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📅 05 October 2023 | 🕟16:00-17:00 CEST | 💻Online |

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In the second Digital Dialogue on Artificial Intelligence, the panelists will discuss what International Civil Society Organizations (CSOs) should be doing to preserve their mandates in the face of the ever-increasing use of AI.

When new generative AI products were put on the market last year, it was duly noted that the workforce for this achievement were mainly underpaid gig workers in Kenya and other countries of the global South. But is that all what can be said about AI and poverty?

The consulting industry has no doubts:

« In the new study ‘Notes from the AI frontier: Applying AI for social good’, the McKinsey Global Institute (MGI) has examined how AI can be used in the fight against hunger and for better health, as well as in issues such as education, security and justice, equality and integration. Based on around 160 societal and social use cases, the study concludes that AI capabilities such as machine vision or natural language processing (NLP) can bring about far-reaching improvements in all 17 UN Sustainable Development Goals. »

 

In view of so much enthusiasm, we asked ChatGPT what are the risks that AI aggravates poverty in our societies? ChatGPT provided an extensive answer:

« AI has the potential to exacerbate poverty in several ways:
1. Job Displacement: Automation and AI technologies can replace certain jobs, particularly those that involve repetitive tasks. This can lead to unemployment and underemployment, especially for low-skilled workers.

2. Wage Inequality: While AI may create high-paying jobs in the tech industry, it can widen the wage gap between skilled workers in AI-related fields and those in lower-skilled occupations, further contributing to income inequality.

3. Access Disparities: Access to AI-related education and resources can be unevenly distributed, leaving some communities behind and exacerbating disparities in economic opportunities.

4. Bias and Discrimination: If AI systems are trained on biased data, they can perpetuate existing societal biases, leading to unfair treatment in areas like hiring, lending, and criminal justice, which can disproportionately affect marginalized groups.

5. Concentration of Wealth: Large tech companies that develop and control AI technologies may accumulate significant wealth and power, potentially concentrating economic resources in the hands of a few.

To mitigate these risks, policymakers and stakeholders must work to ensure equitable access to AI education and opportunities, regulate AI applications to prevent discrimination, and develop social safety nets to support workers affected by AI-driven job changes. »

 

With opportunities and challenges clearly outlined by others, the question arises what is left for CSOs? Are they just bystanders, warners, and focusing on advocacy or is there room for creativity, for using AI to promote social justice and to combat actively poverty and marginalisation?