Artificial intelligence technologies, alongside opportunities such as broader access to educational content, expanding the scope and quality of academic and instructional projects, and applying advanced programs, also pose certain risks. These include enabling students to falsify assignments, threatening personal security, negatively impacting relationships among students and between teachers and students, and spreading false information. In short, this technological innovation demands a fundamental restructuring of educational systems in many countries. Otherwise, schools may become overwhelmed with fraudulent outcomes and conflicts. Developing nations, in particular—those that have not yet fully harnessed the internet's potential or resolved internet accessibility issues—may face additional challenges.

A blanket ban on the use of artificial intelligence in schools or during lessons—such as prohibiting access to AI through phones, tablets, or computers—is irrational, ineffective, and counterproductive. Instead, education systems must learn to coexist with AI and adapt themselves to this technological breakthrough.

First and foremost, the scope of AI integration in schools must be clearly defined. This includes regulating the relationship between companies offering AI technologies, school administrations, teachers, and students. Additionally, all stakeholders in the school must be taught how to use AI systems in a way that does not threaten rules or personal rights.

Secondly, just as basic computer and internet literacy is currently required from school administrations and teaching staff, it is now time to require competencies in using AI technologies. Without this, a generation adept in using technology may begin to dominate interpersonal dynamics, potentially disrupting the current educational structure. In other words, students surpassing teachers in terms of technological proficiency could lead to a loss of control.

Curriculums also need to be revised. Programs, teaching methods, lessons, and assignments must be designed with AI-using students in mind. AI should not be outright banned, but neither should students become overly dependent on it to the point of losing their critical thinking abilities. The new curriculum must consider the co-existence of students and AI, focusing on how students can further develop their abilities with the help of AI. Otherwise, we risk producing a generation either incapable of working independently with technology or entirely reliant and mentally subdued by it.

This process also includes reassessing the evaluation system. For example, traditional tasks like essay writing may no longer accurately reflect a student's abilities. Homework assignments that have long been considered standard should also become obsolete in the face of technological advancement. Continuing to rely on outdated formats in the age of AI, as we already did in the internet era, is a deliberate neglect of developing thinking skills. Assignments should be reshaped to emphasize reasoning, public speaking, and analytical explanation. Moreover, central educational authorities must explicitly define whether AI is permitted or prohibited in assessing students’ tasks and abilities. If permitted, specifying the ethical framework under which AI algorithms may operate can help prevent conflicts.

Thirdly, ethical standards for using AI in schools, colleges, universities, and institutes must be developed. These rules should be introduced to all stakeholders—officials, teachers, students, and learners. Importantly, these regulations should not result in banning AI but rather promote its integration into educational processes. The rules should emphasize protecting personal dignity (e.g., not using AI to manipulate others' images, audio, or video) and safeguarding private data when processed through AI systems. At the university level, it’s also crucial to avoid disclosing state- or regionally significant research projects to AI systems in full, although this does not imply a total ban on AI usage.

In some countries, internet technologies were once treated as competitors to the educational process and subsequently excluded. This ultimately led to internet platforms dominating educational content. The resulting generation uses these platforms ineffectively and fails to harness their potential for innovation. If AI is viewed similarly and simply banned, we risk losing yet another generation. Instead, it is essential to teach students how to work with AI and apply it effectively in subjects like history, chemistry, physics, and mathematics. This approach fosters—not hinders—cognitive development. AI, used as a support tool, can help students think more critically and solve more complex problems. Therefore, educational institutions should stop teaching tasks that AI can already perform. Otherwise, we will continue to produce graduates who are not in demand. Instead, students must be taught to engage with AI effectively, fostering competitive thinking, research, and analysis.

Fourthly, AI can help streamline school operations and processes, reducing administrative and teaching burdens. This would allow teachers to focus more on teaching and improving their professional skills. AI can assist in analyzing students’ behavior, emotional and mental states, and enhancing cooperation between schools and parents.

Nevertheless, no country has yet successfully implemented the integration of artificial intelligence into its education system. At present, only a few countries have developed specific programs in this area. In particular, countries with centrally governed education systems are increasingly struggling to respond to the rapid development of AI and to adapt their curricula accordingly. As a result, they are faced with three main options: liberalize their approach to education, update curricula annually, or retain outdated materials in technology-related subjects for several years. While the first approach offers a genuine solution to the situation, the second leads to wasted resources and system inefficiencies, and the third negatively affects graduates' competitiveness in the labor market.

Currently, 9 out of 10 countries that have published official guidelines for implementing AI in education belong to the democratic bloc. Despite its governmental structure, the United Arab Emirates is also considered a country that provides an open environment in the fields of education and technology. It can be observed that countries with a tradition of open educational environments began adapting their systems to the AI era earlier. Consequently, they are more likely to produce competitive professionals in the AI field and gain a strategic advantage on the global stage by becoming a vital hub in the AI sector.

For the remaining group of countries, the time has come to reconsider and reform their education systems.

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Methodology

AI Risks

1. Uncontrollable AI. Uncontrolled robots pose a risk to human safety through their erratic actions. Governments should enact legislation requiring tech-working units to refrain from totally excluding human participation in AI systems at this point in the development of AI. This principle requires businesses and organizations developing AI programs to have a backup plan in place for when the system becomes uncontrollable.

Question 1: Does the country's legislation require AI developers to maintain human control over the AI system they have developed?

2. Academic AI. Individual groups can carry out research on weapons of mass destruction that could prove hazardous to communities by using AI systems for academic reasons. It increases the availability of chemical and biological weapons and facilitates access to their development processes. Several nuclear-armed powers can reveal the secrets of their missiles and nuclear weapons to other nations. AI systems with strong academic research potential have the ability to not only incite a state arms race but also transfer these techniques to non-state actors and threaten the current system of regulating WMDs.

One way to monitor the use of artificial intelligence is through state legislation that limits uncertified access to sophisticated academic AI systems. It might keep the world from devolving into a war involving weapons of mass destruction.

Question 2: Does the country impose restrictions on access to advanced academic AI systems from uncertified sources?

3. Social Scoring. Governments may use discriminatory algorithms on their electronic platforms that target social minorities and support apartheid and segregation. Second, AI systems might be used to assess citizens based on how faithful they are to the rules and limit their basic rights. Third, those who have not yet committed a crime but have the capacity to do so are penalized by social scoring systems that use AI algorithms. People's freedom thus gets restricted and their fundamental rights continue to be threatened.

To mitigate the case, the community must have access to AI algorithms utilized in the public sector. Furthermore, it must be possible for independent specialists to frequently study and evaluate AI algorithms.

Question 3: Are the algorithms of national AI projects open for public discussion in the country?

4. Manipulative AI. Deepfakes and chatbots with either unreliable data or deliberately accumulated data sources are examples of systems that can be exploited to sway public opinion. An AI chatbot may provide deliberate and restricted responses if the data source is subject to stringent regulations, but it may also generate inaccurate information from an abundance of internet-based data. Both situations have the potential to manipulate the public in the absence of legislation that simultaneously protects freedom of speech and identifies reliable data sources.

Question 4: Does country regulation mandate the use of reliable data sources for AI model training?

5. Data Exploitation. Since data is a fundamental component of artificial intelligence, developers need more data in order to train their models. It can occasionally lead to the misuse of personal information. Governments should enact laws pertaining to the protection and security of personal data and prohibit the use of data for AI model training without consent to hold AI developers more accountable.

Question 5: Does country legislation protect personal data from misuse?

6. AI Militarization. Big data analysis and automated targeting are two uses of military AI. Some nations now prioritize developing lethal autonomous weaponry that improves targeting precision and allows them to utilize smaller weapons to destroy enemy warehouses and vital infrastructure. Nonetheless, the race for AI weapons feeds states' aspirations for armaments and helps to rebalance the existing power structure.

Question 6: Does the country have plans to develop AI (automated weapons) as part of its military strategy?

Sources

Egypt

Egyptian Charter for Responsible AI

Egypt’s views on: “Lethal Autonomous Weapons Systems” resolution A/78/241

Morocco

Law No. 09-08 on the protection of individuals with regard to the processing of personal data

Tunisia

Law on the Protection of Personal Data

Canada

Bill C-27

Artificial Intelligence Strategy

United States

Pentagon Official Lays Out DOD Vision for AI

Mexico

Federal Law on Protection of Personal Data Held by Private Parties

Salvador

Personal Data Protection Act

Nicaragua

Personal Data Protection Law

Panama

Data Protection Law

Colombia

Law 1581 of 2012

Brazil

Brazilian AI Bill

Argentina

Ley de Protección de los Datos Personales

Uruguay

AI Strategy for the Digital Government

Ecuador

Personal Data Protection Organic Law

Peru

Ley de Protección de Datos Personales

Chile

Personal Data Protection Law

Malaysia

Personal Data Protection Act

Indonesia

Personal Data Protection Law

China

Cyberspace Administration of China

Provisions on the Management of Algorithmic Recommendations in Internet Information Services

Interim Measures for the Management of Generative Artificial Intelligence Services

Personal Information Protection Law

Data Security Law

New Generation Artificial Intelligence Development Plan

India

Digital Personal Data Protection Act

Ministry of Defense

Kazakhstan

Law on Personal Data and Its Protection

Japan

Act on the Protection of Personal Information

South Korea

Personal Information Protection Act

Defense AI Center

Philippines

Data Privacy Act

Thailand

Personal Data Protection Act

Vietnam

Decree on Personal Data Protection

Singapore

Personal Data Protection Act

Iran

Shark 33

Mongolia

Five bills on information transparency, protecting personal information, e-signatures, virtual asset service providers and cybersecurity.

Saudi Arabia

Artificial Intelligence Law

Personal Data Protection Law

Oman

Executive Regulation of the Personal Data Protection Law

Armenia

On Protection of Personal Data

Georgia

Law of Georgia on Personal Data Protection

The United Arab Emirates

The UAE Charter for the Development and Use of Artificial Intelligence

Federal Decree by Law No. (45) of 2021 Concerning the Protection of Personal Data

Qatar

Artificial Intelligence in Qatar – Principles and Guidelines for Ethical Development and Deployment

Personal Data Privacy Protection

Israel

Israel’s Policy on Artificial Intelligence. Regulation and Ethics

Lavender

Gospel

Jordan

National Charter of Ethics for AI

Personal Data Protection Law

Uzbekistan

Law on Personal Data

Kyrgyzstan

Law on Personal Data

Bahrain

Law No. (30) of 2018 with Respect to Personal Data Protection Law

Australia

Privacy Act

New Zealand

Public Service AI Framework

Privacy Act

Kenya

The Data Protection Act

South Africa

National Artificial Intelligence Framework

Protection of Personal Information Act

Ireland

EU AI Act

AI-Here for Good. A National Artificial Intelligence Strategy for Ireland

General Data Protection Regulation

Spain

Royal Decree 817/2023 on Artificial Intelligence

EU AI Act

General Data Protection Regulation

Agencia Española de Supervisión de la Inteligencia Artificial

Germany

Public Sector dimension of AI Strategy

EU AI Act

General Data Protection Regulation

Artificial Intelligence in the Armed Forces: On the need for regulation regarding autonomy in weapon systems

Greece

Democratising AI. A National Strategy for Greece

EU AI Act

General Data Protection Regulation

Czech Republic

National Artificial Intelligence Strategy of the Czech Republic

The Czech Armed Forces Vision of Future Warfare Beyond 2040

EU AI Act

General Data Protection Regulation

France

PERP AI

La loi Informatique et Libertés

Report of the AI Task Force

EU AI Act

Sweden

AI Sweden

A Fertile Soil for AI

EU AI Act

General Data Protection Regulation

Norway

National Strategy for Artificial Intelligence

The Personal Data Act

Submission by Norway on Lethal Autonomous Weapons Systems to the UN

Denmark

National Strategy for Artificial Intelligence

General Data Protection Regulation

Austria

Artificial Intelligence Mission Austria 2030

EU AI Act

General Data Protection Regulation

Latvia

EU AI Act

General Data Protection Regulation

Lithuania

EU AI Act

General Data Protection Regulation

Estonia

Estonia: Public Sector dimension of AI Strategy

Estonia AI Strategy Report

EU AI Act

General Data Protection Regulation

DefSecIntel

United Kingdom

Planning and preparing for artificial intelligence implementation

UK General Data Protection Regulation

British Army’s Approach to Artificial Intelligence

Poland

EU AI Act

General Data Protection Regulation

Policy for the Development of Artificial Intelligence in Poland

Slovakia

Slovakia AI Strategy Report

General Data Protection Regulation

Finland

Finland AI Strategy Report

Finland joins the Declaration on Responsible Military Use of Artificial Intelligence and Autonomy

General Data Protection Regulation

Iceland

Guidelines for AI Use

Act on Data Protection and the Processing of Personal Data

Russia

National Strategy for Artificial Intelligence

Federal Law on Personal Data (No. 152-FZ)

Announcement of the establishment of a Department dealing with Artificial Intelligence in the Ministry of Defense of Russian Federation

Italy

Italy’s AI Strategy for 2024-2026: The Key Points

AI Regulation in Europe: Italy’s new draft AI Law introduces local peculiarities compared to the EU AI Act

Exploring the Benefits of a New Force Enabler

General Data Protection Regulation

Belgium

General Data Protection Regulation

Belgium AI Strategy Report

Hungary

General Data Protection Regulation

Romania

General Data Protection Regulation

Bulgaria

Personal Data Protection Act

Belarus

The Belarusian Data Protection Act

The Netherlands

Submission of the Netherlands in accordance with resolution 78/241 of the UN on autonomous weapons systems

General Data Protection Regulation

Turkiye

Personal Data Protection Law

Enabling Technology of Future Warfare

Cyprus

EU AI Act

General Data Protection Regulation

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Summary

American continents are the most influential region in artificial intelligence development as the United States, home to the biggest data center operators, leading AI chips producers, and top universities are located there. Moreover, the soft power of the US affects the countries around the world and they may take the US legislation on the regulation of artificial intelligence granted for democratic principles and technological success. One example is that the lack of federal laws regulating AI breeds a false illusion that an unregulated market facilitates opportunities for businesses to develop AI technologies successfully as companies are conferred with abundant data to train their models. As a result, some governments denounce establishing rules for companies building AI systems, thus ingraining a slow-bursting mine in their societies. Seeing the US as a sample to follow, they usually forget that the technology companies in the country precede the campaigns for AI regulation. It means a vice-versa situation in which the AI conglomeration in the US jeopardizes an effective regulation that provides personal rights and democratic elections in the country. The last elections in the US showed that social media such as Elon Musk’s Twitter could play a significant role in manipulating the voters. The same big data with AI-powered analyzing tools make a bigger impact on the US democracy.

Similarly, the lack of AI regulation is pervasive in the Americas where the majority of the countries have not yet adopted laws on the responsible use of AI. Only Uruguay and Brazil have fostered better ecosystems that maintain personal safety and national security from AI-related threats. In terms of index scores, Uruguay is the regional leader with 5 points.

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Methodology, Ranking, and Sources

AI Risks

1. Uncontrollable AI. Uncontrolled robots pose a risk to human safety through their erratic actions. Governments should enact legislation requiring tech-working units to refrain from totally excluding human participation in AI systems at this point in the development of AI. This principle requires businesses and organizations developing AI programs to have a backup plan in place for when the system becomes uncontrollable.

Question 1: Does the country's legislation require AI developers to maintain human control over the AI system they have developed?

2. Academic AI. Individual groups can carry out research on weapons of mass destruction that could prove hazardous to communities by using AI systems for academic reasons. It increases the availability of chemical and biological weapons and facilitates access to their development processes. Several nuclear-armed powers can reveal the secrets of their missiles and nuclear weapons to other nations. AI systems with strong academic research potential have the ability to not only incite a state arms race but also transfer these techniques to non-state actors and threaten the current system of regulating WMDs.

One way to monitor the use of artificial intelligence is through state legislation that limits uncertified access to sophisticated academic AI systems. It might keep the world from devolving into a war involving weapons of mass destruction.

Question 2: Does the country impose restrictions on access to advanced academic AI systems from uncertified sources?

3. Social Scoring. Governments may use discriminatory algorithms on their electronic platforms that target social minorities and support apartheid and segregation. Second, AI systems might be used to assess citizens based on how faithful they are to the rules and limit their basic rights. Third, those who have not yet committed a crime but have the capacity to do so are penalized by social scoring systems that use AI algorithms. People's freedom thus gets restricted and their fundamental rights continue to be threatened.

To mitigate the case, the community must have access to AI algorithms utilized in the public sector. Furthermore, it must be possible for independent specialists to frequently study and evaluate AI algorithms.

Question 3: Are the algorithms of national AI projects open for public discussion in the country?

4. Manipulative AI. Deepfakes and chatbots with either unreliable data or deliberately accumulated data sources are examples of systems that can be exploited to sway public opinion. An AI chatbot may provide deliberate and restricted responses if the data source is subject to stringent regulations, but it may also generate inaccurate information from an abundance of internet-based data. Both situations have the potential to manipulate the public in the absence of legislation that simultaneously protects freedom of speech and identifies reliable data sources.

Question 4: Does country regulation mandate the use of reliable data sources for AI model training?

5. Data Exploitation. Since data is a fundamental component of artificial intelligence, developers need more data in order to train their models. It can occasionally lead to the misuse of personal information. Governments should enact laws pertaining to the protection and security of personal data and prohibit the use of data for AI model training without consent to hold AI developers more accountable.

Question 5: Does country legislation protect personal data from misuse?

6. AI Militarization. Big data analysis and automated targeting are two uses of military AI. Some nations now prioritize developing lethal autonomous weaponry that improves targeting precision and allows them to utilize smaller weapons to destroy enemy warehouses and vital infrastructure. Nonetheless, the race for AI weapons feeds states' aspirations for armaments and helps to rebalance the existing power structure.

Question 6: Does the country have plans to develop AI (automated weapons) as part of its military strategy?

Canada

Bill C-27

Artificial Intelligence Strategy

United States

Pentagon Official Lays Out DOD Vision for AI

Mexico

Federal Law on Protection of Personal Data Held by Private Parties

Salvador

Personal Data Protection Act

Nicaragua

Personal Data Protection Law

Panama

Data Protection Law

Colombia

Law 1581 of 2012

Brazil

Brazilian AI Bill

Argentina

Ley de Protección de los Datos Personales

Uruguay

AI Strategy for the Digital Government

Ecuador

Personal Data Protection Organic Law

Peru

Ley de Protección de Datos Personales

Chile

Personal Data Protection Law

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Summary

In the Middle East and North Africa, Egypt, Qatar, Jordan, and Cyprus foster ecosystems to build more secure AI systems for humans adopting documents that initiate reliable use of artificial intelligence. Egypt is the leader in the region whose AI policy breeds human oversight, transparency, and security.

The legislation related to the responsible implementation of artificial intelligence technologies in the Middle East and North Africa (MENA) shows varying features that contain distinct national characteristics. First, people in the region are vulnerable to personal data abuse by companies to train their AI models. Conflicts in Yemen, Palestine, Syria, Libya, and Sudan make the users of digital platforms unprotected to be exploited and cultivate an unregulated flow of data. Secondly, the government of Cyprus cannot impose a single mandate over the whole country as the island has been torn apart due to a conflict. It degrades its actual position, which is supported by the enforcement of the principles of the EU AI Act. Moreover, none of the countries in MENA restrict access to uncertified sources to academic AI systems. Advanced computers that enable the development of military equipment undermine security when non-state actors acquire the structure of weapons. Another point to consider is that the region is one of the first testing grounds of AI for military purposes. Israel Defense Forces employ Lavender and Gospel AI systems in the Gaza war. However, only three countries (Iran, Turkiye, and Israel) are developing military AI technologies.

To summarize, the Middle East and North African countries can be categorized into stable lands to build responsible AI and unstable territories subject to personal data exploitation and violent use of AI. To alleviate the situation, the former could support the latter in protecting their citizens’ data from misuse by AI developers. Besides, international and regional organizations may become facilitators or coordinators to decrease the gap, maintain cooperation, and increase public awareness.

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Methodology, Ranking and Sources

AI Risks

1. Uncontrollable AI. Uncontrolled robots pose a risk to human safety through their erratic actions. Governments should enact legislation requiring tech-working units to refrain from totally excluding human participation in AI systems at this point in the development of AI. This principle requires businesses and organizations developing AI programs to have a backup plan in place for when the system becomes uncontrollable.

Question 1: Does the country's legislation require AI developers to maintain human control over the AI system they have developed?

2. Academic AI. Individual groups can carry out research on weapons of mass destruction that could prove hazardous to communities by using AI systems for academic reasons. It increases the availability of chemical and biological weapons and facilitates access to their development processes. Several nuclear-armed powers can reveal the secrets of their missiles and nuclear weapons to other nations. AI systems with strong academic research potential have the ability to not only incite a state arms race but also transfer these techniques to non-state actors and threaten the current system of regulating WMDs.

One way to monitor the use of artificial intelligence is through state legislation that limits uncertified access to sophisticated academic AI systems. It might keep the world from devolving into a war involving weapons of mass destruction.

Question 2: Does the country impose restrictions on access to advanced academic AI systems from uncertified sources?

3. Social Scoring. Governments may use discriminatory algorithms on their electronic platforms that target social minorities and support apartheid and segregation. Second, AI systems might be used to assess citizens based on how faithful they are to the rules and limit their basic rights. Third, those who have not yet committed a crime but have the capacity to do so are penalized by social scoring systems that use AI algorithms. People's freedom thus gets restricted and their fundamental rights continue to be threatened.

To mitigate the case, the community must have access to AI algorithms utilized in the public sector. Furthermore, it must be possible for independent specialists to frequently study and evaluate AI algorithms.

Question 3: Are the algorithms of national AI projects open for public discussion in the country?

4. Manipulative AI. Deepfakes and chatbots with either unreliable data or deliberately accumulated data sources are examples of systems that can be exploited to sway public opinion. An AI chatbot may provide deliberate and restricted responses if the data source is subject to stringent regulations, but it may also generate inaccurate information from an abundance of internet-based data. Both situations have the potential to manipulate the public in the absence of legislation that simultaneously protects freedom of speech and identifies reliable data sources.

Question 4: Does country regulation mandate the use of reliable data sources for AI model training?

5. Data Exploitation. Since data is a fundamental component of artificial intelligence, developers need more data in order to train their models. It can occasionally lead to the misuse of personal information. Governments should enact laws pertaining to the protection and security of personal data and prohibit the use of data for AI model training without consent to hold AI developers more accountable.

Question 5: Does country legislation protect personal data from misuse?

6. AI Militarization. Big data analysis and automated targeting are two uses of military AI. Some nations now prioritize developing lethal autonomous weaponry that improves targeting precision and allows them to utilize smaller weapons to destroy enemy warehouses and vital infrastructure. Nonetheless, the race for AI weapons feeds states' aspirations for armaments and helps to rebalance the existing power structure.

Question 6: Does the country have plans to develop AI (automated weapons) as part of its military strategy?

Iran

Shark 33

Saudi Arabia

Artificial Intelligence Law

Personal Data Protection Law

Oman

Executive Regulation of the Personal Data Protection Law

The United Arab Emirates

The UAE Charter for the Development and Use of Artificial Intelligence

Federal Decree by Law No. (45) of 2021 Concerning the Protection of Personal Data

Qatar

Artificial Intelligence in Qatar – Principles and Guidelines for Ethical Development and Deployment

Personal Data Privacy Protection

Israel

Israel’s Policy on Artificial Intelligence. Regulation and Ethics

Lavender

Gospel

Jordan

National Charter of Ethics for AI

Personal Data Protection Law

Bahrain

Law No. (30) of 2018 with Respect to Personal Data Protection Law

Egypt

Egyptian Charter for Responsible AI

Egypt’s views on: “Lethal Autonomous Weapons Systems” resolution A/78/241

Morocco

Law No. 09-08 on the protection of individuals with regard to the processing of personal data

Tunisia

Law on the Protection of Personal Data

Cyprus

EU AI Act

General Data Protection Regulation

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Artificial Intelligence as a new phenomenon brings opportunities and challenges to societies. Societies that can reduce AI risks and take advantage of opportunities can employ this technological phenomenon successfully and safely. In this process, governments are responsible for adopting necessary regulations to control potential AI threats.

Responsible AI Index monitors and informs government regulations that intend to prevent people from AI threats. The index attempts to show where a safer AI ecosystem exists according to current legislation. Regulations to prevent AI threats are the main measuring component to rank countries in the index.

Summary on Asia

Although Japan and South Korea are prominent examples of technological development, their legislations still focus less on accountability and transparency of artificial intelligence. This tendency also covers Southeast Asian and South Asian countries. China is an outstanding leader in AI regulation in these parts of Asia. On the other hand, countries in the Middle East excel at AI legislation fostering safer ecosystems and human contact. Qatar dominates in this field in the continent facilitating a better environment for responsible AI. At the same time, Iran is positioned in the lowest row due to the lack of laws in this domain and AI militarization ambitions.

Israel uniquely exemplifies how to strike a balance between legislation and innovation. Contrary to the arguments claiming that AI rules discourage technological rise, the country stands out in both sectors. Regardless, the implementation of AI-powered Gospel and Lavender in Gaza causing civilians, women, and children deaths denounces the prestige of Israel.

Apart from Israel, China, Russia, Turkey, India, South Korea, and Iran have exposed their intentions to develop artificial intelligence in the defense sector. Only the legislations of Qatar, Jordan, the United Arab Emirates, and Israel mandate human oversight over AI and only China in Asia regulates access to advanced academic AI. Furthermore, China is the single country that requires the use of reliable data to train artificial intelligence whereas Qatar and Israel partially hint at this requirement.

To summarize, legislation on AI is developing in Asia. For example, most countries have adopted laws that protect personal data. Qatar, Jordan, the United Arab Emirates, and China have established legislation for the responsible use of artificial intelligence above an average level (at or more than 3.5 points).

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Methodology, Ranking and Sources

AI Risks

1. Uncontrollable AI. Uncontrolled robots pose a risk to human safety through their erratic actions. Governments should enact legislation requiring tech-working units to refrain from totally excluding human participation in AI systems at this point in the development of AI. This principle requires businesses and organizations developing AI programs to have a backup plan in place for when the system becomes uncontrollable.

Question 1: Does the country's legislation require AI developers to maintain human control over the AI system they have developed?

2. Academic AI. Individual groups can carry out research on weapons of mass destruction that could prove hazardous to communities by using AI systems for academic reasons. It increases the availability of chemical and biological weapons and facilitates access to their development processes. Several nuclear-armed powers can reveal the secrets of their missiles and nuclear weapons to other nations. AI systems with strong academic research potential have the ability to not only incite a state arms race but also transfer these techniques to non-state actors and threaten the current system of regulating WMDs.

One way to monitor the use of artificial intelligence is through state legislation that limits uncertified access to sophisticated academic AI systems. It might keep the world from devolving into a war involving weapons of mass destruction.

Question 2: Does the country impose restrictions on access to advanced academic AI systems from uncertified sources?

3. Social Scoring. Governments may use discriminatory algorithms on their electronic platforms that target social minorities and support apartheid and segregation. Second, AI systems might be used to assess citizens based on how faithful they are to the rules and limit their basic rights. Third, those who have not yet committed a crime but have the capacity to do so are penalized by social scoring systems that use AI algorithms. People's freedom thus gets restricted and their fundamental rights continue to be threatened.

To mitigate the case, the community must have access to AI algorithms utilized in the public sector. Furthermore, it must be possible for independent specialists to frequently study and evaluate AI algorithms.

Question 3: Are the algorithms of national AI projects open for public discussion in the country?

4. Manipulative AI. Deepfakes and chatbots with either unreliable data or deliberately accumulated data sources are examples of systems that can be exploited to sway public opinion. An AI chatbot may provide deliberate and restricted responses if the data source is subject to stringent regulations, but it may also generate inaccurate information from an abundance of internet-based data. Both situations have the potential to manipulate the public in the absence of legislation that simultaneously protects freedom of speech and identifies reliable data sources.

Question 4: Does country regulation mandate the use of reliable data sources for AI model training?

5. Data Exploitation. Since data is a fundamental component of artificial intelligence, developers need more data in order to train their models. It can occasionally lead to the misuse of personal information. Governments should enact laws pertaining to the protection and security of personal data and prohibit the use of data for AI model training without consent to hold AI developers more accountable.

Question 5: Does country legislation protect personal data from misuse?

6. AI Militarization. Big data analysis and automated targeting are two uses of military AI. Some nations now prioritize developing lethal autonomous weaponry that improves targeting precision and allows them to utilize smaller weapons to destroy enemy warehouses and vital infrastructure. Nonetheless, the race for AI weapons feeds states' aspirations for armaments and helps to rebalance the existing power structure.

Question 6: Does the country have plans to develop AI (automated weapons) as part of its military strategy?

Malaysia

Personal Data Protection Act

Indonesia

Personal Data Protection Law

China

Cyberspace Administration of China

Provisions on the Management of Algorithmic Recommendations in Internet Information Services

Interim Measures for the Management of Generative Artificial Intelligence Services

Personal Information Protection Law

Data Security Law

New Generation Artificial Intelligence Development Plan

India

Digital Personal Data Protection Act

Ministry of Defense

Kazakhstan

Law on Personal Data and Its Protection

Japan

Act on the Protection of Personal Information

South Korea

Personal Information Protection Act

Defense AI Center

Philippines

Data Privacy Act

Thailand

Personal Data Protection Act

Vietnam

Decree on Personal Data Protection

Singapore

Personal Data Protection Act

Iran

Shark 33

Mongolia

Five bills on information transparency, protecting personal information, e-signatures, virtual asset service providers and cybersecurity.

Saudi Arabia

Artificial Intelligence Law

Personal Data Protection Law

Oman

Executive Regulation of the Personal Data Protection Law

Armenia

On Protection of Personal Data

Georgia

Law of Georgia on Personal Data Protection

The United Arab Emirates

The UAE Charter for the Development and Use of Artificial Intelligence

Federal Decree by Law No. (45) of 2021 Concerning the Protection of Personal Data

Qatar

Artificial Intelligence in Qatar – Principles and Guidelines for Ethical Development and Deployment

Personal Data Privacy Protection

Israel

Israel’s Policy on Artificial Intelligence. Regulation and Ethics

Lavender

Gospel

Jordan

National Charter of Ethics for AI

Personal Data Protection Law

Uzbekistan

Law on Personal Data

Kyrgyzstan

Law on Personal Data

Artificial Intelligence as a new phenomenon brings opportunities and challenges to societies. Societies that can reduce AI risks and take advantage of opportunities can employ this technological phenomenon successfully and safely. In this process, governments are responsible for adopting necessary regulations to control potential AI threats.

Responsible AI Index monitors and informs government regulations that intend to prevent people from AI threats. The index attempts to show where a safer AI ecosystem exists according to current legislation. Regulations to prevent AI threats are the main measuring component to rank countries in the index.

Subscribe now

Summary on Europe

Firstly, the EU AI Act plays a significant role in shaping a responsible AI ecosystem in which developers build more human-centric artificial intelligence. The Act imposes obligations regarding human control and selective access to high-risk AI systems. However, not all countries on the continent have implemented the EU AI Act as the document will become mandatory in 2026. It is reflected on the map with significant distinctions among countries that have implemented the Act more or less.  

Secondly, the General Data Protection Regulation has a positive impact on securing personal data from exploitation and misuse. Similarly, non-EU countries have also adopted data protection laws protecting personal data and fostering a safe environment in the continent in this matter.

Thirdly, AI militarization is trending into three dimensions. First-group countries are actively working to improve their capacities with AI or autonomous weapons without any restrictions while the second group advocates using artificial intelligence in the military sector according to some regulative frameworks. The last group does not explicit their intention but coordinates their military plans with NATO, Russia, and similar actors.

Fourthly, countries in the continent still need legislation that mandates algorithmic transparency of AI systems in the public sector. In light of increasing migration and the rise of right-wing parties, algorithmic transparency is necessary to restrict discriminatory electronic platforms.

Finally, Ireland is the leading country where AI systems become more responsible and human-centric under state legislation. The role of Ireland in AI militarization appears minimal according to the current research. On the other hand, the Netherlands and Belgium hesitate to adopt strategic laws that impose human control over AI and access selection to advanced academic AI systems.

Methodology, Ranking and Sources

AI Risks

1. Uncontrollable AI. Uncontrolled robots pose a risk to human safety through their erratic actions. Governments should enact legislation requiring tech-working units to refrain from totally excluding human participation in AI systems at this point in the development of AI. This principle requires businesses and organizations developing AI programs to have a backup plan in place for when the system becomes uncontrollable.

Question 1: Does the country's legislation require AI developers to maintain human control over the AI system they have developed?

2. Academic AI. Individual groups can carry out research on weapons of mass destruction that could prove hazardous to communities by using AI systems for academic reasons. It increases the availability of chemical and biological weapons and facilitates access to their development processes. Several nuclear-armed powers can reveal the secrets of their missiles and nuclear weapons to other nations. AI systems with strong academic research potential have the ability to not only incite a state arms race but also transfer these techniques to non-state actors and threaten the current system of regulating WMDs.

One way to monitor the use of artificial intelligence is through state legislation that limits uncertified access to sophisticated academic AI systems. It might keep the world from devolving into a war involving weapons of mass destruction.

Question 2: Does the country impose restrictions on access to advanced academic AI systems from uncertified sources?

3. Social Scoring. Governments may use discriminatory algorithms on their electronic platforms that target social minorities and support apartheid and segregation. Second, AI systems might be used to assess citizens based on how faithful they are to the rules and limit their basic rights. Third, those who have not yet committed a crime but have the capacity to do so are penalized by social scoring systems that use AI algorithms. People's freedom thus gets restricted and their fundamental rights continue to be threatened.

To mitigate the case, the community must have access to AI algorithms utilized in the public sector. Furthermore, it must be possible for independent specialists to frequently study and evaluate AI algorithms.

Question 3: Are the algorithms of national AI projects open for public discussion in the country?

4. Manipulative AI. Deepfakes and chatbots with either unreliable data or deliberately accumulated data sources are examples of systems that can be exploited to sway public opinion. An AI chatbot may provide deliberate and restricted responses if the data source is subject to stringent regulations, but it may also generate inaccurate information from an abundance of internet-based data. Both situations have the potential to manipulate the public in the absence of legislation that simultaneously protects freedom of speech and identifies reliable data sources.

Question 4: Does country regulation mandate the use of reliable data sources for AI model training?

5. Data Exploitation. Since data is a fundamental component of artificial intelligence, developers need more data in order to train their models. It can occasionally lead to the misuse of personal information. Governments should enact laws pertaining to the protection and security of personal data and prohibit the use of data for AI model training without consent to hold AI developers more accountable.

Question 5: Does country legislation protect personal data from misuse?

6. AI Militarization. Big data analysis and automated targeting are two uses of military AI. Some nations now prioritize developing lethal autonomous weaponry that improves targeting precision and allows them to utilize smaller weapons to destroy enemy warehouses and vital infrastructure. Nonetheless, the race for AI weapons feeds states' aspirations for armaments and helps to rebalance the existing power structure.

Question 6: Does the country have plans to develop AI (automated weapons) as part of its military strategy?

Ireland

• EU AI Act

• AI-Here for Good. A National Artificial Intelligence Strategy for Ireland

• General Data Protection Regulation

Spain

• Royal Decree 817/2023 on Artificial Intelligence

• EU AI Act

• General Data Protection Regulation

• Agencia Española de Supervisión de la Inteligencia Artificial

Germany

• Public Sector dimension of AI Strategy

• EU AI Act

• General Data Protection Regulation

• Artificial Intelligence in the Armed Forces: On the need for regulation regarding autonomy in weapon systems

Greece

• Democratising AI. A National Strategy for Greece

• EU AI Act

• General Data Protection Regulation

Czech Republic

• National Artificial Intelligence Strategy of the Czech Republic

• The Czech Armed Forces Vision of Future Warfare Beyond 2040

• EU AI Act

• General Data Protection Regulation

France

• PERP AI

• La loi Informatique et Libertés

• Report of the AI Task Force

• EU AI Act

Sweden

• AI Sweden

• A Fertile Soil for AI

• EU AI Act

• General Data Protection Regulation

Norway

• National Strategy for Artificial Intelligence

• The Personal Data Act

• Submission by Norway on Lethal Autonomous Weapons Systems to the UN

Denmark

• National Strategy for Artificial Intelligence

• General Data Protection Regulation

Austria

• Artificial Intelligence Mission Austria 2030

• EU AI Act

• General Data Protection Regulation

Latvia

• EU AI Act

• General Data Protection Regulation

Lithuania

• EU AI Act

• General Data Protection Regulation

Estonia

• Estonia: Public Sector dimension of AI Strategy

• Estonia AI Strategy Report

• EU AI Act

• General Data Protection Regulation

• DefSecIntel

United Kingdom

• Planning and preparing for artificial intelligence implementation

• UK General Data Protection Regulation

• British Army’s Approach to Artificial Intelligence

Poland

• EU AI Act

• General Data Protection Regulation

• Policy for the Development of Artificial Intelligence in Poland

Slovakia

• Slovakia AI Strategy Report

• General Data Protection Regulation

Finland

• Finland AI Strategy Report

• Finland joins the Declaration on Responsible Military Use of Artificial Intelligence and Autonomy

• General Data Protection Regulation

Iceland

• Guidelines for AI Use

• Act on Data Protection and the Processing of Personal Data

Russia

• National Strategy for Artificial Intelligence

• Federal Law on Personal Data (No. 152-FZ)

• Announcement of the establishment of a Department dealing with Artificial Intelligence in the Ministry of Defense of Russian Federation

Italy

• Italy’s AI Strategy for 2024-2026: The Key Points

• AI Regulation in Europe: Italy’s new draft AI Law introduces local peculiarities compared to the EU AI Act

• Exploring the Benefits of a New Force Enabler

• General Data Protection Regulation

Belgium

• General Data Protection Regulation

• Belgium AI Strategy Report

Hungary

• General Data Protection Regulation

Romania

• General Data Protection Regulation

Bulgaria

• Personal Data Protection Act

Belarus

• The Belarusian Data Protection Act

The Netherlands

• Submission of the Netherlands in accordance with resolution 78/241 of the UN on autonomous weapons systems

• General Data Protection Regulation

Turkiye

• Personal Data Protection Law

• Enabling Technology of Future Warfare

The strategic location of Southeast Asian countries close to China, India, Japan, South Korea, and Taiwan Island makes the region a key destination for the semiconductor industry. Each Southeast Asian country could claim to become a hub of microelectronics, a significant technology in the world. Current shadows over Taiwan due to the tensions with China have spiked competition among the region's countries to receive more industrial capacities in their territories. As all of them can take advantage of their strategic locations, other factors such as business environment, infrastructure, and well-trained labor play critical roles in this contest. In this manner, every country in the region has advantages and disadvantages.

Southeast Asia is home to more than 60 universities teaching electrical engineering, material science, and technology and engineering fields. The Malay Peninsula is a cluster of the highest-ranked universities, and the territory is located between Java Island and Bangkok, the next higher education centers in the region. In addition, its proximity to the Malacca Strait enables it to navigate industrial products around the globe conveniently. Nine universities in the peninsula train specialists in both electrical engineering and material science which are the two most significant fields for the semiconductor industry and they are located in Malaysia, Singapore and Thailand.

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Approximately 120,000 students graduate in engineering annually in Southeast Asia. Malaysia, the Philippines, and Singapore educate one engineer for around 2000 people while the statistics are between about 5000 and around 7000 for Indonesia, Myanmar, and Laos. Vietnam is the leader in training engineers per person with about a 1/1000 rate while Cambodia shows the lowest numbers with around 1/17000. This indicator is significant as it presents labor availability for the semiconductor industry.

Furthermore, there is a wide disparity among countries in their innovation capacities. According to the Global Innovation Index, Singapore is one of the leaders, ranking fourth in the list, while Brunei, Laos, Cambodia, and Myanmar are in lower positions. Malaysia, Thailand, Vietnam, the Philippines, and Indonesia are placed in the middle of the index.

Another factor that the countries in Southeast Asia should address is the gap between innovation input and output. Singapore, Malaysia, and Indonesia experience systematic loss of input, which is necessary to resolve to increase productivity in the technology sector. In this manner, the biggest burden comes to Brunei positioned at 55th in input and 123th in output. Two separate researches on the innovation barriers in Malaysia and Indonesia show the high cost of innovation, lack of internal and external funding, uncertain demands, and differences among regions' development as key factors contributing to the innovation gap. To wrap up, the contradictory information about supportive government input in the Global Innovation Index and the lack of funding in research papers leads to the possible conclusions:

• business and communities have no adequate information about government input in the innovation sector

• there is fear of taking a risk

• the government services for innovative units and people are less accessible

• lack of trust exists between technology researchers and business owners

It signals that governments should incentivize structural and systematic reforms to increase the profitability of their inputs. First, the business-to-government talks and open platforms pave the ground for national technology firms to benefit more from state support initiatives. Secondly, inter-regional migration in Malaysia and Indonesia provides knowledge flow along the territorial units of these countries. Thirdly, the free movement of engineers among regional countries may fill the innovation gaps. For instance, Vietnam, Thailand, and the Philippines take more output than their inputs while Singapore and Malaysia are Southeast Asian leaders according to overall parameters. Finally, states could stimulate medium and small companies to organize consortiums to mitigate the problem related to the lack of internal and external funding. Structural and systemic reforms serve to improve innovation ecosystems including the semiconductor industrial ecosystem in the region.

Shakhboz Juraev is the Chief Coordinator of Technology in Global Affairs. He is the author of the book "Hybrid Strategy of Cybersecurity: The Role of Information Technology Companies in Chinese Cybersecurity Policy”.

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An overview of modern geopolitical realities

For more than half a century, the clash between the United States and the USSR (then its successor Russian Federation) is seen as the next potential World War. It was in the 1960s after the Cuban crisis that tensions reached their zenith. However grandiose these expectations look, the United States and Russian Federation do not have a direct fault line from the point of geopolitics. It is unbelievable that Russia, a land power, will send its army across the oceans to be destroyed by the US naval, and the United States, a sea power, put its cavalries and artilleries at nearly the same fate as Napoleon and Hitler’s troops in Russian forests and vast plains.

Geopolitically, there are four fault lines with one exception where the great powers of similar types of force may collide with one another in the current world:

• the Atlantic Ocean between the US (sea power) and the UK (sea power);

• Eastern Europe between Russia (land power) and some European countries under the lead of Germany (land power)

• Central Asia, Mongolia, and China-Russian border between Russia (land power) and China (land power)

• the Pacific Ocean between Japan (sea power) and the US (sea power)

• the only exception is the Korean peninsula and seas between China (land power) and Japan (sea power) as the space separating two different types of countries is crossable without huge losses.

It is difficult to imagine other cases, for example, that China (land power) and India (land power) go to a full-scale war across the Tibet mountains, in which supply chains are mostly possible to be disrupted geographically. Somehow this case also applies to the US-Russian direct warfare. Nevertheless, the emerging areas of contradiction that enable to shorten the geographical lengths, contribute to the great power rivalry as a form of an arms race. They include:

• air space where airplanes are used to paralyze the opponent’s army, naval, ports, infrastructure, resource sites, and send paratroops to support one’s soldiers. The air space also contains missiles with the same purpose and nuclear warheads for full destruction.

• cyberspace, a field where attacks against technologies, technics, plants, and infrastructures are carried out;

• space, where satellite telecommunications are operated.

Yet not fully developed, these areas may overpass the natural borders and change the means of warfare. Consequently, global and regional actors in international relations are keen on building their air, cyber, and space potentials while strengthening land and sea capabilities. Unlike traditional weapons that are mainly compounded from “steel and gunpowder”, modern equipment of armies of all five contradiction areas require semiconductors to improve maneuvers and precision.

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Forth Industrial Revolution

ChatGPT introduced by OpenAI has revolutionized the perceptions of people about the ability of artificial intelligence (AI), the driver of the Forth industrial revolution. The logic behind the AI is self-learning characteristics of the machine, whose main components are computing-power, data, and algorithms. As occurred nearly in all industrial revolutions, the ideas on the economic, political, and military uncertainty of consequences have arisen. It is undeniable that a few tendencies that may influence the present world order have emerged on the brink of the AI era.

First of all, the rise of China as an economic superpower at a degree that is possible to put the US dominance under question demonstrates that artificial intelligence is not developed according to unipolar rules. It is Chinese Huawei and its 5G technological capacity that have been embarrassing most Western politicians.

Secondly, mutual sanctions, boycotts, embargos, tariffs, and limits by the West and Russia after the Ukrainian crisis undermines the ongoing architecture of global cooperation. All of them along with withdrawals from international conventions, treaties, and pacts rejuvenate races for arms sphere, space, and moon-landing.

Both of these tendencies mean that artificial intelligence is the under the uncertainty of “which actor uses it for what purpose”. It shows that countries may find it difficulty to reach common ground on AI, a technology that will be playing an integral role in economic progress and state defense. As a result, competition for integrated circuits and demand for the national chip industry is expected to increase when it comes to data (memory chips) and computing power (logic chips) of artificial intelligence.

The relevance of the work and research methodology

The U.S. Congress’s success in passing the CHIPS and Science Act (informally the CHIPS Act) shows that legislators are united on one point: the United States needs to manufacture more semiconductors at home. The CHIPS Act’s $52.7 billion investment in domestic semiconductor manufacturing aims to fulfill three main objectives: 1) reduce the likelihood that shocks abroad might disrupt the supply of chips, 2) boost American international economic competitiveness and create domestic jobs, and 3) protect semiconductors from being sabotaged in the manufacturing process. The CHIPS Act prohibits funding recipients from expanding semiconductor manufacturing in China and countries defined by US law as posing a national security threat to the United States. These restrictions would apply to any new facility unless the facility produces legacy semiconductors predominately for that country’s market.

Furthermore, the proposed European Chips Act aims to: strengthen Europe’s research and technology leadership towards smaller and faster chips; put in place a framework to increase production capacity to 20% of the global market by 2030; build and reinforce capacity to innovate in the design, manufacturing, and packaging of advanced chips; develop an in-depth understanding of the global semiconductor supply chains; address the skills shortage, attract new talent and support the emergence of a skilled workforce.

Both acts hint a radical shift of chip policy of the West that intends reshoring the related facilities to their territories. These steps by the United States and European Union make it important to study the chip production capacities of more countries and regions to draw a broader image of the industry and technological and technical security. The relevance of the research that focuses on the chip industry potential of Russia lies in the above-mentioned view.

The methodology includes data collection, an expert assessment questionnaire, and a SWOT analysis. At first, information about Russian raw material mines, R&D laboratories, education and training capacities, chip designing facilities, DUV and EUV machines, fabrication units, and companies is collected. Secondly, initial values are given according to the findings and further questions for experts’ assessment are formulated. Finally, a SWOT analysis is conducted based on both estimations of research findings and experts’ assessments.

The potential of the semiconductor industry in Russia

Raw materials

The most used semiconductor materials are silicon, germanium, and gallium arsenide. Of the three, germanium was one of the earliest semiconductor materials used. Silicon has seen extensive use as a semiconductor material since the 1950s. Gallium arsenide is the second most common semiconductor in use today.

Russia is the world’s second-largest silicon producer, with its production estimated at 640 thousand metric tons in 2022. Deposits of quartz raw materials suitable for smelting crystalline silicon in the country are Mount Karaulnaya (Antonovskoye) in the Sverdlovsk region for the needs of OAO Kremniy-Ural and Cheremshanskoye in Transbaikalia ore base for ZAO Kremniy. Silicon is produced at facility JSC Silicon in Shelekhov. It manufactures two types of products – smelter-grade silicon for producing AlSi alloys and refined silicon for the chemical and electrical industries.

About 90% of the world production of gallium is provided by aluminum production. An analysis of technological schemes for the production of alumina shows that the main amount of gallium passes into alkaline aluminate solutions, regardless of whether the feedstock is bauxite or nepheline. Semiconductor compounds of gallium are also used for the manufacture of various rectifiers, nuclear radiation detectors, devices using the Hall effect, and lasers for both the visible and infrared regions of the spectrum. In addition, the demand for gallium leads to its use in the production of solid-state emitters, thin film transistors, batteries, lithium batteries, and photovoltaic gallium alloys. Gallium arsenide (GaAs) is a promising material for semiconductor electronics. Gallium nitride has excellent chemical and mechanical properties typical of all nitride compounds and is used in semiconductor lasers and LEDs.

The only company in Russia that has a full cycle of germanium processing and the production of compounds is “Germanium” JSC (part of the Rostec Group of Companies). The main raw materials for obtaining germanium in Russia are caustobiolites (coals), the sources of which are located in the regions of the Perm Territory, Sakhalin, and Chita regions. One of the most promising is the deposit of germanium lignite located in the Yenisei region of the Krasnoyarsk Territory. The company divides the consumption of germanium into 5 main groups: infrared optics - 30%; fiber optics - 20%; PET - 20%; electronics and solar power - 20%; other fields - 10%.

The statistics show the abundance of essential raw materials of semiconductors and chips in Russia, a country that was ranked second in all three resources. In addition, the market leader in silicon, germanium, and gallium is China, a neighboring Russian country. Conclusively, Russia is in an advantageous position from the point of mineral resources.

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Silicon Wafers

In the process, the silicon will be purified, which is one of the most important stages of semiconductor production. Its significance lies in purification at an adequate level.  In July 2022, on its webpage, Rostec reports – “Ruselectronics holding of the Rostec State Corporation presented at the Innoprom-2022 exhibition a sample of single-crystal silicon produced entirely from Russian materials. The technology was developed at NPP Salyut of the Ruselectronics holding together with the Institute of Physics of Microstructures of the Russian Academy of Sciences and the Institute of Chemistry of High-Purity Substances of the Russian Academy of Sciences by order of the Russian Ministry of Industry and Trade.”

According to its claims, Epiel in Zelenograd is the only company in Russia specializing in the production of epitaxial structures based on silicon and sapphire for a wide range of semiconductor devices, including integrated circuits, discrete power devices, and many other electronic components. Epiel produces silicon epitaxial structures with diameters of 100, 150, and 200 mm, which are supplied to the largest microelectronics plants in Russia - Micron and Angstrom.

However, it must be noticed that more than 90% of all single-crystal silicon produced in the Russian Federation is of solar panel quality and is intended for export to the EU, Japan, and China in the form of wafers, less often ingots. On the territory of the Russian Federation there are many small industries that have the necessary capacities for cutting single-crystal silicon ingots into wafers (Zelenograd, Ryazan, Vladivostok, Khabarovsk, etc.).

Research and development (R&D)

The innovative potential in the semiconductor industry plays a key role to develop competitiveness and provide strategic technological and technical security. It is no coincidence that Japan and South Korea, countries with fewer mineral resources and more progressed human capital concentrate enormous and various facilities related to chip production. The main research objects are on the purification of raw materials, and minimization of size in nanometer scales. The first topic is mostly solved by industrial leaders, however, remains significant for runners-up. The second one is the “constant problem of semiconductor science”, on which research is regularly conducted to possess advanced technology and technics. On the page “Semiconductors information” by D.W. Palmer, the names of 17 semiconductor research laboratories in Russia (Table 1) are counted.

For example, the Institute of Metal Physics of the RAS is modern and fully equipped to study condensed matters (metals, semiconductors, metal-ceramics and others) under the high and low temperatures, high and low pressure, constant and pulsed magnetic fields. Research and Training Laboratory of IC Design at Voronezh State University, another example, develops schematic-based designs in IC design, testing, and application. However, a review of the information pages of the units (as a form of laboratories, institutes, departments, faculties, universities, or centers) shows that the research processes depend on mainly state sponsorship and grants and are less commercialized, which results negatively in bringing ambitious talents and continuous improvement of material, technological and technic bases.

Lithography

On lithography machine construction, there are now three giant lithography machine companies worldwide, namely ASML in the Netherlands, Nikon in Japan, and Canon in Japan. In 2021, ASML has grown to be the absolute leader in the field of lithography machines, with a global market share of nearly 70%, and it monopolizes 100% of the market for high-end EUV lithography machines.

Recent information demonstrates that the lithography sector is the most serious break in the Russian semiconductor system. At a scientific seminar at the National Center for Physics and Mathematics (NCFM) dedicated to EUV lithography and prospects of a Russian EUV lithograph for microelectronics, Nikolay Chkhalo, head of the Department of multilayer X-ray optics at the Institute for Physics of Microstructures (IPM) RAS said a domestic lithograph with a wavelength of 11.2 nm for the production of next-generation microcircuits is being developed by scientists from the Institute of Physics of Microstructures (IPM) RAS by 2030.

China, a close ally of Russia in international relations, also lacks sustainable experience and potential in the field. The top Chinese photolithography firm, Shanghai Micro Electronics Equipment (SMEE), has existed for 18 years, but its most sophisticated tool operates at the 90 nm node, about eight generations (16 years) behind the currently leading 5 nm node. And even SMEE’s 90 nm tool is only a prototype without any sales.

Furthermore, the lithography machine is a complex structural equipment, and its main components include several major parts which consist of the laser light source, the objective lens system, the table system, the mask table system, the mask transfer system, the silicon transfer system, and the exposure system. The exposure system consists of a projection objective lens and illumination system, which is the core of the lithography machine. This means that parallel research, development, and investment are needed to build lots of different parts of a single EUV machine for businesses or government organizations.

Chip design

Chip design is the process of designing a chip and is an essential part of electronics engineering. This process of chip design involves the knowledge of circuit design and its logic formation. All chips are made using basic elements which are known as transistors. Two of the major players in the chip design tool market are Siemens and Cadence, alternatives to whom cannot be found in Russia.

However dependent on foreign counties for tools its chip designers are, the Russian government tends to support the fabless model, giving design companies a very large preferential tax policy. The corporate income tax rate has even dropped from 20% to 3%. In the Catalogue of Russian Organizations for International Cooperation in Semiconductor Design prepared under the EU-funded FP7 SEMIDEC project in 2010 (despite the date being old, the information provided in the document is rare in the sources and important to see a façade of the industry), 29 units were listed in the chip design area (Table 2). Further analysis of the data shows several critical points. Firstly, semiconductor materials are diverse including silicon, germanium, gallium arsenide, and sapphire. Secondly, there are operating private and state organizations unlike to R&D laboratories system. Thirdly, the industrial actors are agglomerated mostly in Moscow, Zelenograd, and St. Peterburg. The facts such as the existence of the private sector companies and the usage of four types of semiconductor materials give a positive signal in conclusion.

Providing that the US chip industry also is clustered mainly in California, the third factor possesses less impact on development. In the end, the task to reduce the dependency on foreign chip design tools remains a problem part to be solved.

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Fabrication

Although there are several domestic chip manufacturers in Russia (Mikron, JSC MCST, and Baikal Electronics), they were highly dependent on the supply of finished semiconductor products by foreign vendors such as SMIC (China), Intel (USA), and Infineon (Germany). As for contract manufacturing, JSC "MCST" and "Baikal Electronics" mainly used the services of factories in Taiwan and Europe.

At the end of May 2022, it became known that the MCST company, which is the developer of the Russian Elbrus processors, is negotiating the possibility of transferring their production to the Russian Mikron factory.

The main domestic manufacturer of microprocessors, the Zelenograd-based Mikron, now mainly produces chips for bank and transport cards and RFID tags. The company also fell under sanctions, and the thinnest process technology it has mastered is 65 nanometers. Mikron claims 54% of Russian microelectronics exports.

Other than Mikronm the production of the two companies is less than 100nm. Crocus Nano Electronics reports that it is the only company in Russia capable of mass-producing new-generation non-volatile resistive memory based on the 55 nm ULP (Ultra Low Power) process. And the third company, Syntez Microelectronics, which fabricates dies at a 65 nm scale, has outsourced the process to Freescale, XFAB, and other foreign and Russian partners. Reliance on foreign fabs generates uncertainty and instability in the supply of modern chips by Syntez Microelectronics.

Education and training capacities

A degree in materials science and engineering or a related field, such as applied physics with materials science or electrical engineering, is considered usually a good background for those interested in a career as a semiconductor engineer. According to the QS university ranking, 15 universities teaching Electrical and Electronic engineering (Table 4) and 13 universities teaching Material science (Table 5) are included in Top-1000 in 2023. It is noticeable that ITMO University and Moscow Institute of Physics and Technology are ranked at higher positions in both subjects. The facts show that Russia possesses adequate training potential at its universities and institutes to provide the industry with specialists.

Furthermore, education along with R&D is a more mobile and borderless stage of the supply chain in contrast to the mining of raw materials and fabrication process. Researchers are flexible to being engaged in laboratories and centers from universities of different countries. In the meantime, students may travel and study at more universities around the world. Online education and remote training opportunities have also accelerated the mobilization of human capital. These factors allow an accessible climate for industries, including the semiconductor production sector of Russia, to acquire know-how and knowledge and enrich the organizations and companies in the field with high-portfolio cadres.

International Trade

Since the crisis in Ukraine, several sanctions, restrictions, and boycotts have been being exchanged between Russia and the “collective West”, which result in the disruption of the trade of several goods, including semiconductors import to Russia. For example, the European Union (the EU) banned the export of cutting-edge technologies to Russia listing advanced semiconductors and electronic components among them. The export-banned products list has covered laptop computers and computing components in the 9^th package and electronics goods in the 10^th package of the EU sanctions. Furthermore, Australia, New Zealand, Norway, and Canada have joined as partner countries to the EU.

In a White House report on February 24 in 2022, the United States imposed restrictions on semiconductors, telecommunication, encryption security, lasers, sensors, navigation, avionics, and maritime technologies. The global computer chip industry, including the giant Taiwan Semiconductor Manufacturing Company, began halting sales to Russia in the wake of U.S. sanctions. In February of 2023, Japan announced the restriction of the delivery of items, and semiconductor equipment too, to 49 organizations in Russia. In April 2023, South Korea decided to expand the scope of its export controls over items, including semiconductors, in its trade with Russia and Belarus.

On the other hand, the data also showed that China exported a total of US$312.93 million worth of semiconductors and integrated circuits to Russia in 2022, up from US$231.97 million in 2021, or a year-on-year increase of 34.9 percent. Moreover, In an interview with RIA Novosti, Malaysian Ambassador to Moscow Bala Chandran said that the authorities of his country would consider any request from Russia regarding the supply of semiconductors and electronics. The Malaysian Ambassador to Moscow added that he did not yet know anything about possible negotiations at the government level, but at the same time expressed hope for a dialogue between businessmen. It is noticeable that most of the South-Eastern Asian countries as well as India have been continuing their trade with Russia. Singapore is the only state that supported the sanctions on Russia.

In the end, the Russian opportunities for semiconductor trade are divided into two groups: 1) the countries that have restricted semiconductor exports and 2) the countries that have been continuing their trade. The former group has been playing a lower role in terms of transfers until 2021 (Graph 1) while advanced chips and production technologies are provided by companies and organizations of those countries. The latter, such as China, Malaysia, and Vietnam are the top three semiconductor providers of Russia and remain in their sound relations with Moscow. However, the second group also depends on the technologies developed by the United States, Germany, Japan, South Korea, and the Netherlands and is at risk of secondary sanctions. As a result, a dilemma of Eastern markets or further sanctions has appeared in discussions of the “Collective West” and the polarization of the tech world is increasing.

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Overview

In Russia, overall 99 units are found to be in the semiconductor industry or training cadres for the sector directly or indirectly. The highest share (28 units) belongs to top-1000 universities/institutes which are teaching either materials science or electrical engineering. This gives a clear advantage for Russia to develop the industrial knowledge relied on the national education system. R&D potential (17 units) is also noticeable to enable to innovate at a substantial level. These two stages together account for nearly half of all units in the Russian semiconductor industry. The production of standard-purified silicon wafers and the construction of DUV/EUV machines (0 units) have been exposed as the main problems Russia faces.

The collected information about the actors in the Russian semiconductor industry (Graph 2) displays two lines of agglomeration: The Western line and the Southern line. The Western agglomeration (Graph 3) starts from Saint Petersburg, crosses Zelenograd and Moscow, Voronezh, and ends in Voronezh. It includes 64 objects or about 2/3 of the industrial potential. The locations are connected via M-11, MKAD, and M-4 routes and both sites of the line are open to the sea trade. The disadvantage of this agglomeration contains its distance from the growing markets in China, India, and East Asia as well as ally or neutral countries to Russia.

The Southern line of agglomeration, around a 6000 km automobile route, stretches from Chita, a site of caustobiolites mine for germanium, and reaches to Shelekhov (silicon) and Achinsk (Gallium) mines of RUSAL. In westward, Novosibirsk and Tomsk, destinations of R&D, training, fabrication, and design capacities, are located. Despite its relatively modest magnitude than the Western agglomeration, the area possesses an opportunity to be developed as a tech hub between China and Russia.

Conclusion

In the context of the technological and technical advances in the Fourth Industrial Revolution, the realities of geopolitics (cyber world, competition for space) are emerging, which makes a hybrid structure of powers a necessity. The weaponry of the existing fields (sea, land, air) is being re-innovated with intelligent systems, unmanned aerial vehicles, drones, etc. However, nearly all of these innovations are based on the computation and memory that are provided by chips.

The Analysis of the semiconductor industry in Russia reveals several aspects of this significant sector of the new geopolitical era. First of all, the agglomeration of the actors along the Western and Southern lines. Secondly, the main strengths and opportunities of the industry in Russia include abundant resources, R&D capacities, and cooperation with China. Thirdly, the negative impact of the insufficient development of modern semiconductors production and the absence of lithography construction, are increased with sanctions, mainly by the European Union. Finally, the semiconductor industry of Russia needs more radical changes such as diversification, and regrouping of actors to raise its competitiveness.

You can read the research with tables and SWOT analysis in a pdf version.

Author: Shakhboz Juraev is the Chief Coordinator of Technology in Global Affairs. He is the author of the book "Hybrid Strategy of Cybersecurity: The Role of Information Technology Companies in Chinese Cybersecurity Policy”.

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Israel is the single country with a semiconductor ecosystem in the Middle East. The industry in Israel is characterized by its multi-dimensional relations with Asian, American, and European companies. It reflects on joint projects, the acquisition of designing and manufacturing facilities, and start-up exports to foreign companies. These features develop based on the talent sector and free market rules. Similar elements also play a crucial role in the rise of India’s semiconductor sector. However, close ties of Israel with the United States and the European Union enable it to bring more advanced production in the country than that of neutral India.

Joint projects with foreign companies provide an inflow of know-how and industrial security. Tower Semiconductor, headquartered in Migdal Haemek, possesses manufacturing units in Newport Beach and San Antonio in the United States besides two facilities in Israel. These factories are specialized in producing CMOS, CIS, Power, Power Discrete, MEMS, and RF Analog. STMicroelectronics of Switzerland collaborates with Tower Semiconductor to manufacture 65nm Analog RF, Power, and Displays in Agrate capacity in Italy while Intel grants the Israeli company with foundry services in New Mexico. Moreover, TPSCo-Tower in cooperation with Nuvoton Technology Corporation Japan (NTCJ) produces Analog, Power Discrete, NVM, and CCD in Tonami and Analog, CMOS, CIS, and 45 nm RFCMOS/ SOI in Uozu. However, the Indian government blocked an 8 billion USD wafer fab proposal of Tower Semiconductor.

Tower Semiconductor through its subsidiary, Jazz Semiconductor, can participate in US government programs and the Newport Beach facility plays a key role in this partnership. In 2013, Jazz Semiconductor Trusted Foundry of Jazz Semiconductor was indexed by the US Department of Defense’s Defense Microelectronics Activity as a Category B1 Trusted Supplier. The Defense Microelectronics Activity program is responsible for “the integrity and confidentiality of integrated circuits during design and manufacturing while providing the US Government with access to advanced microelectronics technologies for both Trusted and non-sensitive applications.”

The acquisition of designing and manufacturing facilities to the country is another critical component of Israel’s semiconductor industry. As Tower Semiconductor leads partnership projects with foreign companies, Intel's role in bringing capacity to Israel is remarkable. Intel operates a 10nm manufacturing facility in Kiryat Gat, a hardware and software development center for processors and AI in Haifa, a communication and AI solutions development center in Petah Tikvah, and a communications, software, and cyber security development center in Jerusalem. In 2022, Intel exported operations in 8.7 billion USD, accounting for 5.5% of Israel’s high-tech exports and 1.75% of the country’s GDP.

Apart from Intel, Qualcomm (in Haifa, Hod Hasharon) Marvell (in Yokneam, Petah Tikva) Nvidia (in Tel Aviv), NXP (in Yokne'am Ilit), and Samsung (in Herzliya) possess R&D centers in Israel.

Start-up export is a way to bring know-how and technological development to Israel. Successful start-ups are partially or fully sold to a foreign company linking international and national businesses. In 2017, Intel acquired 97.3% shares of Mobileye, a producer of components for autonomous driving. Habana Labs, another company purchased by Intel, mainly specializes in data center training, artificial intelligence, and deep learning products. In addition to Intel, NVIDIA (Mellanox), Medtronic (Mazor Robotics), Google (Waze), and IBM (Trusteer) bought billion-dollar Israeli tech start-ups.

The Israeli semiconductor industry's success depends on the country's talent sector and free market. Technion – Israel Institute of Technology containing 4 campuses (Haifa, Tel Aviv, Cornell Tech, and Guangdong Technion Israel Institute of Technology) is considered the key factor contributing to training technology specialists. The Electrical and Computer Engineering faculty at the institute consists of 40 labs and 11 centers. Along with Technion, Tel Aviv University, Hebrew University of Jerusalem, and Ben Gurion University of Negev are also key engineer-training units in Israel whose graduates account for the most staff in semiconductor facilities.

In this manner, Israel resembles India where education at national universities is a critical factor in attracting the semiconductor industry to the country. In turn, both countries have geopolitical hurdles that make foreign companies hesitate to establish new facilities. Indian government is in a good-balanced position with both the West and Russia which keeps Western countries away from bringing strategic products to India. Meanwhile, Israel is located in geopolitically risky territory. The Houthi attacks in the Red Sea demonstrate how fragile the Israeli industrial supply chain is. In other words, the development rate of the industry in Israel is somehow parallel and proportional to the reliability of iron-dome-style systems. However, the Iron Dome is not tested against missiles produced in factory standards.

From the point of security, Israel's semiconductor sector could be divided into four categories. The first is foreign R&D and designing capacities that are mobile to evacuate in case of emergency. The second includes the facilities of Tower Semiconductor that are located in the safe zones overseas. The third is Intel’s high-tech facility in Kiryat Gat which belongs to an American company. The fourth is the national companies (Hailo, Valens Semiconductor, TriEye, Vayyar Imaging) that are both mobile and fragile to the crisis in Israel.

By sector, semiconductors for autonomous systems are the major area of the industry. Hailo, Valens Semiconductor, and TriEye produce components for autonomous vehicles. Mobileye is among the leaders of chip makers for self-driving cars. Mobileye produces EyeQ chipset packages for the autonomous car industry.

To wrap up, Israel has a globally multi-tied semiconductor industry based on national talent pool and market rules. However, the industry is located in geographically fragile zone although Tower Semiconductor’s capacities have been outsourced in secure zones in the United States, Japan and Italy.

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India along with Indonesia, Malaysia, Vietnam, Mexico, and Costa Rica is a candidate state to receive a semiconductor ecosystem in case of an emergency around Taiwan. The country's current state in the industry is characterized by its talent pool in the designing sector (20% of global semiconductor design engineers), unbalanced development among semiconductor-related sectors, and promising projects. Moreover, India possesses the characteristics of the largest population for sales, access to the Indian Ocean for international trade, and managers at the top global companies to import know-how.

Bangalore is home to more than 1 million software engineers plus around 90,000 graduates from local universities. The city houses 14 semiconductor designing centers and R&D facilities of international and national top companies such as NXP Semiconductors, Infineon Technologies, NVIDIA, AMD, MosChip Technologies, and Tata Elxsi. In Bangalore, SITAR Society operates MEMS and CMOS production facilities processing 500nm in 150mm wafers in cooperation with the Defense Research and Development Organization under the Ministry of Defense.

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Hyderabad is the second most well-known semiconductor center of India where another production facility of SITAR Society is located. The facility (GAETEC) manufactures 500nm MESFET for strategic and security purposes. In addition to this, Intel, MosChip Technologies, and NXP Semiconductors own design or R&D centers in Hyderabad.

Pune, Noida, Chennai, and Gujarat are among the Indian cities actively attracting and building a semiconductor ecosystem. Punjab hosts Semi-Conductor Laboratory under the Ministry of Electronics and Information Technology that is equipped with 180nm technology and specializes in VLSI design, and CMOS and MEMS fabrication. The laboratory also contains VLSI assembly, packaging and testing, and MEMS testing services. SPEL Semiconductor of Natronix in Chennai is considered as India's only IC assembly and test facility.

Bangalore holds a leading position according to semiconductor start-ups with AGNIT Semiconductors, Aura Semiconductor, FermionIC, Saankhya Labs, and SignOff Semiconductors. There are 2 start-ups (InCore Semiconductor and Mindgrove Technologies) in Chennai. Hyderabad and Greater Noida each have one start-up (Silizium Circuits and Vervesemi).

Indian Institute of Technology plays a central role in training engineers in the country. The Institute consists of a network of 23 institutions. Indian Institute of Science, Vellore Institute of Technology, Birla Institute of Technology and Science, and SRM Institute of Science and Technology are included as Indian top electrical and electronic engineering education organizations.To support semiconductor education, Lam Research trains 60,000 engineers through its Semiverse Solution virtual fabrication platform and Applied Materials allocates 400 million dollars to launch an engineering center in India.

Along with knowledge sectors, promising projects are announced in the field of assembly, testing, and packaging. Micron under the support of the Indian government released its plan to build an assembly and testing facility in Gujarat for DRAM and NAND products. Another facility in Gujarat is projected in Sanand by CG Power, Renesas Electronics of Japan, and Stars Microelectronics of Thailand to provide ATMP service. Morigoan in Assam is expected to receive an ATMP unit of Tata Semiconductor Assembly and Test Pvt. Dholera in Gurajat is masked as the home to the first Indian fab Tata Electronics and Powerchip Semiconductor of Taiwan.

In an overview, India is growing as a lucrative hub of engineers that serves to draw the attention of global semiconductor giants and feed the demands of local enterprises. On the other hand, semiconductor manufacturing, mining of industrial minerals, and wafer production sectors of India remain underdeveloped. For example, there are overall 3 manufacturing facilities, 2 ATP, and 2 gallium mines (Hindalco Industries at Renukoot in Uttar Pradesh and National Aluminium at Damanjodi in Odisha) in the country. To mitigate the situation, the government and private sector are supporting facilities with national and international companies such as Tata Electronics, Micron, and Powerchip Semiconductor. Although there is a long way for India to become a self-maintaining semiconductor power, Bangalore, Chennai, and Hyderabad in the country are good examples of how to start and gain a share in this industry.

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The data about the locations of semiconductor manufacturing facilities is collected from open sources and visualized under the Semiconductor Geography project. You can see the map of Semiconductor manufacturing facilities in Google Maps in a more informative and detailed form by clicking the link.

Google Maps

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Semiconductor manufacturing is highly concentrated in a few regions clustering in the United States, the European Union, and East Asia. Around 92% of facilities are located in these three regions. Furthermore, the most advanced semiconductors that are printed smaller than 14nm are produced in the facilities of these regions.

East Asian cluster accounts for about 66% of manufacturing facilities with 292 sites in number. The region holds three-fourths of global chip production. Taiwan manufactures 60% of semiconductors and 90% most advanced semiconductors in the world while Korean companies play a dominant role in the memory chip market with more than 60% share.

American cluster accounts for about 17% of semiconductor manufacturing facilities. There are 76 facilities concentrated in Oregon, Arizona, Texas, and California. These four states embrace more than half of manufacturing facilities in the United States. However, the US shows a decreasing trend of chip manufacturing from 37% in 1990 to 12% in current times.

European cluster includes 37 out of global 438 manufacturing facilities. Germany plays a central role in the European Union with 20 facilities and a 22nm printing capacity overall. In terms of the processing technology, facilities in Ireland and the Netherlands can print 14nm and 10nm semiconductors accordingly. The European Union gives less than 10% of manufactured global semiconductors.

Gray zones are characterized by the sparse location of manufacturing facilities in the different regions of the world. These zones cover Africa, Latin America, the Middle East, Central Asia, East Europe, and Australia. The Gray zones can be divided into high-potential countries (Russia, Israel, India, Costa Rica, Switzerland, etc), medium-potential countries (Brazil, Argentine, Australia, etc), and low-potential countries (countries without any semiconductor facilities) according to the existing capacity of processing technologies in the facilities, resources, companies and scientific environment.

In terms of cities (municipalities), 34 fabs are operating in Hsinchu while Singapore possesses 15 facilities. Shanghai with 12 fabs can be seen as the center of Chinese semiconductor manufacturing and Dresden has the highest number in Germany with 5 facilities. Chandler and Hillsboro with 6 fabs are the leaders among the cities in the United States.

The data about the locations of semiconductor manufacturing facilities is collected from open sources and visualized under the Semiconductor Geography project. You can see the map of Semiconductor manufacturing facilities in Google Maps or Google Earth in a more informative and detailed form by clicking the link.

View in Google Maps

View in Google Earth

If you have noticed any inappropriate information and you have a source of accurate information to replace it, Technology in Global Affairs is open to receive your messages via: technologyglobal.official@gmail.com.

All messages are reviewed and passed through a fact-checking process. If the information is approved, the page is updated according to it.

Semiconductor Geography project aims to collect and systemize information about the location, production type, and the number of facilities related to the semiconductor supply chain. It helps to understand the geographical agglomeration of capacity and potential crisis zones in the industry. In its early stage, the project contains information only about the leaders in the semiconductor supply chain.
In its next stages, the project intends to cover the production capacities of facilities, capacities in more countries, and start-ups.
In subsequence, Technology in Global Affairs publishes updates and alerts about changes and trends in the industry wrapped in the Semiconductor Geography project. Furthermore, the project will be enriched with updates and country profiles.

It is noticeable that the global economy is connected through supply chains. Semiconductor production also includes manufacturing capacities and facilities from silicon mining to assembling and testing that are located in the territories of different countries. Recent disruptions in the food and energy supply chain after the crisis in Ukraine have exposed the significance of monitoring key actors of an industry to avert or mitigate the consequences. The research aims to develop a map of the semiconductor supply chain through the geographic locations and consideration of facilities of industry leaders to determine focal points. In the study, 55 countries were identified to be involved in the process at different stages and degrees. The concentration of the industry around the Pacific is noticed and analyzed as its vulnerability to military and environmental crises.

The Western sanctions after the Ukrainian crisis and Russian responsive politics through energy resources have demonstrated how the world is interconnected and what an interruption in a supply chain of goods eventually brings. Initially, a jump in gas prices triggered inflations in economies recently recovering from global lockdowns. Subsequently, the restrictions on agricultural fertilizers put developing countries under the pressure of food shortages. Finally, sectors related to electronics run up to the problem of semiconductor scarcity when the provision of neon gases from Mariupol is disrupted.

Those expose that a serious political, economic, financial, social, or environmental crisis in a point of the world directly or indirectly influences another sector and country through supply chains. It means that a colossal delay in the industry, for example, a Chinese missile strike on Taiwan Semiconductor Manufacturing Company (TSMC), slows down or suspends the strategic development of a substantial number of countries. For this reason, this policy brief analyzes the sustainability of critical sites in the semiconductor supply chains as microchips are becoming an integral part of technology and techniques from military tanks through modern automobiles to personal laptops. In consequence, a model to better understand and be prepared for upcoming turbulences is aimed to be promoted.

Methodology

In the research, the supply chain is, primarily, dismantled to identify key products and services. It includes the extraction of raw materials, designing, manufacturing, and assembling and testing. ASML, a Dutch company that has nearly monopolized the construction of lithography machines, and its providers are also underlined in the meantime.

The selected components and services, simultaneously, are designated to their main companies with geographic locations one by one. Accordingly, the influential actors in the supply chain are classified by measuring the scale of their impact. Finally, the geography of the semiconductor industry is clarified for risk management, anti-crisis planning, and strategic development in the sector.

As the work intends to develop a structured map of the semiconductor supply chain and demonstrate the more and less important points in the industry, this policy brief does not include academic debates and possesses an explanatory character that may support further research.

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Silicon mining and wafers

Silicon, gallium arsenide, and germanium are mostly used raw materials in semiconductor production. Since the 1950s, silicon, the most abundant element on earth after carbon, has already surpassed germanium despite its conductivity with four valence electrons. Gallium arsenide with overall eight valence electrons has fallen into the second due to its compound and toxic qualities. In nature, silicon typically contains large amounts of impurities and so the initial stages of the manufacturing process are concerned with the reduction and purification of the silica sand to produce metallurgical grade polysilicon, typically >98% pure silicon.

The total global production of silicon in 2022 was an estimated 8.8 million metric tons, of which around 6 million metric tons belong to China. The provinces of Xinjiang (40%) and Yunnan (20%) account for more than half of silicon mining in the country. Furthermore, the SINOSI Group reports that their silica mines including quartz and crystal cover the provinces of Hebei, Jiangsu, Sichuan, Tibet, Gansu, Shanxi, Anhui, and Jiangxi provinces in China. The countries such as Russia (640 000 metric tons), Brazil (400 000 metric tons), Norway (360 000 metric tons) and the United States (310 000 metric tons) follow China with a sizeable difference.

In the next step, the large crystals are cut down to shape and then cut into silicon wafers by bandsaws or diamond saws. Wafers require a lot of beveling, heating, and polishing to achieve exact parameters for dimensions and smoothness. The processing of silicon wafers often involves various further processing steps. Finally, the wafers are inspected, packaged, and delivered to the customer as raw material for the manufacture of MEMS, sensors, RF devices, or power devices. According to IMARC Group, the global silicon wafer market size reached US$ 11.6 Billion in 2022. The leading manufacturing facilities of silicon wafers are predominantly owned by East Asian companies and located in the region. Moreover, the US and German giants have outsourced to Eastern and Southeastern Asia (Table 1).

Manufacturing

In the fabrication stage, the clean wafers are combined with designed layouts. Since the “fabless revolution, when US companies outsourced their manufacturing to avoid the costs of building fabrication facilities, three types of semiconductor companies have emerged: designing-oriented, manufacturing-oriented, and hybrid (containing both designing and manufacturing facilities). Semiconductor designing is linked with a knowledge-based economy and protected by patents and licenses and complexity to imitate while fabrication centers around cost-effective cheap labor and advanced lithography machines.

Data collected from about 24 companies (Table 2) show that the semiconductor industry is clustered in four countries: USA (13 headquartered companies, 44 manufacturing facilities), China (2 headquartered companies, 22 manufacturing facilities), Taiwan (3 headquartered companies, 19 manufacturing facilities) and Japan (2 headquartered companies, 13 manufacturing facilities). Even though the US is leading by the number of manufacturing units, 4 out of the top five semiconductor foundry companies (TSMC, Samsung, UMC, GlobalFoundries, SMIC) are located in East Asia and Taiwan, China, and South Korea combined for roughly 87% of the global foundry market.

The current architecture indicates that the East Coast of the Pacific is crowded with plants while the other coast of the ocean emphasizes innovation, capital, and management. For instance, Nvidia, AMD, Marwell Technology Group, and Qualcomm, according to the current data (Table 2), outsource their fabrications. In addition, the role of Europe is also marginalized with 3 companies and 17 fabrics in this phase.

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Designing, R&D, and training of specialists

Designing is a complicated operation on semiconductors that necessitates research and skilled engineers to provide stable development of the industry and competitiveness of companies. Intel research and development expenses for the twelve months ending December 31, 2022, were $17.528 billion, a 15.39% increase year-over-year.

Advances in chip manufacturing require etching ever-smaller transistors onto silicon wafers. IBM, in May 2021, unveiled a breakthrough in semiconductor design and process with the development of the world's first chip with 2 nanometer (nm) nanosheet technology. In an announcement of TSMC, the first fab of the company in Arizona is scheduled to begin production of 4-nm process technology in 2024. In addition, TSMC has also started the construction of a second fab which is scheduled to begin production of 3nm process technology in 2026. Samsung Electronics, in June 2022, announced that it has started the initial production of its 3-nanometer (nm) process node applying Gate-All-Around (GAA) transistor architecture.

More detailed statistics about the types of chips (Table 3) present that US companies occupy the most diversified industrial climate. Only Samsung of South Korea in DRAM and NAND memory integrated circuits and NXP Semiconductor of the Netherlands in microcontrollers outperform their North American counterparts. In view, it is noticeable that the Pacific region countries, except NXP Semiconductor of the Netherlands and STMicroelectronics of Switzerland, are excelling in several models of chips.

However, the geography of research and development (Table 4) shifts toward the Trans-Atlantic region. 177 of 258 semiconductor research laboratories are in Europe and 40 of them are in the United States and Canada.  The core countries of NATO (United Kingdom, United States, Germany, and France) bear 46.9 percent of that total number. Three full members (Russia, Belarus, and Armenia) of CIS contain 25 R&D facilities.

Lithography

Lithography refers to a graphic micromachining technology that uses the chemical sensitivity of photoresist under the action of visible light, ultraviolet light, and electron beam to transfer the graphics designed on the mask to the substrate through the process of exposure, development, and etching. There are now three giant lithography machine companies worldwide: ASML in the Netherlands, Nikon in Japan, and Canon in Japan. In 2021, ASML has grown to be the absolute leader in the field of lithography machines, with a global market share of nearly 70%, and it monopolizes 100% of the market for high-end EUV lithography machines.

ASML outsources approximately 90% of the value of the scan-and-step systems it produces. ASML outsources 90% of the process to over 400 suppliers in the southern Netherlands, the Ruhr area of Germany, the EU countries, Asia, and the US. Zeiss produces the optical systems used in ASML’s machines, in particular the highly complex and expensive projection lens. Deep ultra-violet light sources are developed, manufactured, and serviced by Cymer, an independent business within the ASML group. In 2016, as part of a mutually beneficial agreement, ASML acquired HMI, a well-regarded name in the semiconductor industry for its sophisticated e-beam inspection systems.

The top Chinese photolithography firm, Shanghai Micro Electronics Equipment (SMEE), has existed for 18 years, but its most sophisticated tool operates at the 90 nm node, about eight generations (16 years) behind the currently leading 5 nm node. SMEE struggles even to produce photolithography steppers: earlier-generation photolithography tools are used both for making less advanced chips as well as for the packaging stage of chip production, in which finished wafers are turned into completed chips. Meanwhile, China has no presence in the markets for electron-beam and laser lithography tools. These tools are necessary for producing the photomasks used in photolithography and for low-volume production of chips; and they are made only by U.S., Japanese, German, and Swedish firms.

Assembling, testing, and packaging

The semiconductor assembly and test process flow is: the wafer from the wafer pre-process is cut into small wafers (Die) through the scribing process, and then the cut wafer is mounted with glue onto the corresponding substrate (lead frame) frame island. Then the wafer's bond pad is connected to the corresponding lead of the substrate using ultra-fine metal (gold, tin, copper, aluminum) wires or conductive resin. After sealing, a series of operations are performed, such as Post Mold Cure, Trim&Form, Plating, and Printing. Then, the finished product is tested, usually through Incoming, Test, and Packing processes, and finally warehoused for shipment.

The back-end part of semiconductor production is collected in East and South-East Asia where 9 of 10 top companies are headquartered and 42 facilities are being operated. In 2020, more than 46% of the market share belonged to Taiwanese companies, respectively 30% to ASE Holdings, 8.18% to Powertech, 3.11% to KYEC, 2.47% to ChipMOS and 2.39% to Chipbond. There is only Amkor among the top 10 from the United States and a facility of ASE Holding in California. The role of Europe at this stage is marginal with Amkor’s facility in Portugal.

The final map of the semiconductor supply chain

During data collection about the semiconductor supply chain from silicon mining to packaging, the top companies of the industry are covered and the locations of their headquarters and facilities are assigned to regions and states. It is determined that 57 countries at different degrees and stages participate in the semiconductor production process of high-portfolio companies. In the end, it is possible to classify countries into three groups: main actors, medium actors, and small actors.

The first group includes countries that are engaged in 6 or more stages of the production line. They are the United States, China, Japan, Taiwan, South Korea, and Germany. Exceptionally, the Netherlands is involved in this category due to its 100% manufacturing of EUV lithography and 70% construction of DUV machines. Furthermore, top companies in the semiconductor industry are rooted in the territory of these states. All of these make them the focal points of the semiconductor supply chain as long as a colossal crisis in these territories influences the technological and technical security and stability at the global level.

The second group contains several companies and facilities that produce a small part of semiconductors. These countries are France, Malaysia, India, Australia, Italy, Finland, and Singapore. This group of actors has built the initial bases to develop further in the industry. The next phase whether they will progress or decline depends on the governmental and corporate ambitions and reforms.

Finally, the last group of actors plays a marginal role in the supply chain with few resources and facilities. Three countries, Russia (second in silicon mining, fourth in research laboratories), Great Britain (first in the research laboratories, third in specialist training along with Australia), and Switzerland (home of STMicroelectronics) are paradoxically joined into this group as long as they have not materialized their advantages yet

Conclusion

The geography of the semiconductor supply chain is found diverse and accumulated at the same time. The agglomeration partially depends on the patent and license rights, the complexity of the production to imitate, and the monopoly of lithography machine-building. Countries with successful innovation and know-how by R&D centers, universities, and institutes usually protect their invention with patents and licenses. As a result, the semiconductor industry is being centralized in East Asia, the United States, and the Netherlands. Simultaneously with centralization, the risk of crisis in the supply chain is also increasing.

First of all, the main threat is connected with the ambitions of Beijing toward Taiwan. This island, which mainland China considers a rebellious territory, is important for the Chinese government to end the contradictions officially. From the point of geopolitics, the occupation promotes direct access to the Pacific breaking out the pro-American line from Northern Japan through Taiwan to Southern Philippines. Ideologically, Beijing will be able to rewrite the role of the Chiang Kai-shek government in the current World order based on the Yalta-Potsdam negotiations. Otherwise, the Republic of China remains an actor during the World War and documentation of modern systems of global affairs. A clash between China and Taiwan puts two centers of the semiconductor industry at risk of supply chain interruptions.

Secondly, the uncertainty in the Korean Peninsula jeopardizes the industrial climate in South Korea, where companies such as Samsung and SK Hynix, leaders of the memory chips phase, operate. In case of a military crisis between North and South Korea, the semiconductor companies and facilities are likely to be destroyed or re-specialized for military orders. In both situations, the supply chain will be shaken severely.

Thirdly, 5 of 7 focal points (the USA, Japan, South Korea, Taiwan, China) are located around the Ring of Fire, where about 81% of the world’s largest earthquakes occur. United States Geological Survey informs that California has more earthquakes that cause damage than any other state. Semico Research considers fabs in Japan, Taiwan, and the west coast of the United States to be in the high-risk areas for earthquake activity. Moderate-risk areas include China, Malaysia, Singapore, South Korea, and certain additional areas in the western US. Thirty-seven percent of all fabs are in these high-risk areas, with another 24% in moderate-risk locations. In terms of capacity, 36.7% are in high-risk areas, with another 39% in moderate-risk areas.

Conclusively, the concentration of the semiconductor industry around the Pacific coasts is vulnerable to military and environmental crises. Simultaneously with complications of the production process and lithography machine constructions, inequality of shares in the supply chain is growing. However, diversification of actors around the globe is recommended to avoid the crisis in technological and technical development due to a semiconductor shortage.