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<pdf width="1500px">https://ceur-ws.org/Vol-2079/intro1.pdf</pdf>
<pre>
AI & Automated News: Implications on Trust, Bias, and
                   Credibility

                                                       Edgar Meij
                                                       Bloomberg



                                                                Biography
                                                                Edgar Meij is a senior scientist at Bloomberg. Before
                       Abstract
                                                                this, he was a research scientist at Yahoo Labs and a
    While the technology is far from mature, ar-                postdoc at the University of Amsterdam, where he also
    tificial intelligence in the form of autonomous             obtained his Ph.D. His research focuses on all applica-
    production of journalistic content is becoming              tions and aspects of knowledge graphs, entity linking,
    increasingly prominent in newsrooms – and                   and semantic search.
    it’s here to stay. The promise of automatically
    generating news at a faster pace, a larger scale,
    in multiple languages, and with potentially
    fewer errors, has scholars and practitioners
    championing this technology. As always, this
    development fuels fears that journalists will
    soon be out of work. Yet, today’s algorithms
    cannot ask questions, explain phenomena, or
    establish causality, giving human journalists
    the opportunity to write stories that address
    the ‘why’ something happens – as opposed to
    the ‘what’ that machines tell us. When es-
    tablished news organizations start publishing
    partly or fully automated news stories, they
    lend credibility to them. Little is known yet
    about potential societal implications of this
    on dimensions of trust and potential bias, as
    the algorithms themselves cannot be held ac-
    countable. In this talk, I will discuss these
    developments and also place them in the con-
    text of news search and recommendations, au-
    tomatic media monitoring, polarity detection
    and sentiment analysis.




Copyright c 2018 for the individual papers by the papers’ au-
thors. Copying permitted for private and academic purposes.
This volume is published and copyrighted by its editors.
In: D. Albakour, D. Corney, J. Gonzalo, M. Martinez,
B. Poblete, A. Vlachos (eds.): Proceedings of the NewsIR’18
Workshop at ECIR, Grenoble, France, 26-March-2018, pub-
lished at http://ceur-ws.org

</pre>