Published by IBM in Principles for Trust and Transparency, May 30, 2018

Principle: AI system designers and builders need to apply a user centric approach to the technology. They need to consider their collective responsibility in building AI systems that will not pose security risks to the Internet and Internet users. Recommendations: Adopt ethical standards: Adherence to the principles and standards of ethical considerations in the design of artificial intelligence, should guide researchers and industry going forward. Promote ethical considerations in innovation policies: Innovation policies should require adherence to ethical standards as a pre requisite for things like funding.

Published by Internet Society, "Artificial Intelligence and Machine Learning: Policy Paper" in Guiding Principles and Recommendations, Apr 18, 2017

a. Build trust by ensuring that designers and operators are responsible and accountable for their systems, applications and algorithms, and to ensure that such systems, applications and algorithms operate in a transparent and fair manner. b. To make available externally visible and impartial avenues of redress for adverse individual or societal effects of an algorithmic decision system, and to designate a role to a person or office who is responsible for the timely remedy of such issues. c. Incorporate downstream measures and processes for users or stakeholders to verify how and when AI technology is being applied. d. To keep detailed records of design processes and decision making.

Published by Personal Data Protection Commission (PDPC), Singapore in A compilation of existing AI ethical principles (Annex A), Jan 21, 2020

Published by ACM US Public Policy Council (USACM) in Principles for Algorithmic Transparency and Accountability, Jan 12, 2017

Published by World Health Organization (WHO) in Key ethical principles for use of artificial intelligence for health, Jun 28, 2021