When we think about data, we hardly remember the fact that there is an abundance of it all around us. And when that data isn’t identified, sorted, or navigated, it merely acts as clutter. Just think about the mountain of data that exists in the military, local police, national aerospace organizations, and other constituents of the public sector. We see companies from small to large utilizing the latest technologies AI has to offer in their daily operations, services, and products. Why not branch that out to the level of national security and government?
As a matter of fact, AI and computer vision are implemented in government organizations and operations across dozens of countries worldwide. Some applications of AI and computer vision by the government may be familiar to you while others are less prominent. Let’s further examine the role that AI has to play on a national level along with the pros and cons of that implementation for our current times and the near future.
Regarding all of this, we’ll expand further on the following points:
- AI & computer vision in government operations: Advantages and limitations
- Current use cases & applications
- The future of AI in government
- Key takeaways
AI & computer vision in government operations: pros and cons
Deployment of AI and computer vision applications for state and local government processes is gradually becoming widespread. Some governments utilize it more while others are still anticipating integrating more AI into their day-to-day operations within the near future. In fact, there is something known as a “government AI readiness index” provided by Oxford Insights that showcases which international countries are utilizing AI in their operations or allocating sufficient funding for it in the near future. Currently, the top five countries according to the index are Singapore, UK, Germany, USA, and Finland in 5th place.
But what does the public sector have to gain or lose from entrusting valuable aspects like national security to artificial intelligence? As always, there are positive and negative sides to just about anything.
Here is a detailed breakdown of the pros and cons of computer vision applications for state and local government:
Advantages
- Reducing human error — Long hours of work, miscalculation, or momentary lapses are all what lead to human error in processes. It is estimated that AI error chances are ~3% for executing computer vision tasks like image classification and other methods of image annotation, for example, while human error is ~5% for completing those tasks manually.
- Cutting down manual labor — It is important to note that this is not synonymous with a reduction in workforce or a decrease in the importance of specialists in governmental spheres. Simply, with the use of AI in government, specialists can dedicate more time to tasks that require their expertise with less time spent on manual tasks such as sitting through hours of surveillance footage.
- Diversity and variety of resources — One of the major perks of AI is a system’s capability to absorb substantial information (and a variety of it) in a short period of time. Object detection is an exceptional example of how the computer can be trained to “see” and label several objects in one frame despite their variety of them. Animals, people, cars, and other objects can be identified and labeled correspondingly at once. This is merely one example of how AI can offer a multitude of opportunities in use that would otherwise require a larger pool of resources.
- Predictive capabilities — Depending on the algorithm and model utilized, AI can be trained to provide predictive analysis of data to make advanced predictions that can later go on to provide substantial information for policymaking.
Limitations
- Chance of authoritarianism — By essentially automating facial recognition and detection, governments are able to monitor and track individuals’ movements among society. This proposes a situation where on one hand, national security can immensely improve as a result of this while on the other hand, governments may misuse this newfound opportunity, diverting from AI ethics. Authoritarian governments can decide to closely monitor the daily activities of residents that go beyond the appropriate level of interference.
- Adaptability to new processes — Statistically, the majority of employees in government or high positions in the public sector are millennials or from older generations, which leads to less preference for new technology implementation. People are used to their manual processes and know how to navigate the necessary tasks while working alongside AI would require learning how to co-exist and adapt to newer modes of work. Depending on demographics, some branches of government are less enthused about incorporating AI and computer vision in their processes or prefer to do so gradually.
Current use cases & applications
AI and computer vision applications in government or public sector institutions are not limited to developed countries. There are many vital processes that are possible to streamline with the help of artificial intelligence that have already been deployed for years, ensuring our well-being and supporting us. Both machine learning and deep learning algorithms are utilized to execute a variety of resourceful tasks. Here are a few of the most prominent use cases that currently exist worldwide.
Surveillance and road monitoring
The day-to-day tasks of the local police are significantly impacted for the better when computer vision is integrated into their field of work. They can spend less time in front of a surveillance camera recording, searching for the data that they want to find, and more time analyzing the data that the algorithm detected and highlighted. Both machine learning and deep learning algorithms can be utilized for surveillance in order to accurately and quickly detect criminal activity.
Fraud detection
AI and computer vision in the government is also targeted towards handling internal affairs as well. That includes but is not limited to assessing individual documents, financial transactions, healthcare records, and so on to detect fraudulent activity or discrepancies. A system that is equipped with predictive analysis algorithms is an optimal example of how AI can streamline problem-solving. That will help navigate both current and future prospects with the use of the data available.
License plate detection
Detecting license plates from live footage is a vital task for public security. Thanks to optical character recognition (OCR), a dedicated system will be able to detect license plate numbers. It is by far one of the most widespread applications of computer vision utilized for public security. Via this, the process of identifying stolen vehicles, labeling vehicles that have violated traffic regulations, and other related tasks are executed with more accuracy and ease.
Virtual assistants
According to a survey carried out by Gartner across ~300 participants in some branches of the government from around the world, chatbots, and virtual assistants were found to be the most prominent AI applications on a government level. These virtual assistants or chatbots are primarily deployed to answer questions from residents on a local and national level regarding specific institutions such as healthcare, transportation, military, security, and so on. The implementation of this technology has significantly cut down on processing times and increased the response rate for their claimants.
Natural language processing (NLP)
Natural language processing is the branch of AI that concentrates on in-depth analysis of how people speak and talk. It considers the analysis of a variety of data from audio to visual and then later utilizes that information to execute different processes. Those processes include doing digital translations, identifying handwriting differences and similarities, transcribing, and so on. All of that is to benefit high-priority tasks in government related to assessing the handwriting of alleged criminals, predicting gaps in criminal evidence that are unavailable, and much more thanks to machine learning algorithms.
The future of AI in government
With all of the current information in consideration, specialists in the field have preliminary predictions about how the future of AI and computer vision in governments across the world will look like.
That includes but is not limited to:
- More financing for “gov-tech” (government tech and AI). More and more countries are anticipated to provide upwards of $500,000 as an annual budget for implementing AI into government operations.
- More governments will refer to AI as an investment that can cut down on processing and manual labor costs. According to Deloitte Insights, automation of tasks, primarily paperwork, in the federal government can save governments at least 3 billion dollars annually.
Last, but not least, it is predicted that the controversy and hesitance towards AI implementation in more sections of the public sector will die down. Many are fearful that people will remain unemployed as a result, however, newer developments are confident that while AI may eliminate a million jobs, it will also create millions more. Additionally, employees will be able to direct their efforts at more critical tasks in their field while working alongside the technology.
Key takeaways
AI and computer vision in governmental and public sector processes are gradually becoming widespread across the world — with some countries ahead of the game at the moment than others based on preferences and opportunities. However, that doesn’t mean state-of-the-art AI is out of hand’s reach for governments across the globe. As we saw with only a handful of use cases for computer vision in government processes, many of the examples we covered are utilized in dozens of countries to benefit national security, accuracy of reports, and streamline processes with the latest technologies. Nonetheless, the future of AI in government is promising and will come with paramount benefits for everyone involved.
