate when reading news online\, and how short digital news practices relate to meaningful experiences with news. \nBy talking with people instead of about them\, this thesis critically assesses longstanding assumptions and misconceptions about audiences and their (digital) behaviors at a time when VI audience metrics have become integral to professional journalism and journalism studies. While I situate my research in relation to the audience turn in journalism research\, this thesis contributes to the existing literature by detailing methodological and epistemological implications of studying news use as experience. In doing so\, my research recognizes the lived\, contextual dimensions of everyday life that ultimately give shape and meaning to people’s news practices: it demonstrates how audiences’ behaviors are formed not merely by perceptions of the news content itself\, but also by embodied\, material\, and technological dimensions; the spatial\, temporal\, and social contexts in which it unfolds; and by their identities and previous knowledge. As such\, the thesis explicates how news use can result from conscious and explicit\, as well as unconscious and tacit practices and behaviors. I therefore argue that digital trace data – although relevant for identifying patterns and trends – cannot be applied as proxies for people’s interests or preferences. These insights are not only relevant from a societal perspective and to the field of journalism studies to inform more balanced assessments of news use in digital societies\, but also in professional terms as media organizations justify their policies and financial investments on the basis of such metrics. \nOpponents:  \n\nProfessor Jannie Møller Hartley\, The Department of Communication and Arts\, Roskilde University\nProfessor Marcel Broersma\, Centre for Media and Journalism Studies\, University of Groningen\n\nLeader of committee: \nProfessor Dag Elgesem\, Department of Information Science and Media Studies\, University of Bergen. \nChair of the defense:  \nProfessor Leif Ove Larsen\, Department of Information Science and Media Studies\, University of Bergen.
URL:https://mediafutures.no/event/news-experience-understanding-why-and-how-audiences-interact-with-news-beyond-audience-metrics/
LOCATION:Ulrike Pihls Hus\, Ulrikes aula\, Professor Keysers gate 1\, Bergen\, Norway
CATEGORIES:Events
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DTSTART;TZID=Europe/Oslo:20251215T091500
DTEND;TZID=Europe/Oslo:20251215T140000
DTSTAMP:20260510T112258
CREATED:20251006T085055Z
LAST-MODIFIED:20251006T085055Z
UID:21692-1765790100-1765807200@mediafutures.no
SUMMARY:Popularity Bias in Recommender Systems​
DESCRIPTION:We are pleased to invite you to the trial lecture and public defence of Anastasiia Klimashevskaia\, PhD candidate at SFI MediaFutures. \n Date: 15 December Venue: Ulrikes Aula\, University of Bergen \nTime: To be confirmed \nPhD Thesis:Beyond Popularity: Investigating and Mitigating Bias in Recommender Systems \nThesis Summary:Recommender systems are powerful tools shaping what users see and engage with online. However\, they often suffer from popularity bias\, where already popular items are disproportionately promoted while niche content remains underrepresented. This bias reduces diversity\, user satisfaction\, and fairness across platforms. \nIn her doctoral work\, Anastasiia Klimashevskaia examines the causes and effects of popularity bias through a comprehensive literature review\, explores debiasing strategies using real-world datasets\, and evaluates their performance in an online A/B test within a live recommender system. \nHer research further investigates how popularity bias interacts with other algorithmic biases and proposes novel mitigation strategies based on alternative theoretical frameworks. The findings shed light on the trade-offs between fairness\, diversity\, and recommendation quality—contributing to the creation of more equitable recommender systems. \nAll are warmly welcome to attend and take part in celebrating Anastasiia’s important milestone.
URL:https://mediafutures.no/event/popularity-bias-in-recommender-systems/
LOCATION:Ulrike Pihls Hus\, Ulrikes aula\, Professor Keysers gate 1\, Bergen\, Norway
CATEGORIES:Events
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