Artificial Intelligence (AI) holds enormous promise for global development, offering solutions to some of the most pressing challenges in healthcare, education, agriculture, and financial inclusion. However, alongside its potential benefits, AI also introduces significant risks that could exacerbate inequalities, infringe on human rights, and disrupt societies, particularly in developing countries where safeguards and regulatory frameworks may not yet be fully established. As AI adoption accelerates, it is critical to understand and address these risks to ensure that the technology serves as a force for good rather than deepening existing problems.

This article explores the key risks associated with AI in global development, from data privacy and bias to job displacement and ethical concerns, and discusses how these risks can be mitigated through responsible development practices.

1. Bias and Inequality in AI Systems

One of the most prominent risks of AI in global development is the potential for bias in AI algorithms, which can lead to discriminatory outcomes. AI systems are trained on large datasets, and if these datasets are not representative of the populations they serve, AI can reinforce existing social inequalities.

• Data Bias: AI models rely on historical data, and if that data reflects societal biases related to gender, race, class, or geography, AI systems can perpetuate those biases. For example, an AI system used to allocate healthcare resources or approve loans may prioritize wealthier or urban populations because the data used to train the model is skewed toward those groups. This can result in further marginalization of already underserved communities in rural or low-income areas.
• Exacerbation of Inequality: Developing countries often have limited access to high-quality data, and AI systems designed in and for developed countries may not be suited to local contexts. This creates the risk that AI technologies could worsen inequalities, as wealthy nations and individuals with better access to technology benefit more from AI, while poorer communities are left behind. The “AI divide” could mirror the existing digital divide, where unequal access to technology further entrenches economic and social disparities.

2. Data Privacy and Security Concerns

AI systems require vast amounts of data to function effectively, raising concerns about privacy and data security, especially in regions where legal protections are weak or nonexistent. In developing countries, where many people may not fully understand how their data is being used, there is a heightened risk of exploitation.

• Data Exploitation: Many developing nations lack comprehensive data protection regulations, making it easier for companies or governments to collect and misuse personal data. Without stringent privacy laws, sensitive information—such as health records, financial transactions, or even personal conversations—could be harvested, sold, or misused, often without the individual’s consent or knowledge. This could lead to serious breaches of privacy, undermining trust in AI systems and technology providers.
• Cybersecurity Vulnerabilities: As AI becomes more integrated into critical infrastructure, such as energy grids, transportation systems, or healthcare, it also becomes a target for cyberattacks. Developing countries may not have the cybersecurity measures in place to protect AI systems from hackers, raising the risk of malicious use of AI, data theft, or large-scale system failures that could destabilize economies and disrupt essential services.

3. Job Displacement and Economic Disruption

AI-driven automation presents significant risks to employment in both developing and developed countries, but the impact could be particularly severe in regions with large labor forces engaged in low-skill or manual work. The automation of jobs in sectors such as agriculture, manufacturing, and customer service could lead to widespread job displacement, exacerbating poverty and social unrest.

• Impact on Low-Skilled Workers: Many jobs in developing countries are manual or repetitive, making them more susceptible to automation. AI-driven machines and robots could replace workers in factories, farms, and call centers, displacing millions of people. While AI has the potential to create new jobs in tech-related fields, the transition may be difficult for workers without access to education or training in these new skills. This could lead to higher unemployment rates and growing economic inequality.
• Informal Economy Vulnerability: Many people in developing countries work in the informal economy, where jobs are often precarious and lack legal protections. AI could further disrupt these sectors, particularly in agriculture, where automation could reduce demand for manual labor. Governments will need to create policies and programs to support workers who are affected by AI-driven economic disruption, including reskilling initiatives and social safety nets.

4. Ethical and Human Rights Concerns

The use of AI in global development raises ethical concerns, particularly when AI is deployed in ways that infringe on human rights, such as mass surveillance, social control, or the misuse of AI in warfare. Developing countries, where governance structures may be weak, are particularly vulnerable to the misuse of AI technologies.

• AI in Surveillance and Social Control: AI-powered surveillance systems, including facial recognition and biometric tracking, are increasingly being used by governments around the world to monitor citizens. While such technologies can be beneficial for maintaining public safety, they also raise significant concerns about privacy, freedom of expression, and the potential for authoritarian control. In countries with weak rule of law or human rights protections, AI surveillance could be used to suppress dissent, target political opponents, or track vulnerable populations such as refugees or ethnic minorities.
• Autonomous Weapons and Conflict: AI is being incorporated into military systems, including autonomous drones and weapons. While these technologies can provide strategic advantages, their use raises serious ethical concerns about accountability, particularly in conflict zones where the distinction between combatants and civilians is often unclear. In regions prone to instability, the proliferation of AI-enabled weapons could escalate violence and make it harder to achieve peaceful resolutions to conflicts.

5. Lack of Regulatory Frameworks

Many developing countries lack the regulatory frameworks needed to manage the deployment of AI safely and ethically. This regulatory gap makes it difficult to address the risks associated with AI, such as data privacy violations, bias, and job displacement. Moreover, without clear regulations, companies and governments may adopt AI technologies without fully considering the long-term social and economic consequences.

• Weak Legal Protections: In regions where legal systems are underdeveloped or where enforcement is lax, AI technologies could be deployed without sufficient oversight. This could lead to abuses, such as the use of AI for mass surveillance or discriminatory decision-making in areas like policing, hiring, and lending. Governments in developing countries will need to work with international organizations, NGOs, and tech companies to create and enforce robust AI governance frameworks that prioritize human rights and fairness.
• International Standards and Cooperation: AI development is a global effort, but developing countries may lack the resources to participate in international conversations about AI governance. Without representation in global standard-setting bodies, these countries could find themselves on the receiving end of AI technologies designed elsewhere, with little input on how these systems are used or regulated. Ensuring that developing nations have a voice in shaping global AI policies is essential to creating a more equitable and just AI future.

6. Environmental Impact

AI’s environmental impact is often overlooked in discussions about its risks, but it is particularly relevant for developing countries that are already vulnerable to the effects of climate change. AI systems require massive amounts of computational power and energy, particularly for tasks like training large machine learning models. This can contribute to increased carbon emissions and environmental degradation.

• Energy Consumption: The computational power required to develop and operate AI systems is energy-intensive, and many developing countries still rely on non-renewable energy sources such as coal and oil. As AI adoption grows, so too could the environmental footprint of these technologies, potentially exacerbating environmental problems in countries already facing resource constraints and environmental challenges.
• E-Waste: AI systems also contribute to the growing problem of electronic waste (e-waste), particularly as more hardware, such as sensors, drones, and data centers, are deployed in development projects. Many developing countries lack the infrastructure to manage e-waste, leading to harmful environmental and public health outcomes.

Conclusion: Navigating the Risks of AI in Global Development

AI has the potential to be a powerful force for good in global development, but its deployment must be carefully managed to avoid exacerbating inequalities, infringing on human rights, and causing social or economic disruption. Governments, international organizations, and the private sector must work together to ensure that AI technologies are developed and deployed in ways that prioritize fairness, transparency, and inclusivity.

By addressing the risks associated with AI—such as bias, job displacement, privacy violations, and environmental impact—while also promoting ethical standards and regulatory frameworks, we can harness AI’s transformative potential for the benefit of all. Ultimately, the future of AI in global development depends on striking a balance between innovation and responsibility, ensuring that AI serves as a tool for equitable progress rather than deepening divides.