Public sector data-driven decision-making enabled by AI

The digital economy is an exciting topic, and there is no doubt about it.

Even more so is the glut of technological advancements that we are introduced to daily, all of them promising a vastly different world than the one we live in today.

Artificial Intelligence (AI) and Large Language Models (LLMs) are the champions of the technology field today. A few days ago, Nvidia (developer of the Graphical Processing Units, GPUs, on which AI applications are built) surpassed Apple as the second most valuable company in the world, primarily driven by its central role in the AI space.

It is abundantly clear that AI is not just the ‘next big thing’; it’s a brand-new foundation upon which today’s digital economies are being built. However, all the Foundational Blocks of the digital economy that are spoken of generally (and in the book authored by Appiah-Adu and Asare (2022) titled, “The Enabling Architecture for a Digital Economy”) are of little use to ordinary citizens who primarily experience a ‘digital economy’ via the applications made available to them.

This also holds true for government officials as well, and perhaps even more so, as their work directly touches millions of lives. If, as we say, ‘charity begins at home’, it is even more important that governments pushing digital applications in a digital economy live in that digital space themselves.

Explanations

We provide some simple explanations for terms we will use extensively in this piece: Artificial Intelligence (AI), Generative AI (or GenAI) and Large Language Models (LLMs).

▪ Artificial intelligence (AI) is the ability of a constructed machine, such as a computer, to simulate or duplicate human cognitive tasks. A machine with AI can make calculations, analyse data to create predictions, identify various types of signs and symbols, converse with humans and help execute tasks without manual input (per Cloudflare).

▪ Large Language Models (LLMs) are a type of AI that are designed to understand and generate human language. These models are trained on vast amounts of text data and can then generate human-like text and responses.

▪ Generative AI, or GenAI, refers to AI systems that have the ability to create new content, whether it be text, images or other forms of media, based on the data they have been trained on. Most people are interfacing with AI via GenAI programmes such as ChatGPT or Gemini.

It is worth noting that governments worldwide are already starting to harness the power of AI and LLMs to improve governance and better serve their citizens.
From predictive analytics to personalised services, AI is transforming the way governments operate.

Innovative

For example, Seoul Talk in South Korea exemplifies an innovative initiative utilising AI consultants to manage citizen inquiries and complaints about city functions and services. This platform addresses a fundamental responsibility of government: informing citizens on how to access public services.

The Automatic Social Energy Tariff Initiative in Portugal utilises secure, integrated data from government agencies and energy companies to identify eligible citizens for social energy tariffs and automatically enrol them in the programme.

This system streamlines transactional interactions between citizens and the government, such as tax collection and benefit distribution, which are typically managed by multiple agencies at both local and national levels.

Moreover, in India, the integration of voice-payment technology into the instant payments system is set to enhance financial inclusion, especially by providing support in multiple languages.

Leverage

Similarly, African governments are being served with an excellent opportunity to leverage AI tools to improve service delivery for their citizens in several key areas. Broadly, here are the top three main benefits to consider:

• A key benefit of AI in governance is its ability to improve decision-making. By analysing vast amounts of data, AI systems can provide valuable insights that human decision-makers might overlook.

This can lead to more efficient policies, better resource allocation and ultimately improved citizen outcomes. With AI, policymakers can design and implement interventions in complex systems, conduct real-time policy evaluations and gain detailed insights into public sentiments.

• Furthermore, AI can help governments provide more personalised services to their citizens. By analysing individual data and preferences, AI systems can tailor services to meet the specific needs of each citizen.

This can lead to greater satisfaction among citizens and increased trust in government institutions.

• Furthermore, AI can enable governments to deliver more tailored services to various communities. By analysing segmented data and group preferences, AI systems can customise services to address the specific needs of different communities. This approach can lead to greater overall satisfaction and increased trust in government institutions.

• Moreover, AI systems can play a pivotal role in eliminating backlogs and reducing waiting periods within governmental operations.
This technological advancement promises enhanced efficiency, diminished bureaucratic delays, elevated service quality to bolster citizen satisfaction, cost savings and heightened public trust in government institutions. These broad benefits outlined above can also be applied to create valuable solutions in specific sectors. Let us examine a few:

• Healthcare: Generative AI can be used to analyse and predict disease outbreaks, such as COVID-19, Malaria or Ebola.
By using AI to process and interpret data from various sources, including health centres and hospitals, government officials can make data-driven decisions to allocate resources, implement preventive measures and improve public health policies.

Imagine a public official being able to ask a GenAI tool fed with public health data ‘What are the communities in Ghana with the highest maternal mortality rate per district hospital data?’ to plan government subventions targeting specific areas instead of a more expensive national programme. The speed with which tooled LLMs could make such information accessible would in itself be a game changer.

• Agriculture: AI can significantly improve agricultural productivity and food security in the region. Generative AI can help farmers and government officials predict weather patterns, optimise crop yields and detect pests or diseases early.

By analysing satellite imagery, weather data and soil samples, AI can provide actionable insights for policymakers. For instance, AI tools fed with local data from the Ministry of Agriculture can be used to optimise extension service interventions for local farmers, as well as priority investment areas for the government, looking to protect and grow crop yields nationally.

• Infrastructure and Urban Planning: AI can help governments optimise infrastructure development and urban planning. Generative AI can analyse data on population growth, traffic patterns and resource usage to help officials make decisions about where to build new roads, housing or public facilities.

The writers are a senior policy advisor, the Office of the Vice President, a digital transformation and innovation policy advisor, and the CEO of Heritors Labs Limited, respectively.