Interesting Use Cases of Artificial Intelligence In Governance

Artificial intelligence (AI) has found extensive applications across various fields. Among such fields, one domain where there is a lot of potential for AI is governance.

Public sector entities can function several times better if they rely on AI-based solutions to execute certain kinds of tasks.

However, when compared to the private sector, the use of AI in the public sector is limited. 

Governments around the world have started investing in AI to achieve various goals.

Yet, applications of AI in this field are still in their nascent stage.

Even in this stage, the usage of AI has transformed governmental operations in some countries. 

Need for AI in Governance

The need for AI-based solutions in governance can be classified into some key categories which are described below.

1. To automate repetitive tasks

Several sectors of the government have everyday mundane tasks that take up a significant portion of the employees’ time.

If such tasks could be automated using smart AI algorithms, employees will have extra time to focus on more important tasks.

2. Where the data is too large to handle

Some governmental departments are such that humongous data is generated frequently.

In such cases, it is not humanly possible to handle such a large amount of data.

Implementing AI to process such data can drastically cut down resources and manpower which would otherwise be required. 

3. To make predictions

In some sectors such as crime and disaster management, appropriate data collection techniques followed by the implementation of AI algorithms can help predict the occurrence of untoward incidents ahead of time.

Thus, the government can take measures to prevent such incidents by coming up with effective risk mitigation plans.

4. To converse with the citizens

Governments are already exploring options where AI-based bots can converse with citizens and help in grievance redressal.

Of course, the applications are far from the resemblance to actual human conversations. But the bots can help in sectors where there is a shortage of employees. 

Artificial Intelligence in Governance Use Cases

Public sector entities around the world have already begun implementing AI-based solutions to simplify tasks, enhance productivity, and have a better shot at good governance.

Given below are some working examples of how artificial intelligence has helped government operations. 

1. Fixing China’s air pollution

China is known for having notoriously low levels of air quality. This posed a risk when it hosted the Beijing Olympics in 2008.

To ensure the safety of the athletes and the visitors in the Olympic village, the Chinese government enforced strict traffic restrictions and ordered the factories to shut down. 

While the measures did help in creating a safer environment, they were too radical.

As a result, the economy got affected.

Later in 2014, the Chinese government partnered with the tech-giant IBM to build an AI-based solution for the country’s pollution problem. 

Sensors in different regions collect data regarding CO2 and other emissions.

This data is used to identify patterns and forecast the expected pollution levels for the next 72 hours.

Thus, government authorities can warn citizens in advance.

Also, they can decide which regions have to shut down their factories and other major contributors rather than enforce a blanket restriction across a whole province.

2. Minimizing tax fraud

Irrespective of policy enforcement, governments around the world have to deal with tax defaulters and tax evasion.

Intentionally or otherwise, a small percentage of citizens tend to miss the due date. 

The Office of State Revenue in Queensland, Australia turned to AI to minimize the occurrence of irregular tax payments.

Through data-driven insights, the department can now predict the taxpayers who are at risk of default.

The model works with 71% accuracy. With the predicted data, the department can offer assistance programs for potential defaulters. 

Overall, the implementation of AI, data analytics, and machine learning could help the revenue department in decreasing the state debt which will, in turn, contribute to a more stable income. 

3. Better response to natural disasters

When AI algorithms are applied to vast amounts of historic data, the resulting model can predict the extent of damage that one can expect from a particular region should a disaster strike. 

Japan, which is known to have survived multiple disasters with large-scale destruction, is today home to several startups that use past data to forecast the impact of a disaster on various prefectures in the country. 

Disaster-prone countries from around the world can take a leaf out of Japan’s book and implement AI-based models to predict disaster impact.

These predictions can immensely help in designing/redesigning cities, planning disaster mitigation schemes, and enhance the overall disaster preparedness of the country’s population. 

4. ‘Coptivity’ – The Sheriff’s new best friend

Governments have begun leveraging modern technology for better law enforcement.

Police generally have to make calls to the dispatcher to check on a license plate or a potential offender. This process takes away much of the sheriff’s time. 

To make things faster, the San Diego County Sheriff in the USA have implemented Coptivity – an AI-enabled voice assistant.

It is a tool that gives out valuable background information that a cop needs within minutes. No more calls and waiting times. 

When the cop types a license plate number or uploads a photo, the application runs it through the database looking for matches.

If a match is found, it returns all the related data. This helps the cops to be better equipped even before they step out of their cruisers. 

Scope for AI-based solutions in Governance

In a large developing country such as India, government agencies can use AI to track data on public infrastructure.

This would help in timely maintenance. There have been several instances of lapses in infrastructure leading to deaths and grave injuries that could have been avoided. 

For instance, consider the railways. Indian railways consist of thousands of routes that see thousands of trains ferrying passengers from point to point.

Thus, it is impossible to manage the data regarding the maintenance and expiry of coaches, tracks, and other components.

At the same time, not paying attention to these can lead to derailments and other serious accidents.

If the government is equipped with AI-based solutions to keep a record of the last date of maintenance for rail components, accidents can be avoided. 

Challenges in implementing AI in Governance

Although AI comes with several promising possibilities, there are some roadblocks for governments that want to incorporate AI in their operations. 

• For instance, in developing countries or those with weak economies, it may not be financially viable to allocate a budget for R&D in AI.
• Next, in countries that are perhaps interested in building AI-based solutions, there are privacy concerns. If the solution involves the government collecting the citizens’ data, people may see it as a threat to their privacy. 

Summary

Overall, we can say that there is a lot of ongoing research and future scope for AI-based applications in governance.

With time, more governments would invest in research and development of artificially intelligent applications for the betterment of their citizens.