Responsible AI in public service delivery: a reflection from the OECD-AU Artificial Intelligence dialogue in Cairo, Egypt

KCL AI-generated Image

“I was an invited panelist at the OECD-African Union (AU) Artificial Intelligence dialogue in Cairo. The event was held in Cairo from 19 to 21 November 2024. The event brought together participants from over 30 countries. They collaborated on concrete action steps for implementing the Continental AI Strategy.”

Teddy Nalubega is the Head of the AI constancy at KCL . She had the privilege of attending and participating in a panel discussion at the Artificial Intelligence dialogue in Cairo. The discussion was about how governments worldwide can responsibly harness artificial intelligence to enhance service delivery and improve operations.

The panelist collectively agreed that responsible AI should serve as an enabler of improved service delivery. And this can be done by balancing innovation with responsibility. Unlike private-sector AI, public sector applications directly impact citizen rights, equity, and democratic trust.

For instance, an AI-driven social benefits system can unintentionally exclude marginalized groups due to biased training data. Additionally, a generative AI chatbot provides incorrect legal and health advice to vulnerable citizens.

Teddy in red on the panel

In their discussion, they explored a range of perspectives during the event. These perspectives ranged from local to international. We highlighted AI-enabled public services tailored to community needs. They stressed the importance of building capacity among the region’s youth to use, understand, and develop community-specific technological solutions. Citizens must trust the government’s ability to manage AI. This trust is essential because governments handle sensitive citizen data. Sometimes, they run without adequate public scrutiny.

Without proper safeguards, AI deployment in public service delivery can erode public trust and lead to costly failures. Funding opportunities were shared. Programs like the Partnership for Global Inclusivity on AI (PGIAI) offer resources for AI efforts in compute. They also help in capacity building and support local datasets.

Responsible AI in public service delivery requires proper governance, technical safeguards, and citizen-centric delivery. Governance by Design includes establishing multi-stakeholder AI review boards. It involves conducting mandatory impact assessments for high-risk applications. It also requires setting clear public disclosure standards.

Technical Safeguards focus on mitigating risks through bias testing, human-in-the-loop control, and continuous performance monitoring. Citizen-centric delivery prioritizes transparency and inclusivity. It does this by clearly communicating AI use. It also provides redress mechanisms and involves communities in the design processes.

Africa is well-positioned to develop fair AI systems by learning from global precedents while addressing local needs. Unlike legacy-bound economies, African governments can embed responsible AI principles from the outset. This approach allows them to avoid the costly retrofitting now underway in Europe and America.

The success of these efforts depends on African countries investing in local capabilities and capacity. They need to foster cross-border collaboration. Additionally, centering citizen voices in AI design is crucial. This approach guarantees that emerging technologies serve the public good rather than perpetuate existing disparities.

When consulted by public sector leaders, our position is: “The goal isn’t just to deploy AI faster. It is crucial to deploy it right. We need mechanisms that guarantee fairness, accountability, and long-term public confidence.”

By adopting this approach, governments can transform service delivery while reinforcing the social contract in an increasingly digital age.

In our earlier article about Artificial Intelligence for Improved Efficiency and Effectiveness in Africa, we stressed the importance of investing in technical capacity. We focused on building this capacity. We also highlighted the need for managerial capacity. This means training civil servants in data literacy and AI concepts. They must also learn ethical considerations. This ensures that they can manage and evaluate AI solutions critically.

What do you think? Do you think our governments and organizations are ready for these developments?


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