ICTworks

As governments develop artificial intelligence strategies to manage the integration of AI within the private sector and its impact on social dynamics, a schism is developing between wealthier countries and lower-middle-income countries.

AI Integration and Economic Divides: Analyzing Global AI Strategies presents key insights on how socio-economic factors shape the development and focus of national AI strategies in Germany, the United Arab Emirates (UAE), and the United States as one cohort and India, Bangladesh, and Egypt in another cohort. This reveals two important views on AI:

• Wealthy Countries Emphasize AI Risks: Wealthier nations like USA, Germany, and the UAE tend to focus on the risks of AI integration, with a high frequency of risk-related keywords in their AI strategies, reflecting concerns over data security, privacy, job displacement, and worker safety.
• Lower-Middle-Income Countries Emphasize AI Optimism: In contrast, LMICs, such as India, Egypt, and Bangladesh, are more optimistic, focusing on how AI can accelerate economic growth, improve services, and provide new employment opportunities with efficiency gains, job creation, and innovation.

AI Issues for LMIC Citizens

For residents of lower-middle-income countries, the findings of this report are particularly relevant for three reasons:

Economic Development Potential

AI presents a significant opportunity for economic growth in lower-middle-income countries, where technological advancements can drive productivity and innovation in sectors like agriculture, manufacturing, and services. India, Egypt, and Bangladesh are positioning themselves to harness AI to accelerate their economic development, improve public services, and create new employment opportunities.

Workforce Impact

The optimistic approach towards AI in lower-middle-income countries can lead to a positive transformation of the workforce. By emphasizing skills development, reskilling, and new job creation, these countries can use AI to enhance their labor force capabilities. However, the report also serves as a reminder of the importance of preparing for potential challenges, such as job displacement and data privacy issues, which might become more pronounced as AI integration deepens.

AI Governance and Safety

Lower-middle-income countries do need adaptive governance frameworks that balance innovation with worker safety, as regulatory mechanisms might be less developed. Ensuring that AI adoption does not compromise workers’ rights or safety is fundamental to sustainable development. Learning from the experiences of wealthier countries, which place greater emphasis on the risks associated with AI, can help lower-middle-income countries anticipate and address these challenges more effectively.

4 Actions for Humanitarian Organizations

Humanitarian organizations working in lower-middle-income countries have an important role in ensuring that AI development is inclusive, equitable, and safe for all:

1. Advocate for Inclusive AI Policies:

• Work with governments to ensure that AI policies are inclusive and consider the needs of vulnerable populations, such as low-skilled workers who may be at risk of displacement.
• Encourage the creation of AI strategies that emphasize not only economic opportunities but also protections against risks like data misuse and worker exploitation.

2. Support Skills Development Initiatives:

• Collaborate with educational institutions and private sector actors to provide training and reskilling programs. This can help workers transition into new roles created by AI technologies and mitigate the risks of unemployment due to automation.
• Emphasize digital literacy and AI-related skills, particularly among young people, to prepare them for future job markets driven by technological advancements.

3. Promote Adaptive Governance:

• Humanitarians should advocate for the establishment of adaptive governance frameworks that can evolve as AI technologies develop. This includes policies that protect worker safety, ensure ethical AI usage, and prevent misuse, such as discriminatory practices or privacy violations.
• Support local governments in developing safety standards and protocols for AI deployment in industries where worker well-being could be compromised, such as manufacturing and construction.

4. Facilitate Cross-Sector Collaboration:

• Foster collaborations between government, civil society, academia, and the private sector to create comprehensive AI strategies. Such partnerships can help leverage AI for broader social good, such as improving healthcare, education, and public safety.
• Humanitarians can play a key role in bringing different stakeholders together to create AI solutions that address specific local challenges, such as using AI for climate resilience or improving agricultural productivity.