Daniel Schoenberger

Trained mason Tom Litwan began crafting elegant yet edgy, biodynamic, low-intervention Pinot Noirs and Chardonnays in Switzerland's Aargau back in 2006. Today his wines play in the same league as top French and German producers.

Swiss wines remain rare on the international wine scene. But a new generation of talent committed to uncompromising work and meaningfully sustainable viticulture is slowly changing this.

Markus Ruch has been cultivating his own vineyards in the Klettgau, part of Switzerland’s northernmost canton, since 2007. He is widely credited with producing the first Swiss natural wines and leads the movement today. His Pinot Noirs and orange Amphore are served from NOMA in Copenhagen to Konstantin… Mehr anzeigen

Swiss wines remain rare on the international wine scene. But a new generation of talent committed to uncompromising work and meaningfully sustainable viticulture is slowly changing this.

Markus Ruch has been cultivating his own vineyards in the Klettgau, part of Switzerland’s northernmost canton, since 2007. He is widely credited with producing the first Swiss natural wines and leads the movement today. His Pinot Noirs and orange Amphore are served from NOMA in Copenhagen to Konstantin Filippou in Vienna. Ruch’s wines are classy. With a twist. Weniger anzeigen

Daniel Schönberger, Artificial intelligence in healthcare: A critical analysis of the legal and ethical implications, International Journal of Law and Information Technology, Volume 27, Issue 2, Summer 2019, Pages 171–203, DOI: 10.1093/ijlit/eaz004

Abstract:

Artificial intelligence (AI) is perceived as the most transformative technology of the 21st century. Healthcare has been identified as an early candidate to be revolutionised by AI technologies. Various clinical and… Mehr anzeigen

Daniel Schönberger, Artificial intelligence in healthcare: A critical analysis of the legal and ethical implications, International Journal of Law and Information Technology, Volume 27, Issue 2, Summer 2019, Pages 171–203, DOI: 10.1093/ijlit/eaz004

Abstract:

Artificial intelligence (AI) is perceived as the most transformative technology of the 21st century. Healthcare has been identified as an early candidate to be revolutionised by AI technologies. Various clinical and patient-facing applications have already reached healthcare practice with the potential to ease the pressure on healthcare staff, bring down costs and ultimately improve the lives of patients. However, various concerns have been raised as regards the unique properties and risks inherent to AI technologies. This paper aims at providing an early stage contribution with a holistic view on the “decision-making” capacities of AI technologies. The possible ethical and legal ramifications will be discussed against the backdrop of the existing frameworks. I will conclude that the present structures are largely fit to deal with the challenges AI technologies are posing. In some areas sector specific revisions of the law may be advisable, particularly concerning non-discrimination and product liability.

Keywords: Artificial intelligence, medical law and ethics, fairness, data protection, accountability, negligence, liability, product liability
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Daniel Schönberger, Deep Copyright: Up- and Downstream Questions Related to Artificial Intelligence (AI) and Machine Learning (ML), Zeitschrift fuer Geistiges Eigentum / Intellectual Property Journal, Volume 10, Number 1, March 2018, pp. 35-58(24), DOI: https://doi.org/10.1628/zge-2018-0003

Artificial intelligence (AI) systems are increasingly capable of taking over tasks, that until recently required cognitive abilities such as the creation of works. Already commercial applications… Mehr anzeigen

Daniel Schönberger, Deep Copyright: Up- and Downstream Questions Related to Artificial Intelligence (AI) and Machine Learning (ML), Zeitschrift fuer Geistiges Eigentum / Intellectual Property Journal, Volume 10, Number 1, March 2018, pp. 35-58(24), DOI: https://doi.org/10.1628/zge-2018-0003

Artificial intelligence (AI) systems are increasingly capable of taking over tasks, that until recently required cognitive abilities such as the creation of works. Already commercial applications reach the market, whose outputs would arguably be considered as creative, if produced by a human author. Also, systems have become capable of translating all kinds of text including prose between dozens of languages. One enabler for this development is (deep) machine learning (ML), which may require input from copyrighted works to train the respective models in becoming "creative". The present essay discusses some of the legal and philosophical issues that arise from these developments, looking both at the status of the "downstream" generated works, and the possible constraints that copyright law might impose on the materials the systems need for learning and hence for their "upstream" modelling.

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Abstract
Artificial intelligence (AI) systems are increasingly capable of taking over tasks that until recently required cognitive abilities, such as the creation of literary texts, melodies or images. Already commercial applications reach the market, whose outputs would arguably be considered as creative, if produced by a human author. Also, systems have become capable of translating all kinds of text including prose between dozens of languages. One enabler for this development is (deep)… Mehr anzeigen

Abstract
Artificial intelligence (AI) systems are increasingly capable of taking over tasks that until recently required cognitive abilities, such as the creation of literary texts, melodies or images. Already commercial applications reach the market, whose outputs would arguably be considered as creative, if produced by a human author. Also, systems have become capable of translating all kinds of text including prose between dozens of languages. One enabler for this development is (deep) machine learning (ML), which may require input from copyrighted works to train the respective models in becoming “creative”. The present essay discusses some of the legal and philosophical issues that arise from these developments, looking both at the status of the “downstream” generated works, and the possible constraints that copyright law might impose on the materials the systems need for learning and hence for their “upstream” modelling.

Keywords: Copyright, artificial intelligence, AI, machine learning, ML, robolaw, robophilosophy Weniger anzeigen