Recent · FABRICS, Emerging AI Readiness, by Alex Comninos and Martin Konzett, First Edition, 2018, ISBN 978-3-200-05921-4

A lot of industries seem to be overwhelmed by the rise of artificial intelligence (AI). Some proponents dream of utopias, while some opponents have dystopian nightmares. There is a lack of consensus in interpretations of the current legal and regulatory environments covering the implementation of computer systems leveraging AI and the related concepts of machine learning and deep learning. Interpreting, implementing and complying with the regulatory environment is not possible without unpacking the foundations of automated decision making.

FABRICS is an unpacking of artificial intelligence and an investigation of the regulatory challenges to AI and artificial decision making, in particular the “right to explanation” arising from the EU General Regulation on Data Protection (GDPR). FABRICS unpacks the challenges of explaining automated decisions and points to the need for privacy-by-design in the development of tools that use AI.

“FABRICS is a timely and helpful contribution to both the empowering prospects and complex challenges of human rights and AI.“ – Joy Liddicoat, Researcher, University of Otago

FABRICS also tries to address some of the challenges of AI through design: a system of warning signs that inform people of the presence of AI is outlined as a basis for activism, as well as inspiration for privacy-by-design approaches to AI. It also includes a piece of design fiction, which helps unpack the challenges of processing personal data on the edge of cyberspace.

Alex Comninos and Martin Konzett are collaborating as an ad hoc research unit under the working title VOUS. In the context of increasing industry and consumer demand for Artificial Intelligence (AI), VOUS aims to explore and unpack AI in all of its forms. Investigations can be found online, across social media, archived as GIT repositories, and are also available as paperback.

Download a copy of FABRICS, Emerging AI Readiness, by Alex Comninos and Martin Konzett, here.

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