In the ever-evolving digital era, artificial intelligence (AI) has become a primary driver of innovation and transformation across various sectors. However, this immense potential also brings significant challenges related to the security and ethics of AI implementation. Developing countries face unique challenges in ensuring that AI technology is applied safely and responsibly. This article discusses the approaches to assessing the security suitability of AI technology in developing countries, drawing lessons from benchmark countries such as the United States, China, the European Union, and the United Kingdom.
The United States, although not yet having a comprehensive AI regulatory framework at the federal level, has seen agencies like the National Institute of Standards and Technology (NIST) issue guidelines for responsible AI development. Their primary focus is on the security, safety, and resilience of AI systems, as well as the development of unbiased and fair AI, with efforts to protect individual rights in the use of AI technology. China has also taken significant steps in AI security through various regulations such as the “Next Generation Artificial Intelligence Development Plan” and “Governance Principles for a New Generation of Artificial Intelligence.” China’s focus is on national security, social stability, and enhancing public welfare.
The European Union, through the “Artificial Intelligence Act,” regulates AI development and use based on risk levels, with requirements for high-risk AI systems such as impact assessments, transparency, and human oversight. The EU places great emphasis on protecting human rights and fundamental values and promoting the development of trustworthy and transparent AI. The UK, through its “National AI Strategy,” aims to be a global leader in ethical and responsible AI development, with principles such as security, fairness, transparency, and accountability. The UK also emphasizes the importance of AI system security and resilience, as well as the development of explainable and unbiased AI. Based on the approaches taken by these benchmark countries, developing countries can adopt several important measures.
Capacity Building and AI Education
Developing countries need to prioritize capacity building and education in the field of AI. Comprehensive training and education programs should be developed to ensure the availability of experts capable of developing and applying AI technology safely and ethically. To develop AI talent, developing countries should invest resources in curricula that include data science, machine learning, and cybersecurity. Collaboration with universities and other educational institutions is crucial to creating relevant and up-to-date study programs.
Moreover, public education on AI literacy and its applications should also be prioritized. This includes educational programs that explain the basics of AI, its potential benefits, and the risks associated with its use. By increasing AI literacy among the public, they will be better prepared to face technological changes and can utilize AI for daily needs, such as in health, education, and public services.
To ensure that all segments of society benefit from AI technology, training programs should be provided for various skill levels. From basic training for beginners to advanced programs for professionals, all should be designed to equip individuals with the necessary skills in this digital era. Holistic education and training will not only help develop AI and cybersecurity experts but also raise public awareness and understanding of AI technology, enabling them to use it wisely and responsibly.
Utilizing AI for Socio-Economic Development
AI strategies in developing countries should be directed towards addressing urgent socio-economic issues such as poverty, health, education, and agriculture. A concrete example of AI application in combating poverty is through more efficient social assistance programs. AI can analyze demographic and economic data to identify families in need, allowing the government to distribute aid more accurately and reduce resource distribution inequalities.
In the health sector, AI can improve the diagnosis and treatment of diseases. AI systems can help doctors analyze medical images such as X-rays and MRIs quickly and accurately, enabling early detection of diseases like cancer. Mobile AI applications can also provide basic health consultations to people in remote areas, improving healthcare accessibility and reducing the burden on central health facilities.
In the education sector, AI plays a crucial role in personalizing learning. AI systems can identify students’ weaknesses and strengths by analyzing student performance data and recommending appropriate learning materials. AI-based e-learning platforms can provide educational content accessible to students across the country, including rural areas lacking educational resources. AI enhances productivity and sustainability by using sensors and drone technology to monitor soil and crop conditions in real time, helping farmers make more precise decisions, increase yields, and reduce excessive chemical use.
Public-Private Partnership and Digital Sovereignty
Developing countries must encourage collaboration between the public, private, and academic sectors in AI development. This partnership is essential to mobilize resources and ensure AI solutions are relevant to local needs. The public sector can provide data and infrastructure, the private sector offers advanced technology and capital, while academia plays a role in research and training the necessary experts. By combining the strengths and expertise of these sectors, developing countries can overcome existing challenges and create more effective innovations.
Moreover, developing countries should focus on utilizing local resources such as data, infrastructure, and expertise to develop AI solutions that fit the local context. Local data provides specific insights into the needs and problems faced by the community, while infrastructure like internet networks and data centers must be strengthened to support reliable and secure AI operations. Developing local expertise through intensive education and training programs is also important so that the local workforce has the skills needed to manage and develop AI technology.
Utilizing these local resources also contributes to achieving digital sovereignty. By relying on local data and infrastructure, developing countries can reduce dependence on foreign technology and increase control over crucial information and systems. This is important for maintaining data security and protecting citizens’ privacy. Additionally, digital sovereignty allows developing countries to establish regulations and standards that align with their national values and interests, supporting sustainable and inclusive development. Effective collaboration between the public, private, and academic sectors, along with a focus on utilizing local resources, will help developing countries create innovative, sustainable, and sovereign AI solutions, enabling them to address socio-economic challenges and strengthen their position in the increasingly digital global economy.
Strengthening AI Governance and Ethics
It is important to develop a clear regulatory framework to ensure governance and ethics in the use of AI. This includes impact assessments, transparency, accountability, and the protection of human rights. Developing countries, which often only act as users and importers of AI technology, need to implement strict screening of the technologies they adopt. This screening is essential to ensure that imported AI technology fits local needs and conditions.
Additionally, contextualizing AI ethics is crucial to ensure they align with local culture and socio-economic conditions. For instance, ethical principles valid in developed countries may not fully apply or be relevant in developing countries without modification. Therefore, AI regulations must consider local values and norms and the specific challenges faced by the community. This includes considering aspects such as inclusivity, fairness, and social welfare in AI development and implementation.
A clear and contextual regulatory framework will help developing countries protect their national interests and promote responsible AI development. By setting high standards for transparency and accountability, developing countries can ensure that AI technology is used ethically and does not harm society. Protecting human rights should also be a top priority, with policies ensuring that AI is used to enhance the quality of life for all citizens.
Thus, a structured and contextual approach in developing AI regulations will enable developing countries to integrate this technology safely and beneficially. This approach will not only foster local innovation but also help developing countries achieve digital sovereignty with technology that is suitable and sensitive to their local context.
Focusing on AI Security and Resilience
AI system security and resilience must be top priorities. Developing countries need to ensure that the AI systems they develop are resistant to various security threats and reliable under different conditions. This includes ensuring cybersecurity against potential hacker attacks, data manipulation, and other forms of cyber threats. Cyber-attacks can undermine the integrity and functionality of AI systems, making protection against these threats crucial.
Moreover, developing countries should be wary of the use of AI for military attacks. AI technology can be used to develop autonomous weapons or systems capable of conducting military operations without human intervention. Therefore, strict regulations and oversight must be implemented to prevent the use of AI in actions that could threaten national or regional security.
Resilience against ideology introduced through AI also needs attention. AI and the data used in these systems can become channels for spreading ideologies or propaganda that may not align with local values and cultures. Developing countries need to develop mechanisms to filter and monitor content processed by AI systems, ensuring no external influences disrupt the social and cultural order.
By adopting this comprehensive approach, developing countries can ensure that AI systems are not only secure and resilient against cyber-attacks but are also used responsibly and ethically. Protecting against data manipulation and misuse of AI technology for military or ideological purposes is a crucial step in maintaining national stability and security.
Enhancing International Cooperation
Developing countries must actively engage in international cooperation to share knowledge and resources in AI development. Such cooperation helps developing countries access the latest technology and ensures they can compete globally. It is also crucial for developing countries to voice their interests in AI development, not merely as passive consumers but as active stakeholders.
By participating in international forums and cross-country collaborations, developing countries can ensure their voices are heard and their interests considered in the formulation of global AI policies and standards. This includes advocating for technology transfer, equitable access to resources, and local capacity building, thus reducing dependence on imported technology and avoiding new forms of exploitation.
International cooperation also provides opportunities for developing countries to build networks with global AI industry leaders, academics, and other governments. Through such collaborations, they can gain access to the latest research, cutting-edge technology, and best practices, accelerating the adoption of AI technology domestically and strengthening their position in the global digital economy. Moreover, this cooperation enables developing countries to negotiate fairer terms in the adoption of AI technology, ensuring greater control over the development and use of the technology, and supporting sustainable development and digital sovereignty.
Conclusion
By learning from the approaches of benchmark countries, developing countries can adopt holistic and inclusive measures to ensure the suitability of AI technology security. Focusing on capacity building, leveraging AI for socio-economic development, fostering public-private partnerships, strengthening governance and ethics, utilizing local resources, ensuring AI security and resilience, and enhancing international cooperation are key to implementing AI technology that is safe, fair, and beneficial for the wider society.
