1. Accountability:

AI designers and developers are responsible for considering AI design, development, decision processes, and outcomes.
Principle: Everyday Ethics for Artificial Intelligence: Five Areas of Ethical Focus, Sep 6, 2018

Published by IBM

Related Principles

(i) Accountability:

Arrangements should be developed that will make possible to attribute accountability for AI driven decisions and the behaviour of AI systems.

Published by The Extended Working Group on Ethics of Artificial Intelligence (AI) of the World Commission on the Ethics of Scientific Knowledge and Technology (COMEST), UNESCO in Suggested generic principles for the development, implementation and use of AI, Mar 21, 2019

1. Responsible.

Human beings should exercise appropriate levels of judgment and remain responsible for the development, deployment, use, and outcomes of DoD AI systems.

Published by Defense Innovation Board (DIB), Department of Defense (DoD), United States in AI Ethics Principles for DoD, Oct 31, 2019

• Foster Innovation and Open Development

To better understand the impact of AI and explore the broad diversity of AI implementations, public policy should encourage investment in AI R&D. Governments should support the controlled testing of AI systems to help industry, academia, and other stakeholders improve the technology. [Recommendations] • Fuel AI innovation: Public policy should promote investment, make available funds for R&D, and address barriers to AI development and adoption. • Address global societal challenges: AI powered flagship initiatives should be funded to find solutions to the world’s greatest challenges such as curing cancer, ensuring food security, controlling climate change, and achieving inclusive economic growth. • Allow for experimentation: Governments should create the conditions necessary for the controlled testing and experimentation of AI in the real world, such as designating self driving test sites in cities. • Prepare a workforce for AI: Governments should create incentives for students to pursue courses of study that will allow them to create the next generation of AI. • Lead by example: Governments should lead the way on demonstrating the applications of AI in its interactions with citizens and invest sufficiently in infrastructure to support and deliver AI based services. • Partnering for AI: Governments should partner with industry, academia, and other stakeholders for the promotion of AI and debate ways to maximize its benefits for the economy.

Published by Intel in AI public policy principles, Oct 18, 2017

• Require Accountability for Ethical Design and Implementation

The social implications of computing have grown and will continue to expand as more people have access to implementations of AI. Public policy should work to identify and mitigate discrimination caused by the use of AI and encourage designing in protections against these harms. [Recommendations] • Standing for “Accountable Artificial Intelligence”: Governments, industry and academia should apply the Information Accountability Foundation’s principles to AI. Organizations implementing AI solutions should be able to demonstrate to regulators that they have the right processes, policies and resources in place to meet those principles. • Transparent decisions: Governments should determine which AI implementations require algorithm explainability to mitigate discrimination and harm to individuals.

Published by Intel in AI public policy principles, Oct 18, 2017

10. Responsibility, accountability and transparency

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