Machine learning (ML) is a powerful tool that can be used to curb corruption in government by identifying and preventing fraudulent activities. The technology can analyse large amounts of data in real-time, which can be used to detect patterns of corruption and take action before it becomes a major problem.
Corruption in government is not new and is not unique to any nation in particular. However, there are differences in how corruption cases are handled by government institutions across the world and this disparity is often the difference between how a nation develops and how another continues to struggle with the basics. Government officials in the West have sometimes been found guilty of misappropriating government funds and are usually prosecuted and sent to jail for a long time, an example would be the former Governor of the State of Illinois in the United States. Rod Blogojevich was found guilty of crimes including wire fraud, attempted extortion, and conspiracy to solicit bribes and as a result spent nearly eight years in prison. He was alleged to have pocketed about $1.6m in cash bribes and lying to the FBI on several cases. Illinois budgets about $46b annually which is more than the budget of many African nations whose Governors and leaders at all levels pocket more than $50m in bribes in some cases. Governors in Nigeria (past and present) have been accused of misappropriating more than $100m in their eight-year tenure and often go free especially if they belong to the ruling party and the resultant effect is the snail-speed pace of development across Nigeria. A former Economic and Financial Crimes Commission Chairman Nuhu Ribadu (who is now a member of the ruling APC) was once credited with the statement that over $400b has been stolen from Nigeria since independence inn1960 by Nigerians majorly, many of whom are still alive today with no consequence for their actions.
But the beauty of technology is that it is versatile and universal in nature in that it can be applied anywhere under the same conditions of success it recorded in the past. One of such technologies is Machine Learning which can be used by governments the world over to stem corruption so monies can be used for what they were budget for.
One way that ML can be used to curb corruption is through the use of predictive analytics. Predictive analytics can be used to identify potential fraudulent activities before they occur, such as the use of shell companies or the creation of fake invoices. By identifying these activities early, government officials can take action to prevent them from becoming a major problem.
Another way that ML can be used to curb corruption is through the use of natural language processing (NLP). NLP can be used to analyse large amounts of text data, such as emails and social media posts, to identify patterns of corruption. For example, if a government official is found to have sent a large number of emails containing suspicious terms or phrases, such as “kickback” or “Bribery”, this could be a sign of corruption.
In addition to identifying patterns of corruption, Machine Learning can also be used to prevent it. For example, ML can be used to create and monitor compliance systems, which can help ensure that government officials are adhering to laws and regulations. These systems can also be used to detect and prevent fraud, such as the creation of fake invoices or the use of shell companies.
Furthermore, Machine Learning can also be used to create transparency in government transactions by monitoring government procurement. This could help in identifying any undue advantage taken by any supplier or contractor, thereby preventing any corrupt practice.
Overall, machine learning is a powerful tool that can be used to curb corruption in government by identifying and preventing fraudulent activities. By using predictive analytics, natural language processing, and compliance systems, government officials can take action to prevent corruption before it becomes a major problem. Additionally, creating transparency in government transactions can also help in preventing corruption by monitoring government procurement process.
While Machine Learning may be a great tool to combat the scourge of corruption, it is also a very technical field that requires some level of expertise. The Nigerian government for example has scholarship programs where students are sent to developed nations to learn these technologies with the promise of coming back home to deploy them here. This is quite noble but enforcement has been weak, we have quite a number of PTDF scholarship beneficiaries staying back after being sponsored using public funds with no permission of the scholarship authority.
It is quite important to develop the right skills in this area applying it to every tier of government would be beneficial in the long term. We can then begin to hold people accountable while also predicting actions of officials in advance. If we can get the right prediction models, we can redeploy people around sensitive areas of government.
