Secret Search Engine Labs ^BETA

Events For Digital Dignity

At the EASA conference Barcelona, Peter Hervik and Sahana Udupa co-organized a roundtable, Artificial Intelligence: The Oppenheimer Moment? . Gabriele de Seta, Oana-Maria Mateescu, Minna Ruckenstein, Carles Salazar and
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Team For Digital Dignity

Sahana Udupa, Principal Investigator, For Digital Dignity Research GroupInstitute of Social and Cultural AnthropologyLMU Munich, Oettingenstrasse 67, Munich 80538, Germany
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Core Team For Digital Dignity

Founder and Principal Investigator
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About For Digital Dignity

The growth of internet-enabled social networking sites and messaging services has raised the possibility of wider democratic participation but has also created focal points for expressions of hate and exclusion. ONLINERP
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For Digital Dignity

The digital, it might safely be stated, is the language of the present. Its pervasiveness spans the mammoth structures of governance to the intimate intricacies of lived worlds. Beyond a descriptive nod to far-reaching d
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News For Digital Dignity

Applications are invited for 5 postdoctoral positions in the new ERC consolidator grant project on small social media platforms. Visit LMU job board for the links and full description of the positions. Contact ai4dignity
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Blogs For Digital Dignity

06 July 2018This post will begin with an example, and it is hoped that the process of fleshing it out shall help in identifying the dynamic processes that are involved in defining a meme
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Resources For Digital Dignity

Click on relevant sections to read more about the project outputs: academic publications, public scholarship and blogs. We look forward to your comments. Please add your feedback in the comments section.
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Public Scholarship For Digital Dignity

In a new podcast produced by the Bavarian Academy of Sciences, Matthias Quent, Andrea Abele-Brehm, Sahana Udupa, Christoph Neuberger, Anna Wegscheider, Marina Chernivsky, Max Czollek, Astrid Seville, Irma Trommer and Mar
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Peer Reviewed Publications For Digital Dignity

In this article published by Big Data Society, we present new empirical evidence to demonstrate the severe limitations of existing machine learning content moderation methods to keep pace with, let alone stay ahead of,
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