AI and Society 35 (2):355-365 (2020)
| Abstract |
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 of machine learning is embedded. And third, they are a consequence of current technical limitations in the development and use of artificial intelligence. The paper intends to provide an overview of current challenges which the research and development of applications in the field of artificial intelligence and machine learning have to face, whereas all three mentioned areas are to be further explored in this paper.
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| DOI | 10.1007/s00146-019-00886-y |
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References found in this work BETA
How the Machine ‘Thinks’: Understanding Opacity in Machine Learning Algorithms.Jenna Burrell - 2016 - Big Data and Society 3 (1):205395171562251.
Dialektik der Aufklärung. Philosophische Fragmente.M. Horkheimer, Th W. Adorno, Theodor W. Adorno & Jesús Aguirre - 1988 - Revista Portuguesa de Filosofia 44 (1):173-178.
Configuring the User as Everybody: Gender and Design Cultures in Information and Communication Technologies.Marcelle Stienstra, Els Rommes & Nelly Oudshoorn - 2004 - Science, Technology and Human Values 29 (1):30-63.
Citations of this work BETA
Algorithmic Augmentation of Democracy: Considering Whether Technology Can Enhance the Concepts of Democracy and the Rule of Law Through Four Hypotheticals.Paul Burgess - 2022 - AI and Society 37 (1):97-112.
Framing the effects of machine learning on science.Victo J. Silva, Maria Beatriz M. Bonacelli & Carlos A. Pacheco - forthcoming - AI and Society:1-17.
Knowledge-Augmented Face Perception: Prospects for the Bayesian Brain-Framework to Align AI and Human Vision.Martin Maier, Florian Blume, Pia Bideau, Olaf Hellwich & Rasha Abdel Rahman - 2022 - Consciousness and Cognition 101:103301.
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