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  1.  56
    The Ethics of AI Ethics: An Evaluation of Guidelines.Thilo Hagendorff - 2020 - Minds and Machines 30 (1):99-120.
    Current advances in research, development and application of artificial intelligence systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, (...)
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  2.  4
    Privatsphäre 4.0: Eine Neuverortung des Privaten Im Zeitalter der Digitalisierung.Hauke Behrendt, Wulf Loh, Tobias Matzner, Catrin Misselhorn, Carsten Ochs, Charles Melvin Ess, Thilo Hagendorff, Dorota Mokrosinska, Titus Stahl, Sandra Seubert, Johannes Eichenhofer, Christian Djeffal, Eva Weber-Guskar, Jan-Felix Schrape & Sebastian Ostritsch - 2019 - J.B. Metzler.
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  3.  72
    15 Challenges for AI: Or What AI (Currently) Can’T Do.Thilo Hagendorff & Katharina Wezel - 2020 - AI and Society 35 (2):355-365.
    The current “AI Summer” is marked by scientific breakthroughs and economic successes in the fields of research, development, and application of systems with artificial intelligence. But, aside from the great hopes and promises associated with artificial intelligence, there are a number of challenges, shortcomings and even limitations of the technology. For one, these challenges arise from methodological and epistemological misconceptions about the capabilities of artificial intelligence. Secondly, they result from restrictions of the social context in which the development of applications (...)
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  4.  11
    Forbidden Knowledge in Machine Learning Reflections on the Limits of Research and Publication.Thilo Hagendorff - forthcoming - AI and Society:1-15.
    Certain research strands can yield “forbidden knowledge”. This term refers to knowledge that is considered too sensitive, dangerous or taboo to be produced or shared. Discourses about such publication restrictions are already entrenched in scientific fields like IT security, synthetic biology or nuclear physics research. This paper makes the case for transferring this discourse to machine learning research. Some machine learning applications can very easily be misused and unfold harmful consequences, for instance, with regard to generative video or text synthesis, (...)
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  5.  10
    Correction to: The Ethics of AI Ethics: An Evaluation of Guidelines.Thilo Hagendorff - forthcoming - Minds and Machines:1-5.
    In the original publication of this article, the Table 1 has been published incorrectly. Now the same has been provided in this correction.
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  6.  26
    From Privacy to Anti-Discrimination in Times of Machine Learning.Thilo Hagendorff - 2019 - Ethics and Information Technology 21 (4):331-343.
    Due to the technology of machine learning, new breakthroughs are currently being achieved with constant regularity. By using machine learning techniques, computer applications can be developed and used to solve tasks that have hitherto been assumed not to be solvable by computers. If these achievements consider applications that collect and process personal data, this is typically perceived as a threat to information privacy. This paper aims to discuss applications from both fields of personality and image analysis. These applications are often (...)
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  7.  7
    Publisher Correction to: The Ethics of AI Ethics: An Evaluation of Guidelines.Thilo Hagendorff - 2020 - Minds and Machines 30 (3):457-461.
    In the original publication of this article, the Table 1 has been published in a low resolution. Now a larger version of Table 1 is published in this correction. The publisher apologizes for the error made during production.
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