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 policymakers must seriously address. The main challenges include limited infrastructure, high social diversity and significant economic disparities. Inadequate infrastructure often hinders efficient and secure data collection and processing, essential for training and implementing AI systems. This lack of infrastructure can increase the risk of errors and bias in AI, which could negatively impact social justice and inclusiveness.
High social diversity requires sensitive and adaptive strategies in AI development, where policies must be designed to ensure that AI systems respect and understand the cultural and social uniqueness of each group. This approach is essential to prevent unintentional discrimination that may result from bias 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, of 0.86 in a sample of developing countries and 0.37 in a sample of developing countries. sample of developed countries. This indicates that significant economic disparities can be exacerbated by the use of AI that is not adapted to local conditions and economies.
AI must be adapted to account for local contexts and diverse economic conditions to avoid worsening 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 technology. Policymakers must 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 take into account several important aspects: regulatory frameworks, capacity building, public awareness and engagement, as well as the development of context-sensitive AI. the local environment. Here are some analyzes and implementation strategies that can be adopted:
Regulatory framework
A robust regulatory framework provides a crucial foundation for the ethical and responsible implementation of AI. In India, initiatives such as the “National Strategy for Artificial Intelligence” have highlighted the importance of a legal framework that not only supports innovation but also protects the rights of citizens. To address privacy concerns, establishing a data protection framework with legal backing, as proposed by the Justice Srikrishna Committee, is crucial. Data protection and privacy principles, such as informed consent, controller accountability and implementation of strong sanctions, are expected to provide a robust privacy protection regime in the country.
Furthermore, it is also essential to establish sectoral regulatory frameworks that keep pace with rapid technological changes. The examples of Japan and Germany, which have developed new frameworks applicable to specific AI issues such as the regulation of next-generation robots and autonomous vehicles, demonstrate the importance of a tailored approach. Alignment with international standards, as the European Union has done with GDPR, is also necessary to design systems that are less invasive of privacy. India must continually update its privacy regime to reflect an understanding of new risks and their impacts.
In terms of AI safety, the National Strategy for Artificial Intelligence in India addresses the accountability debate, which often focuses on determining who is responsible and should move towards objectively identifying the failing components and means to avoid them in the future. This is similar to how the aviation industry has become safe, where every accident is investigated in detail and future steps are determined. A framework could involve negligence testing for harm caused by AI software, with safe harbor provisions to reduce liability as long as appropriate steps have been taken in design, testing, monitoring and enforcement. improving AI products.
Capacity Building
Building local capacity in artificial intelligence (AI) technology is essential to maximize the use of this technology in developing countries. Through targeted education and training, AI developers and users can understand and implement AI solutions tailored to the local context. For example, in Kenya, the University of Nairobi’s “AI and Data Science Research Group” is an initiative aimed at building the capacity 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 public health issues unique to the region.
Developing local capabilities is crucial because it allows the AI solutions developed to be more relevant and effective. For example, in the Kenyan context, AI applications could be used to predict and manage disease outbreaks like malaria, using locally collected climate and health data. This not only improves the effectiveness of health interventions, but also ensures that the solutions generated are practical and can be directly applied in the field.
Additionally, building local capacity helps ensure that the economy can grow and adapt to global technological changes. By having an educated and AI-trained workforce, countries like Kenya can more quickly integrate this technological innovation into key sectors, from agriculture to banking, improving productivity and competitiveness worldwide. Initiatives like those at the University of Nairobi are paving the way for a new generation of scientists and technologies that will bring about significant social and economic transformations.
Public awareness and engagement
Effective public engagement in the development of AI is crucial to ensure acceptance and wide use of this technology in society. In Brazil, initiatives such as “AI for Good Brazil” play a vital role in raising public awareness by involving the broader community in policy discussions about AI. This program brings together players 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 awareness programs.
Public participation in policy discussions about AI 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, thereby fostering broader acceptance and adoption.
Overall, Brazil actively recognizes the importance of public engagement in AI policymaking and encourages a more inclusive and informative approach to AI development in the country. These initiatives not only help identify the 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 sections of society.
Contextual Local AI Development
Developing AI adapted to 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 outlined 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 resolve agricultural problems faster and more accurately.
One of the main priorities for implementing AI in developing countries is to avoid massive job losses. One strategy that can be adopted is to integrate AI in a complementary manner, not as a replacement for human workers. AI can be used to improve the efficiency and effectiveness of human work, not to replace it. This approach requires policies that support the transition of workers into the new roles created by AI technology, as well as investments in education and training for future skills.
Implementing ethical and responsible AI in developing countries not only supports technological progress, but also ensures that this progress is inclusive and sustainable. By adopting these strategies, developing countries can leverage artificial intelligence to accelerate socio-economic development while maintaining harmony within society.
*Annanias Shinta D, Passionate professional with solid experience in research, communication and business management. Experience working with public and private companies, as well as NGOs, to drive positive change and create a better future.
