Authors:Tuhu Nugraha and Annanias Shinta D*
In the context of developing countries, the development of ethical and responsible artificial intelligence (AI) is a crucial need that must be seriously addressed by policymakers. The main challenges include limited infrastructure, wide social diversity, and significant economic disparities. Inadequate infrastructure often hampers the efficient and secure collection and processing of data, which is essential for the training and implementation of AI systems. This lack of infrastructure can increase the risk of errors and biases in AI, potentially negatively impacting social justice and inclusivity.
The broad social diversity necessitates sensitive and adaptive strategies in AI development, where policies must be designed to ensure AI systems respect and understand the cultural and social uniqueness of each group. This approach is vital to prevent unintentional discrimination that may arise from biases in AI algorithms. Additionally, economic differences between groups must also be a primary consideration. According to data from the World Inequality Database for the period 1995-2021, the correlation between the Gini index for income and wealth inequality is positive, with a coefficient of 0.76 in a global sample, 0.86 in a developing country sample, and 0.37 in a developed country sample. This indicates that large economic disparities can be exacerbated by the use of AI that is not adapted to local conditions and economies.
AI must be adapted to consider local contexts and diverse economic conditions to avoid deepening economic disparities. This means that the development and implementation of AI in developing countries must be done in a way that is not only technologically advanced but also inclusive, ensuring that all societal groups have equal access to new resources and technologies. Policymakers need to focus on creating a framework that supports this, ensuring that AI promotes sustainable social and economic progress for all of society.
The implementation of responsible and ethical AI in these countries should consider several important aspects: regulatory frameworks, capacity building, public awareness and engagement, and the development of AI that is contextual to the local environment. Here are some analyses and implementation strategies that can be adopted:
Regulatory Framework
A strong regulatory framework is a crucial foundation for the ethical and responsible implementation of AI. In India, initiatives like the “National Strategy for Artificial Intelligence” have underscored the importance of a legal framework that not only supports innovation but also protects the rights of citizens. To address privacy issues, the establishment of a data protection framework with legal support, as proposed by the Justice Srikrishna Committee, is crucial. Data protection and privacy principles such as informed consent, data controller accountability, and the implementation of impactful penalties should provide a strong privacy protection regime in the country.
Moreover, it is also essential to establish sector-specific regulatory frameworks that keep pace with rapid technological changes. Examples from Japan and Germany, which have developed new frameworks applicable to specific AI issues like next-generation robot regulation and autonomous vehicles, demonstrate the importance of a tailored approach. Alignment with international standards, as done by the European Union with GDPR, is also necessary to design systems that are less invasive of privacy. India needs to continually update its privacy protection regime to reflect an understanding of new risks and their impacts.
In terms of AI security, the National Strategy for Artificial Intelligence in India discusses the debate on accountability, which often focuses on determining responsibility and should shift to an objective identification of failing components and ways to prevent them in the future. This is similar to how the aviation industry became safe, where each accident is investigated in detail, and future steps are determined. A framework might involve negligence tests for damages caused by AI software, with safe harbor provisions to reduce liability as long as appropriate steps have been taken in the design, testing, monitoring, and enhancement of AI products.
Capacity Building
Local capacity building in artificial intelligence (AI) technology is key to maximizing the utilization of this technology in developing countries. Through focused education and training, AI developers and users can understand and implement AI solutions that are appropriate for the local context. For example, in Kenya, the “AI and Data Science Research Group” at the University of Nairobi is an initiative aimed at enhancing the capabilities of local data scientists. This group focuses not only on improving technical skills but also on adapting AI technologies to address specific local challenges, such as natural resource management or unique public health issues in the region.
The development of local capacity is crucial because it enables the AI solutions developed to be more relevant and effective. For instance, in the Kenyan context, AI applications could be used to predict and manage disease outbreaks like malaria, utilizing locally collected climate and health data. This not only enhances the effectiveness of health interventions but also ensures that the solutions generated are practical and can be directly applied in the field.
Moreover, local capacity building helps ensure that the economy can grow and adapt to global technological changes. By having a workforce that is educated and trained in AI, countries like Kenya can more quickly integrate this technological innovation into key industries, from agriculture to banking, thus enhancing productivity and global competitiveness. Initiatives like those at the University of Nairobi pave the way for a new generation of scientists and technologies that will bring about significant social and economic transformation.
Public Awareness and Engagement
Effective public engagement in AI development is crucial to ensure the acceptance and broad utilization of this technology in society. In Brazil, initiatives like “AI for Good Brazil” play a vital role in raising public awareness by involving the broader community in AI policy discussions. This program gathers stakeholders from various sectors to promote the development of responsible and ethical AI. Additionally, many academic institutions in Brazil are actively researching AI and engaging with the public through seminars, workshops, and public outreach programs.
Public involvement in AI policy discussions is important for several reasons. First, it ensures that AI policies reflect the concerns and aspirations of a wide range of stakeholders, not just experts and policymakers. Second, such engagement can build trust and understanding of AI technology, ultimately fostering broader acceptance and adoption.
Overall, Brazil actively recognizes the importance of public engagement in shaping AI policy and encourages a more inclusive and informative approach to AI development in the country. These initiatives not only help identify social and ethical challenges that may arise from the development and deployment of AI but also ensure that the technology has a positive and inclusive impact on all layers of society.
Contextual Local AI Development
Developing AI that is appropriate for the local context is crucial to ensure that the solutions generated are relevant and effective. This includes adapting technology to address local issues such as agriculture, health, and education, as noted in the Indonesian National Strategy for Artificial Intelligence 2020-2045. In Indonesia, for example, the use of AI in pest detection applications helps farmers identify and address agricultural issues more quickly and accurately.
One of the main priorities in implementing AI in developing countries is to avoid massive job displacement. A strategy that can be taken is to integrate AI in a complementary way, not as a substitute for human workers. AI can be used to enhance the efficiency and effectiveness of human work, not replace it. This approach requires policies that support the transition of workers to new roles created by AI technology, as well as investment in education and training for future skills.
The implementation of ethical and responsible AI in developing countries not only supports technological progress but also ensures that such progress is inclusive and sustainable. By adopting these strategies, developing countries can leverage artificial intelligence to accelerate socio-economic development while maintaining harmony in society.
*Annanias Shinta D, Passionate professional with a strong background in research, communication, and business management. Experienced in collaborating with public and private companies, as well as NGOs, to drive positive change and create a better future.
