Compelling Use Cases of AI That Government Should Nurture

We can consider Artificial Intelligence as cognitive intelligence as it can mimic human intelligence and perform tasks without human interventions. And the task enablement takes place with cues from machine learning that changes and improves its actions by learning patterns.

AI has rapidly shifted its base into our day-to-day lives by surprise, but the public sector is yet to deploy its cognitive brilliance. But, there are many ways the government can make use of AI solutions to the fullest, and reap real potentials out of this component.

We will discover the most comprehensive use cases of AI in the public sector that are truly relevant.

Government acts can impact our living. Today, the government has enormous data. And the public sector can tap into AI potentials and bring about a transformative change the following way.

1. Crowd Analytics

Crowd analytics is by nature intuitive and intelligent tool to interpret data collected from the free and natural movement of the crowd in any place to determine their behavior. As private sectors such as retailers and businesses use crowd analytics to make insightful decisions about customer behavior and bring in techniques to increase efficiency and promote better customer service.

However, the government can harness crowd analytics to improve its people’s needs. But how?

  • Government can improve public services by mapping crowd data in line with the growing demand of citizens’ needs. As they build their platform, it enables them to connect with citizens at a deeper level via an easy-to-use interface.
  • By tapping into the power of data from citizens, the government can be able to reduce risks, boost the performance of their workforces, and optimize scarce resources to help its people.
  • The government can also make use of traffic information and develop a real-time traffic ecosystem to avoid congestion, accidents, control speed, and other street hazards. It is all possible for sensors, bar codes, and cameras that keep a watch on our every step.
  •  As is the case with auto insurance bodies, it can monitor their customer’s driving behavior using GPS, and use the data in combination with behavioral economics to throw insights into accurate pricing. 

2. Dialect Classification

Dialect classification is part of general language identification to differentiate between accents of the specific language spoken. This AI strategy that infuses machine learning is key to deriving the correct language specification due to the complexity of the linguistic similarities between dialects.

The AI system uses acoustic and natural language processing to build a dialect classification system. Then neural network systems extract dialect embeddings from the acoustic signals and present accurate results about the language being spoken by finding similarities and dissimilarities between languages and dialect or accent. The outcomes can be later utilized for automatic speech recognition.

With the new classification of voice data, it can open up new dimensions for government in various ways.

Using dialect classification data, the government can find useful information from a user’s purchase history; know their demographic and geographic data. This can be handy in identifying the users’ age, gender and even ethnicity, race of group, although it is regarded as discriminatory. But, leveraging this type of data helps policing units to determine a user’s connection with a terrorist group. On the other hand, dialect classification can work in sync with surveillance capabilities, and improve oversight for the purpose of immigration control.  

3. Disaster And Emergency Management

AI-powered systems can already predict several variables present in stock markets, customer service, trading and even health care. A similar way, AI can be of great use in the public sector in reducing the threats from disaster and emergency incidents.

If the government can employ AI capabilities the right way, it is easier to harness data and predict varying degrees of norms related to natural disasters. This prediction can help gauge accurate scenarios about the disaster or critical events so that we can take appropriate measures to save thousands of lives and restrict further property damage.

How does it work?

AI-integrated emergency incident detection tools can predict the occurrence of natural disasters ahead of time, allowing disaster recovery personnel enough time to prepare strategies and deal with the incidents with improved rescue operations.

Upon realization of the occurrence of the natural disaster of any type, it sends notifications to the system administration and helps take adequate measurements to improve operations that could make a difference between life and death.

AI can be programmed with seismic data so as to enable the system to detect magnitude and patterns of the earthquake. It also identifies the location of the earthquake and aftershocks.

To predict the likelihood of floods, AI can be trained with rainfall history and flood simulations to predict the occurrence of future rainfall and flood.

So, using AI for disaster and emergency management, the government can make the right use of resources for preventive maintenance and repairs.

4. Face Recognition

Facial recognition is a system integrated with AI to foster greater efficiency at law enforcement agencies and provides a means to ensure safety for its citizens. The tool is there to identify and verify people’s identity in line with face detection and face match. Other than establishing the identification of a person or entity, it is used to detect emotion as well. From this perspective, it means a lot for law enforcement.

This facial recognition case study is an apt resource to improve your understanding of the technology and its application.

Use by law enforcement

  • The foremost use of facial recognition is to ensure safety and security for people by fighting crime and terrorisms. So, it can be at its best in detecting and preventing crimes.
  • The technology is used to issue identity documents in merge with other technologies such as biometrics.
  • A face match is done using this technology to compare the image on the passport with the real holder’s face.
  • It is also used at police checks to ensure crime-free zones. 

Conclusion

According to IDC, AI applications are estimated to grow at a CAGR of 54% across government organizations. It is also expected to leave its mark in the education sector with its growth prospects during 2017 and 2021. It is high time you make use of this technology in the right proportion and achieve its benefits. For any AI-based technology and applications, you can seek assistance from SynergyLabs- an expert in AI analysis and application implementation. Feel free to talk to us about your queries.