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3.2 AI principles enablers (adopted by the city)

The Guideline on Ethical Development and Use of AI provides a self-assessment checklist for
users to establish and adopt AI principles. It involves in several aspects, including: AI strategy and
governance, risk assessment and human oversight, development of AI models and management
of AI systems and communication and engagement with stakeholders. Data Protection Principles
has also been illustrated in this document. The principles cover the entire life cycle of the handling
of personal data, including purpose and manner of collection, accuracy and duration of retention,
use of data, data security, openness and transparency, and access and correction.

3.3 AI principles governance mechanism (adopted by the city)

The Ethical AI Framework provide guidance to IT planners, system analysts, system architects and
data scientists to understand ethical AI principles and practices, initiate discussions on the impact
of AI, adopt standardized practices and terminology, and perform AI assessment. Table 1 contains
an example.

Table 1: Example of AI principles governance mechanism for users
Project strategy Practical guide to establish AI strategy and to ensure AI
principles are embedded.
Project planning Practical guide along with the risk gating criteria to
IT Planners and ensure ethical AI requirements are met and impacts are
executives
assessed.
Project ecosystem Practical guide to evaluate existing technology landscape
and deploy third party AI applications.
Project development To ensure data validation, documentation, biased data,
data privacy, etc. are considered for ethical AI.
System analysts,
system architects System development To ensure AI principles are adopted in the deployment of
and data AI applications.
scientists
System operation and To ensure actions including escalation, continuous review
monitoring and compliance checking are considered.

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