Title page 1

Contents 3

Executive Summary 6

01. Introduction 9

02. Methodology and Data Collection 16

03. Framework for Responsible AI in Cities 21

3.1. Context of Responsible AI in cities 22

3.2. Benefits, Challenges, Opportunities, and Risks (BCOR) of Responsible AI in cities 26

3.3. Governance and Partnerships 41

3.4. AI Capabilities in cities 59

04. AI for Resilient, Inclusive, and Sustainable Cities 66

05. Conclusion and Key Recommendations for Responsible AI in Cities 76

5.1. Capacities gaps and needs summary 77

5.2. Key recommendations for AI in cities 78

1. AI for local government and public services 79

2. Responsible AI in cities 80

3. Capabilities of Responsible AI in cities 81

References 83

Tables 5

Table 1. Global survey dimensions 17

Table 2. Main themes and questions of the EGM 19

Figures 4

Figure 1. A four-step approach for the Global Assessment of Responsible AI 17

Figure 2. Visual representation of global survey responses and collected case studies 18

Figure 3. Analytical framework for Responsible AI in cities 22

Figure 4. Interest toward AI technology by level of adoption of AI and by continent 23

Figure 5. Distribution of AI in cities case studies based on AI typologies 23

Figure 6. Knowledge of AI in cities based on the professional level of respondents 24

Figure 7. Motivations for adopting AI in cities 27

Figure 8. Potential AI use-cases for cities interests 28

Figure 9. Areas benefiting of AI implementation in cities 29

Figure 10. Benefits of AI implementation in cities 30

Figure 11. Factors hindering the adoption of AI in cities 33

Figure 12. Challenges of AI implementation in cities 34

Figure 13. AI risks in implementing AI in cities 37

Figure 14. Ways used by cities to govern AI 41

Figure 15. Available AI governance measures in cities 42

Figure 16. Number of city cases with available, partially available, and not available governance of AI 43

Figure 17. Alignment of city's AI strategy with national strategy 44

Figure 18. Alignment of city's AI strategy with national strategy and SDGs 44

Figure 19. Factors included in the city's AI strategy 45

Figure 20. Results showing policy frameworks with personal data protection 46

Figure 21. Status of AI regulatory frameworks in cities 46

Figure 22. Goals of AI-related legislation in cities 47

Figure 23. Availability of legal framework to regulate AI in cities 48

Figure 24. Availability of legal framework to regulate AI in cities 48

Figure 25. Stakeholders involved in AI policies 50

Figure 26. Citizens involvement in AI system development and deployment 51

Figure 27. Significance level of stakeholders in the AI implementation 52

Figure 28. Status of AI ecosystem in cities 53

Figure 29. Challenges of AI partnership in cities 55

Figure 30. Requirements in the procurement processes of AI solutions in cities 56

Figure 31. AI capabilities to implement, use and govern AI in cities 59

Figure 32. Availability of AI talents and competence in cities 60

Figure 33. City's initiatives to strengthen AI knowledge 61

Figure 34. Ways of funding AI projects in cities 62

Figure 35. Status of infrastructure resources available to support AI implementation 63

Figure 36. Data status in cities 63

Figure 37. AI contribution to economic sustainability 67

Figure 38. AI contributions to environmental sustainability 68

Figure 39. AI Contributions to social and institutional sustainability 70

Figure 40. AI Contributions to social and institutional sustainability 71

Figure 41. AI for cities compliance with the SDGs 72

Figure 42. Core values of AI solutions in cities 73

Figure 43. Accessibility and inclusion of AI-based solutions in cities 74

Figure 44. Summary of the capacities needs and gaps 77

Boxes 28

Box 1. Opportunities of AI in Dublin Beat in Dublin, Ireland 28

Box 2. Benefits of AI as demonstrated in the City Brain in Hangzhou, China 30

Box 3. Challenges of AI as demonstrated in the Sowing App and Commodity Price Forecasting Model in Andhra Pradesh and Karnataka, India 35

Box 4. Risks of AI as demonstrated in automated social protection services in Trelleborg, Sweden 39

Box 5. AI strategy, policy and regulation as demonstrated in Barcelona, Spain 49

Box 6. AI Ecosystem in action: AI speakers in the city of Seodaemun-gu (Seoul, South Korea) 54

Box 7. AI Ecosystem in action: KIRA COVID-19 chatbot and data management platform (Quezon City, Philippines) 54

Box 8. Navigating partnership challenges for AI-powered energy optimization in copenhagen 55

Box 9. Enhancing land monitoring with BEAM: a showcase of AI capabilities in eThekwini, South Africa 64

Box 10. BencanaBot - Harnessing AI for urban resilience in Jakarta, Indonesia 69

Box 11. AI for inclusivity - Transforming urban accessibility in Mexican cities with Project Sidewalk 75