Page 26 - U4SSC Guiding principles for artificial intelligence in cities

Enabler Enabler Examples

Co-created Policies National or local governments can develop R&D (research and development)
and innovation policies on AI, fostering AI applications with positive impacts on
inhabitants’ daily lives, increasing public and private investment and promoting
the development of trustworthy AI.
AI policies can be co-created with city stakeholders to build public confidence
and legitimacy in AI principles. The city stakeholders that may participate in
policy co-creation include:
• City officials;
• Experts related to AI principles, technical AI aspects, human rights, data, etc.;
• Scientists (social, humanities, data);
• Target inhabitants and community groups, councils, associations, etc.
• Private sector experts; and
• NGOs.
Data Governance A robust national or local data governance regulatory framework, potentially
including data privacy and data protection, will assist and facilitate addressing
data concerns in AI implementations.

Cities can potentially capitalize on existing city and national data governance
frameworks as well as cross-border ones (e.g., European Union’s General Data
Protection Regulation or GDPR, Cross-Border Privacy Rules or CBPR developed
by the APEC - Asia-Pacific Economic Cooperation)
Information Security Existing national or local information security and cybersecurity policies will
& Cybersecurity help to address safety and security concerns in AI implementations. Cities
can potentially undertake other security enhancement and incentivisation
mechanisms such as:

• A dedicated certification process for AI Secure applications;
• Transparency of security aspects of AI principles implementation processes;
and
• An open collaboration platform for AI Security issues.

4.2 AI capacity building

AI applications in cities is a relatively new field. Moreover, AI principles are a novel topic requiring
new skills and insights in the context of AI technology. Therefore, capacity building in AI principles
is an important enabler for cities.

Capacity-building programmes can help establish new skills and knowledge for effective
implementation of AI principles. Capacity-building programmes include formal and informal
learning, preparation and conducting of training programmes, developing skills enhancement
tools and related instruments (e.g., toolkits). They can improve inclusion and educate future talent
in the city.

Formal training can help boost the relatively advanced skills of technical experts and informal
education can help build trust and reinforce AI skills.

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