I will discuss relevant AI thrusts at NIST on health care informatics, focusing on the use of machine learning, knowledge representation and natural language processing. I will also discuss the need for explanations in AI systems (XAI) and current state of the art in medical XAI.
Rob wants to argue that if intent is linked to an incorrect assessment of identity, and thus not central to an ethics of behaviour, then this opens up an actionable set of actors actually at play in the digtial (IoT, 5G, AI) namely: objects (with added connectivity like NFC), machines with built in connectivity, animals & plants (as ecosystems) and humans alike , as they can be treated as entities.
It has never been more important that we keep a sharp eye out on the development of this field and how it is shaping our society and interactions with each other. With this inaugural edition of the State of AI Ethics we hope to bring forward the most important developments that caught our attention at the Montreal AI Ethics Institute this past quarter. Our goal is to help you navigate this ever-evolving field swiftly and allow you and your organization to make informed decisions.
With OpenMined, an AI model can be governed by multiple owners and trained securely on an unseen, distributed dataset.The mission of the OpenMined community is to create an accessible ecosystem of tools for private, secure, multi-owner governed AI
OpenMined: open source to make privacy-preserving of AI technologies Leer más »
Learn the basics of secure and private AI techniques, including federated learning and secure multi-party computation. In this talk, Andrew Trask of OpenMined highlights the importance of privacy preserving machine learning, and how to use privacy-focused tools like PySyft.
To improve the performance of U-Net on various segmentation tasks, we propose a novel architecture called DoubleU-Net, which is a combination of two U-Net architectures stacked on top of each other.
DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation Leer más »
Multi-presenter format with exciting Speakers from the current European ICT research projects AI4EU (www.ai4eu.eu) and Helios (helios-social.com/) as well as Guest Speakers.
«ENISA CSIRT training material was introduced in 2008. In 2012, 2013 and 2014 it was complemented with new exercise scenarios containing essential material for success in the CSIRT community and in the field of information security. In these pages you will find the ENISA CSIRT training material, containing Handbooks for teachers, Toolsets for students and Virtual Images to support hands on training sessions. » The materials continue to be updated in 2020 and are appropriate for use by cybersecurity specialists and decision-makers.
We survey 146 papers analyzing «bias» in NLP systems, finding that their motivations are often vague, inconsistent, and lacking in normative reasoning, despite the fact that analyzing «bias» is an inherently normative process.
Language (Technology) is Power: A Critical Survey of «Bias» in NLP Leer más »
This lecture will outline the fundamental ML processes involved in medical image analysis. Achieving prediction and classification for CAD applications will also be discussed. Some preliminary ideas of 3D reconstruction and viewing as applied in medical image analysis will also be presented.
Machine Learning for Medical Imaging Analysis Demystified Leer más »