Fostering an including AI-enabling ecosystem (Principle 2.2)
Governments should foster accessible AI ecosystems with digital infrastructure and technologies, and mechanisms to share data and knowledge.
Governments should foster the development of, and access to, an inclusive, dynamic, sustainable, and interoperable digital ecosystem for trustworthy AI. Such an ecosystem includes inter alia, data, AI technologies, computational and connectivity infrastructure, and mechanisms for sharing AI knowledge, as appropriate. In this regard, governments should consider promoting mechanisms, such as data trusts, to support the safe, fair, legal and ethical sharing of data.
From the AI Wonk
Rationale for this principle
The development of trustworthy AI requires an enabling ecosystem. This recommendation calls on governments – engaging with the private sector as appropriate – to work towards providing, or promoting the provision of, the infrastructure and digital technologies for AI and the mechanisms for AI knowledge sharing, taking into account their national frameworks.
The necessary digital technologies and infrastructure include access to affordable high-speed broadband networks and services, computing power and data storage – as well as supporting data-generating technologies such as the Internet-of-Things (IoT). For example, recent AI advances can be attributed, in part, to the exponential increase in computational speed including with graphics-processing unit resources. Appropriate mechanisms for sharing AI knowledge, including data, code, algorithms, models, research, and know-how, are also required to understand and participate in the AI system lifecycle. Such mechanisms must respect privacy, intellectual property and other rights. Open source tools and high-quality training datasets for managing and using AI, which allow for the diffusion of AI technology and crowdsourcing solutions to software bugs play a key role in AI development.
When developing means of data sharing, such as data trusts or trusted third parties, governments should pay attention to risks related to data access and sharing: risks to individuals (including consumers), organisations and countries of sharing data may include confidentiality and privacy breaches, risks to intellectual property rights, data protection, competition and commercial interests, as well as potential national security and digital security risks. When it comes to the datasets themselves, and in conjunction with recommendation 2.1, governments are invited to promote and utilise datasets that are as inclusive, diverse and representative as possible.
The recommendations for policymakers draw special attention to policies for small and medium-sized enterprises (SMEs): to facilitate SME access to data, AI technologies and relevant infrastructure (such as connectivity, computing capacities and cloud platforms) in order to foster digital entrepreneurship, competition and innovation through the adoption of AI.
Other principles
Inclusive growth, sustainable development and well-being
Human rights and democratic values, including fairness and privacy
Transparency and explainability
Robustness, security and safety
Accountability
Investing in AI research and development
Fostering an inclusive AI-enabling ecosystem
Shaping an enabling interoperable governance and policy environment for AI
Building human capacity and preparing for labour market transition
