To realize Society 5.0 and continuous innovation in which people evolve along with AI, it is necessary to account for national, industry academia, and public private borders, race, sex, nationality, age, political and religious beliefs, etc. Beyond these boundaries, through a Global perspective we must promote diversification and cooperation between industry academia public private sectors, through the development of human capabilities and technology.
To encourage mutual collaboration and partnership between universities, research institutions and private sectors, and the flexible movement of talent.
To implement AI efficiently and securely in society, methods for confirming the quality and reliability of AI and for efficient collection and maintenance of data utilized in AI must be promoted. Additionally, the establishment of AI engineering should also be promoted. This engineering includes methods for the development, testing and operation of AI.
To ensure the sound development of AI technology, it is necessary to establish an accessible platform in which data from all fields can be mutually utilized across borders with no monopolies, while ensuring privacy and security. In addition, research and development environments should be created in which computer resources and highspeed networks are shared and utilized, to promote international collaboration and accelerate AI research.
To promote implementation of AI technology, governments must promote regulatory reform to reduce impeding factors in AI related fields.
Published by: Defense Innovation Board (DIB), Department of Defense (DoD), United States in AI Ethics Principles for DoD
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
IEEE supports the inclusion of ethical considerations in the design and deployment of autonomous and intelligent systems.
Autonomous and Intelligent systems (A IS) are systems that are capable of adaption and learning based on feedback and data from their environment. A IS hold great promise to benefit society in applications domains as diverse as transportation, health and social care, environmental preservation, enterprise productivity, communication network optimization, power grid adaptation and management, agriculture, manufacturing, and entertainment. Recent success in machine learning, signal processing, planning algorithms, digital sensing, embedded systems, cloud computing, as well as voice, image and pattern analysis have greatly accelerated application of A IS. They hold great promise to benefit society, but they also present potential new social, legal and ethical challenges, with corresponding new requirements to address issues of systemic risk, diminishing trust, privacy challenges and issues of data transparency, ownership and agency.
Therefore, there is a compelling need for developers and operators of A IS systems to maintain awareness of and employ consensus based global best technical practices and standards that recognize and align end users’ and citizen’s values when building and deploying A IS. To that end:
1.3 Robust and Representative Data
Published by: Information Technology Industry Council (ITI) in AI Policy Principles
To promote the responsible use of data and ensure its integrity at every stage, industry has a responsibility to understand the parameters and characteristics of the data, to demonstrate the recognition of potentially harmful bias, and to test for potential bias before and throughout the deployment of AI systems. AI systems need to leverage large datasets, and the availability of robust and representative data for building and improving AI and machine learning systems is of utmost importance.
Artificial intelligence should be safe and reliable. We are dedicated to accentuating technical robustness and security throughout the research process, providing a secure and reliable system to improve the ability to prevent attack and conduct self repair.