Guidelines and Regulatory Framework for Machine Learning in Aviation

2022 ◽  
Author(s):  
Christoph Torens ◽  
Umut Durak ◽  
Johann C. Dauer
2020 ◽  
Vol 27 (3) ◽  
pp. 242-258
Author(s):  
Fedele Bonifazi ◽  
Elisabetta Volpe ◽  
Giuseppe Digregorio ◽  
Viviana Giannuzzi ◽  
Adriana Ceci

Abstract The use of machine learning (ML) in medicine is becoming increasingly fundamental to analyse complex problems by discovering associations among different types of information and to generate knowledge for medical decision support. Many regulatory and ethical issues should be considered. Some relevant EU provisions, such as the General Data Protection Regulation, are applicable. However, the regulatory framework for developing and marketing a new health technology implementing ML may be quite complex. Other issues include the legal liability and the attribution of negligence in case of errors. Some of the above-mentioned concerns could be, at least partially, resolved in case the ML software is classified as a ‘medical device’, a category covered by EU/national provisions. Concluding, the challenge is to understand how sustainable is the regulatory system in relation to the ML innovation and how legal procedures should be revised in order to adapt them to the current regulatory framework.


2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.


2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  

2020 ◽  
Author(s):  
Marc Peter Deisenroth ◽  
A. Aldo Faisal ◽  
Cheng Soon Ong
Keyword(s):  

Author(s):  
Lorenza Saitta ◽  
Attilio Giordana ◽  
Antoine Cornuejols

Author(s):  
Shai Shalev-Shwartz ◽  
Shai Ben-David
Keyword(s):  

2006 ◽  
Author(s):  
Christopher Schreiner ◽  
Kari Torkkola ◽  
Mike Gardner ◽  
Keshu Zhang

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