Transparency is key to building and maintaining citizen’s trust in the developers of AI systems and AI systems themselves. Both technological and business model transparency matter from an ethical standpoint. Technological transparency implies that AI systems be auditable, comprehensible and intelligible by human beings at varying levels of comprehension and expertise. Business model transparency means that human beings are knowingly informed of the intention of developers and technology implementers of AI systems. Explicability is a precondition for achieving informed consent from individuals interacting with AI systems and in order to ensure that the principle of explicability and non maleficence are achieved the requirement of informed consent should be sought. Explicability also requires accountability measures be put in place. Individuals and groups may request evidence of the baseline parameters and instructions given as inputs for AI decision making (the discovery or prediction sought by an AI system or the factors involved in the discovery or prediction made) by the organisations and developers of an AI system, the technology implementers, or another party in the supply chain.

Published by The European Commission’s High-Level Expert Group on Artificial Intelligence in Draft Ethics Guidelines for Trustworthy AI, Dec 18, 2018

Published by Tencent Research Institute in "ARCC": An Ethical Framework for Artificial Intelligence, Sep 18, 2018

Published by Tencent Research Institute in "ARCC": An Ethical Framework for Artificial Intelligence, Sep 18, 2018

Published by Tencent Research Institute in "ARCC": An Ethical Framework for Artificial Intelligence, Sep 18, 2018

AI shall not harm human beings. AI systems must be secure, applicable and controllable. Personal privacy should be protected and data breach and abuse prevented. AI algorithms must be traceable and transparent and there should be no algorithm discrimination;

Published by Center for International Strategy and Security, Tsinghua University (Tsinghua CISS) in Six AI Principles proposed by Mme Fu Ying, Jan 23, 2019