3. Traceable

The department's AI capabilities will be developed and deployed such that relevant personnel possess an appropriate understanding of the technology, development processes and operational methods applicable to AI capabilities, including with transparent and auditable methodologies, data sources and design procedures and documentation.
Principle: DoD's AI ethical principles, Feb 24, 2020

Published by Department of Defense (DoD), United States

Related Principles

3. Traceable.

DoD’s AI engineering discipline should be sufficiently advanced such that technical experts possess an appropriate understanding of the technology, development processes, and operational methods of its AI systems, including transparent and auditable methodologies, data sources, and design procedure and documentation.

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

· 1.4. Robustness, security and safety

a) AI systems should be robust, secure and safe throughout their entire lifecycle so that, in conditions of normal use, foreseeable use or misuse, or other adverse conditions, they function appropriately and do not pose unreasonable safety risk. b) To this end, AI actors should ensure traceability, including in relation to datasets, processes and decisions made during the AI system lifecycle, to enable analysis of the AI system’s outcomes and responses to inquiry, appropriate to the context and consistent with the state of art. c) AI actors should, based on their roles, the context, and their ability to act, apply a systematic risk management approach to each phase of the AI system lifecycle on a continuous basis to address risks related to AI systems, including privacy, digital security, safety and bias.

Published by The Organisation for Economic Co-operation and Development (OECD) in OECD Principles on Artificial Intelligence, May 22, 2019

3. Provision of Trusted Products and Services

Sony understands the need for safety when dealing with products and services utilizing AI and will continue to respond to security risks such as unauthorized access. AI systems may utilize statistical or probabilistic methods to achieve results. In the interest of Sony’s customers and to maintain their trust, Sony will design whole systems with an awareness of the responsibility associated with the characteristics of such methods.

Published by Sony Group in Sony Group AI Ethics Guidelines, Sep 25, 2018

3. Scientific Integrity and Information Quality

The government’s regulatory and non regulatory approaches to AI applications should leverage scientific and technical information and processes. Agencies should hold information, whether produced by the government or acquired by the government from third parties, that is likely to have a clear and substantial influence on important public policy or private sector decisions (including those made by consumers) to a high standard of quality, transparency, and compliance. Consistent with the principles of scientific integrity in the rulemaking and guidance processes, agencies should develop regulatory approaches to AI in a manner that both informs policy decisions and fosters public trust in AI. Best practices include transparently articulating the strengths, weaknesses, intended optimizations or outcomes, bias mitigation, and appropriate uses of the AI application’s results. Agencies should also be mindful that, for AI applications to produce predictable, reliable, and optimized outcomes, data used to train the AI system must be of sufficient quality for the intended use.

Published by The White House Office of Science and Technology Policy (OSTP), United States in Principles for the Stewardship of AI Applications, Jan 13, 2020

6. Flexibility

When developing regulatory and non regulatory approaches, agencies should pursue performance based and flexible approaches that can adapt to rapid changes and updates to AI applications. Rigid, design based regulations that attempt to prescribe the technical specifications of AI applications will in most cases be impractical and ineffective, given the anticipated pace with which AI will evolve and the resulting need for agencies to react to new information and evidence. Targeted agency conformity assessment schemes, to protect health and safety, privacy, and other values, will be essential to a successful, and flexible, performance based approach. To advance American innovation, agencies should keep in mind international uses of AI, ensuring that American companies are not disadvantaged by the United States’ regulatory regime.

Published by The White House Office of Science and Technology Policy (OSTP), United States in Principles for the Stewardship of AI Applications, Jan 13, 2020