Trustworthy Journalism Through AI Journal Article Opdahl, Andreas L.; Tessem, Bjørnar; Dang-Nguyen, Duc-Tien; Motta, Enrico; Setty, Vinay; Throndsen, Eivind; Tverberg, Are; Trattner, Christoph In: Data & Knowledge Engineering (DKE), Elsevier, 2023. @article{Opdahl2023,
title = {Trustworthy Journalism Through AI},
author = {Andreas L. Opdahl and Bjørnar Tessem and Duc-Tien Dang-Nguyen and Enrico Motta and Vinay Setty and Eivind Throndsen and Are Tverberg and Christoph Trattner},
url = {https://mediafutures.no/1-s2-0-s0169023x23000423-main/},
year = {2023},
date = {2023-04-29},
urldate = {2023-04-29},
journal = {Data & Knowledge Engineering (DKE), Elsevier},
abstract = {Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid spread of disinformation. At the same time, quality journalism is under pressure due to loss of revenue and competition from alternative information providers. This vision paper discusses how recent advances in Artificial Intelligence (AI), and in Machine Learning (ML) in particular, can be harnessed to support efficient production of high-quality journalism. From a news consumer perspective, the key parameter here concerns the degree of trust that is engendered by quality news production. For this reason, the paper will discuss how AI techniques can be applied to all aspects of news, at all stages of its production cycle, to increase trust.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid spread of disinformation. At the same time, quality journalism is under pressure due to loss of revenue and competition from alternative information providers. This vision paper discusses how recent advances in Artificial Intelligence (AI), and in Machine Learning (ML) in particular, can be harnessed to support efficient production of high-quality journalism. From a news consumer perspective, the key parameter here concerns the degree of trust that is engendered by quality news production. For this reason, the paper will discuss how AI techniques can be applied to all aspects of news, at all stages of its production cycle, to increase trust. |
WP3 2021 M3.1 Report The industrial expectations to, needs from and wishes for the work package Technical Report Tverberg, Are; Agasøster, Ingrid; Grønbæck, Mads; Monsen, Marius; Strand, Robert; Eikeland, Kristian; Throndsen, Eivind; Westvang, Lars; Knudsen, Tove B.; Fiskerud, Eivind; Skår, Rune; Stoppel, Sergej; Berven, Arne; Pedersen, Glenn Skare; Macklin, Paul; Cuomo, Kenneth; Vredenberg, Loek; Tolonen, Kristian; Opdahl, Andreas L.; Tessem, Bjørnar; Veres, Csaba; Dang-Nguyen, Duc-Tien; Motta, Enrico; Setty, Vinay Jayarama University of Bergen, MediaFutures 2021. @techreport{Tverberg2021,
title = {WP3 2021 M3.1 Report The industrial expectations to, needs from and wishes for the work package},
author = {Are Tverberg and Ingrid Agasøster and Mads Grønbæck and Marius Monsen and Robert Strand and Kristian Eikeland and Eivind Throndsen and Lars Westvang and Tove B. Knudsen and Eivind Fiskerud and Rune Skår and Sergej Stoppel and Arne Berven and Glenn Skare Pedersen and Paul Macklin and Kenneth Cuomo and Loek Vredenberg and Kristian Tolonen and Andreas L. Opdahl and Bjørnar Tessem and Csaba Veres and Duc-Tien Dang-Nguyen and Enrico Motta and Vinay Jayarama Setty},
url = {https://mediafutures.no/wp3-q2-2021-m3-1-report-by-the-industrial-partners-final-2/},
year = {2021},
date = {2021-07-25},
urldate = {2021-07-25},
institution = {University of Bergen, MediaFutures},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
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