Indonesia-National AI Strategy

In 2020, Indonesia published its National AI strategy.

This National AI Strategy, titled “Strategi Nasional Kecerdasan Artifisial 2020-2045,” serves as a guiding framework for the development and implementation of AI technologies in Indonesia. It aims to direct efforts across various sectors, including government, industry, education, and research, to ensure that AI contributes positively to the nation’s economy and society.

Contents-

CHAPTER 1: INTRODUCTION 13
1.1 Background 13
1.2 SWOT Analysis and National Artificial Intelligence Strategy 21
1.3 Framework of the National Artificial Intelligence Strategy 29

CHAPTER 2: VISION AND MISSION 31
2.1 Vision of Artificial Intelligence in Indonesia 31
2.2 Mission of Artificial Intelligence in Indonesia 32

CHAPTER 3: ETHICS AND POLICY OF ARTIFICIAL INTELLIGENCE IN INDONESIA 39
3.1 Strategic Issues 39
3.2 Initiative Programs 45

CHAPTER 4: DEVELOPMENT OF ARTIFICIAL INTELLIGENCE TALENT IN INDONESIA 49
4.1 Strategic Issues 49
4.2 Initiative Programs 53

CHAPTER 5: DATA AND INFRASTRUCTURE 61
5.1 Strategic Issues 61
5.2 Initiative Programs 65

CHAPTER 6: RESEARCH AND INDUSTRY INNOVATION 79
6.1 Strategic Issues 80
6.2 Initiative Programs 83

CHAPTER 7: PRIORITY AREAS OF ARTIFICIAL INTELLIGENCE 113
7.1 Priority Area in Health 115
7.2 Priority Area in Bureaucratic Reform 121
7.3 Priority Area in Education and Research 126
7.4 Priority Area in Food Security 131
7.5 Priority Area in Smart Mobility and Cities 135

CHAPTER 8: ACCELERATION PROGRAMS AND ROADMAP 139
8.1 Acceleration Program for Artificial Intelligence 139
8.2 Roadmap for Artificial Intelligence Programs 151
8.3 Institutional Framework for the National Artificial Intelligence

Chapter 1

Chapter  1 of Indonesia’s National AI Strategy focuses on the introduction to the national strategy for artificial intelligence in Indonesia. The chapter is divided into three main sections:

  1.  Background: This section discusses the significance of artificial intelligence (AI) in the contemporary world. It emphasizes the need for Indonesia to develop a coherent strategy in AI to harness its potential effectively. The background highlights the global advancements in AI and the necessity for Indonesia to catch up with these developments to improve national competitiveness. It also outlines the implications of AI on various sectors such as economy, education, healthcare, and governance, detailing how AI can drive innovation and efficiency.
  2. SWOT Analysis and National Strategy for Artificial Intelligence: In this section, a SWOT analysis is presented, which evaluates the Strengths, Weaknesses, Opportunities, and Threats related to AI in Indonesia.
    • Strengths might include a large population with a growing interest in technology, a young workforce, and existing investments in digital infrastructure.
    • Weaknesses could encompass the lack of skilled professionals, insufficient research and development (R&D) funding, and a fragmented regulatory framework.
    • Opportunities may highlight the potential for AI to enhance productivity, improve public services, and stimulate economic growth.
    • Threats could involve ethical concerns, data privacy issues, and the risk of job displacement due to automation.
  1. Framework of the National Strategy for Artificial Intelligence: This section outlines the framework that will guide the implementation of the national strategy. It includes the vision and mission for AI in Indonesia, which aim to create a conducive environment for AI development and application. The framework emphasizes collaboration among various stakeholders, including government, academia, and industry, to foster innovation and ethical practices in AI deployment.

Chapter 2

Chapter 2 of Indonesia’s National AI Strategy focuses on the vision and mission of Artificial Intelligence (AI) in Indonesia. It outlines the long-term aspirations and the specific objectives that guide the development and implementation of AI technologies in the country.

 Vision of Artificial Intelligence in Indonesia

The vision emphasizes the goal of making Indonesia a leading nation in the field of AI by 2045. This vision is rooted in the belief that AI can significantly contribute to various sectors, enhancing productivity, efficiency, and overall quality of life. The chapter underscores the importance of aligning AI advancements with national interests and ethical standards.

 

 Mission of Artificial Intelligence in Indonesia

The mission comprises several objectives aimed at achieving the vision:

  1. Enhancing National Competitiveness: Developing AI capabilities to improve the competitiveness of Indonesian industries on a global scale.
  2. Promoting Innovation: Encouraging research and innovation in AI technologies that cater to local needs and challenges.
  3. Ensuring Ethical Standards: Establishing ethical guidelines for the development and use of AI, ensuring that it aligns with the values of Pancasila, the foundational philosophical theory of Indonesia.
  4. Building Talent: Fostering a skilled workforce capable of driving AI initiatives through education and training programs.
  5. Collaboration: Promoting collaboration among government, academia, and industry stakeholders to create a robust ecosystem for AI development.

Chapter 3

Chapter 3 of Indonesia’s National AI Strategy focuses on the strategic issues and initiatives related to the ethical implications and policy frameworks surrounding the development and application of artificial intelligence (AI) in Indonesia.

3.1 Strategic Issues

This section outlines various strategic issues that arise with the implementation of AI technologies. It emphasizes the importance of establishing ethical standards and frameworks to guide the development and use of AI systems. Key points include:

  • Data Ethics: The need to ensure ethical data sharing practices that adhere to national legal frameworks, including Pancasila (the philosophical foundation of Indonesia) and the 1945 Constitution.
  • Institutional Policies: The necessity of formulating institutional policies that orchestrate the national AI innovation ecosystem.
  • Ethics Council Formation: The establishment of an Ethics Council for Data to oversee and regulate data sharing practices, ensuring that ethical considerations are integrated into AI usage.
  • Data Collection and Sharing: Policies must be prepared for the collection and sharing of data, particularly from the One Data Indonesia initiative, which aims to enhance research and experimentation in AI.

3.2 Initiative Programs

This section details several initiative programs aimed at addressing the ethical and policy challenges mentioned:

  1. Data Ethics Implementation: The implementation of ethical data sharing practices that align with national regulations.
  2. Institutional Policy Frameworks: Developing comprehensive institutional policies to manage and orchestrate the national AI ecosystem effectively.
  3. Establishment of Data Ethics Council: Creating a council responsible for defining and enforcing ethical standards related to data sharing.
  4. Policy Development for Data Use: Preparing policies that facilitate the ethical collection and sharing of data for AI research and development.

Chapter 4

Chapter 4 emphasizes the importance of developing AI talent in Indonesia to support the national strategy for artificial intelligence. By addressing the identified strategic issues and implementing the proposed initiatives, Indonesia can build a robust pipeline of skilled professionals capable of driving innovation and growth in the AI sector..

4.1 Strategic Issues

The chapter begins by identifying several strategic issues related to the development of AI talent in Indonesia. These issues include:

  1. Talent Shortage: There is a notable gap between the demand for skilled AI professionals and the available talent in the market. This shortage is hindering the growth of the AI sector in the country.
  2. Quality of Education: The current education system does not adequately prepare students with the necessary skills and knowledge in AI. This inadequacy is evident in both formal education and non-formal training programs.
  3. Awareness and Interest: There is a lack of awareness and interest in AI-related fields among students, which needs to be addressed to cultivate future talent.
  4. Industry Collaboration: There is a need for stronger collaboration between educational institutions and the industry to ensure that the curriculum aligns with the needs of the market.

4.2 Initiative Programs

To address these issues, the chapter proposes several initiative programs:

  1. Curriculum Development: The development of a curriculum that emphasizes AI education from early schooling through higher education is essential. This curriculum should include foundational knowledge in data science, machine learning, and programming.
  2. Training Programs: The establishment of training programs and workshops that focus on AI skills for various levels of education, including vocational training, is necessary to upskill the existing workforce.
  3. Scholarships and Incentives: Providing scholarships and financial incentives for students pursuing degrees in AI and related fields can help attract more talent into the sector.
  4. Industry Partnerships: Collaborations between universities and industry players can facilitate internships and practical experience for students, making them more job-ready upon graduation.
  5. Public Awareness Campaigns: Initiatives to raise public awareness about the importance of AI and the career opportunities it presents can inspire more students to pursue careers in this field.
  6. Research and Development Support: Encouraging research in AI through grants and funding can help develop innovative solutions and foster a culture of inquiry and experimentation.

Chapter 5

 Chapter 5 provides a comprehensive overview of the strategic importance of data and infrastructure in the context of Indonesia’s AI development. It identifies key challenges, advocates for robust frameworks, and outlines initiatives to improve data quality and accessibility.

  1. Strategic Issues:
    • The chapter begins by highlighting the importance of data as a foundational element for AI development. It emphasizes that the availability, accessibility, and quality of data are critical for effective AI applications.
    • There are challenges regarding data ownership, privacy, and the need for robust data governance frameworks to ensure responsible usage.
  2. Data Infrastructure:
    • The establishment of a comprehensive data infrastructure is discussed. This includes the integration of data from various sources, such as government agencies, private sectors, and academia.
    • The chapter advocates for the development of a “shared infrastructure” that can facilitate data sharing and collaboration among stakeholders. This infrastructure should support data storage, processing, and analysis capabilities.
  3. Data Protection and Privacy:
    • A significant focus is placed on the need for legal frameworks to protect personal data, in line with national regulations. The chapter outlines the role of the government in ensuring that data privacy is maintained while promoting the use of data for AI development.
    • The necessity of implementing secure data handling practices and compliance with data protection laws is emphasized.
  4. Data Quality and Standards:
    • The importance of high-quality data for AI training and application is discussed. The chapter calls for the establishment of standards for data collection, processing, and sharing to ensure consistency and reliability.
    • It encourages collaboration between various sectors to improve data quality and address issues such as data gaps and inaccuracies.
  5. Initiatives for Data and Infrastructure Development:
    • The chapter outlines specific initiatives aimed at enhancing data infrastructure, such as:
      • Developing a national data repository that aggregates data from various sources.
      • Implementing training programs to improve the skills of personnel involved in data management and analysis.
      • Encouraging partnerships between government, industry, and academia to foster innovation and improve data utilization.
  6. Use of Data in AI Applications:
    • Discussions include the application of data in various sectors such as health, education, agriculture, and transportation. The chapter highlights how AI can leverage data to improve services and outcomes in these areas.
    • Examples of potential AI applications that rely heavily on data are provided, showcasing the impact of data-driven decision-making.
  7. Future Directions:

The chapter concludes with recommendations for future actions to enhance data and infrastructure related to AI. This includes continuous evaluation of data policies, investment in technology and infrastructure, and fostering a collaborative ecosystem among stakeholders.

Chapter 6

This chapter highlights the importance of a robust research ecosystem to support AI development, emphasizing the need for collaboration between academic institutions, government agencies, and the private sector. It outlines several strategic issues, such as the need for improved data accessibility, fostering innovation through research, and enhancing the quality of research outputs.

Proposed initiatives:

  1. Developing a comprehensive research agenda that aligns with national priorities and industry needs.
  2. Establishing partnerships between universities and industries to leverage resources and expertise for AI research.
  3. Creating funding mechanisms to support AI research projects, particularly those focused on local challenges and solutions.
  4. Promoting knowledge-sharing and best practices among researchers and industry practitioners to accelerate innovation.
  5. Implementing policies that encourage the commercialization of research findings, ensuring that innovations can be translated into practical applications.

This chapter also emphasizes the need for ethical considerations in AI research and advocates for guidelines to ensure responsible development.

Chapter 7

Chapter 7 of Indonesia’s National AI Strategy focuses on the priority fields of Artificial Intelligence (AI) in Indonesia. It outlines the following key areas:

  1. Healthcare: The chapter emphasizes the importance of predictive, preventive, personalized, and participatory healthcare approaches. It discusses the potential for AI to enhance healthcare delivery by utilizing genomic data and improving disease detection and treatment. AI can also help in managing public health data effectively.
  2. Bureaucratic Reform: This section discusses the need for reform in the bureaucratic processes in Indonesia to ensure transparency, efficiency, and accountability. It highlights the role of AI in automating administrative tasks, thus improving public service delivery.
  3. Education and Research: The chapter outlines the significance of AI in education, promoting intelligent online education, adaptive learning systems, and serious games to enhance learning experiences. It also underscores the necessity for research and innovation in AI to continuously improve educational methodologies.
  4. Food Security: AI is presented as a tool for predicting agricultural production and improving food supply management, ensuring food security in the nation.
  5. Mobility and Smart Cities: The chapter discusses the implementation of AI in urban planning and transportation systems to promote smart city initiatives, enhancing overall urban living conditions.

Chapter 8

Chapter 8 of Indonesia’s strategy outlines the acceleration program and roadmap for AI development in Indonesia. The key points include:

  1. AI Acceleration Programs: Various programs aimed at enhancing AI capabilities within different sectors, including healthcare, education, and public administration, are detailed. These programs are designed to build momentum and establish a strong foundation for AI integration across industries.
  2. Implementation Roadmap: The chapter provides a strategic roadmap for implementing AI initiatives, including timelines and responsible parties for various programs, ensuring that all stakeholders are aligned in their efforts to advance AI in Indonesia.
  3. Collaborative Efforts: Emphasis is placed on the importance of collaboration between government agencies, educational institutions, and industry players to foster an ecosystem conducive to AI growth and innovation.
  4. Monitoring and Evaluation: The chapter highlights the need for continuous monitoring and evaluation of AI programs to measure effectiveness and make necessary adjustments to strategies.