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Are governments ready for AI?

20 minute read
When the Summer Olympics were about to open in Beijing, China, Government concerns about the city's dire pollution issue have escalated.
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When the Summer Olympics were about to open in Beijing, China, Government concerns about the city's dire pollution issue have escalated. To avoid risking the health of athletes and visitors who came to the city for the Games, The government has closed dozens of nearby factories and imposed driving restrictions that have reduced traffic congestion by 90 percent, according to recent government reports. The Beijing government had no choice but to take such measures, which many saw as harsh and affected the region's economy.

Today, Beijing is dotted with sensors capable of measuring the volume of carbon dioxide and other pollutants in the atmosphere. Action has also been taken to convert data from these instruments and information provided by the city's meteorological service into an algorithm developed by IBM's Almadden laboratory in Silicon Valley to predict how the city will be affected by high levels of pollution. Based on the results, Entities can choose which factories to close if they want to reduce their risk of exposure to high levels of pollution by 50 percent before the situation worsens.

The technology responsible for all of this is artificial intelligence.

By collecting a huge amount of data and linking it to previous data related to weather patterns, The city can anticipate the severity of pollution and thus control the manufacturing sector and traffic early instead of shutting down the entire city as happened in 2008. This is a practical way to use AI to mitigate the challenges facing cities, reduce their impact on the economy and reduce pollution in general.

Progress based on a large amount of data

If you're looking for one word that sums up today's AI description, it's definitely "practical." While individuals are either excited or wary of the idea that computers are able to see, hear and speak, Governments are confident in practical applications of AI that can improve the environment, enhance security in public spaces and, most importantly, manage backlogs that disrupt government operations.

In contrast, We find that the era of artificial intelligence has already begun in the private sector. The Economist explored the role of AI technologies in reshaping traditional tasks such as supply, finance, human resources and customer service. For example, Companies use AI to predict which equipment is likely to malfunction or a user may be late in paying their dues. 30 percent of companies use their own chatbots to answer questions and resolve outstanding issues. In the field of human resources management, Companies are creating systems capable of predicting and surveying eligible job applicants for interview to ensure diversity in the company's employees.

We mentioned just some of the limited examples experts consider to be for AI applications where machine learning, neural networks, and predictive analytics deliver results that are properly understood. Specific AI applications are associated with intelligent automation of mechanisms that require a lot of manual labor and questions that require decisions that can be transferred to computers.

Artificial intelligence is evolving with a large amount of data. Until recently, The process of storing and processing data was very expensive for anyone. However, the costs of storage and electronic devices have dropped significantly, enabling entities to adopt artificial intelligence.

But so far, the adoption of artificial intelligence in government and local agencies is still following a similar trend to the adoption of technology in general. It happens, but at a slower pace and at a much smaller level when compared to the private sector.

Governments should benchmark their adoption and application of AI technologies with the application of other private actors working in a similar field, such as finance, banking, and other financial services. When looking at those who have achieved advanced performance in these areas, We find that 15 percent of them have invested significant amounts in scalable applications versus a 2 percent investment in the government sector. This is only a testament to how big the gap is, and more importantly, governments need to move faster toward adopting AI technologies.

Dialogue with the Government

Despite somewhat modest efforts to use AI in states and local areas, However, the desire to use artificial intelligence is strong and there are experiences in this field from which we draw many lessons and benefits. This is evident in AI-based conversations, Many governments have launched chatbots. It is an emerging field where AI is making an impact on state and local governments and is undergoing a lot of experimentation. For example, The San Diego County Office has launched a chatbot to help police officers get critical information from the comfort of their vehicles. These officers contact the call center employee to look for the license plate number or verify a suspect's file. The chatbot, dubbed "Coptivity," is a voice-activated assistant that officers can communicate with from the comfort of their cars and is able to extract criminal records and other information from databases in real time. It also saves time for call center staff to perform routine tasks, allowing them to focus on more advanced information requests. This AI application would not be possible without cloud computing that collects data, cognitive services, and cutting-edge computing that enables officers to respond quickly.

Chatbots are thus the most widespread form of artificial intelligence in government work. But for now, they are used in limited applications to answer simple and frequently asked questions. But its value increases when listening to more conversations, receiving and learning more questions, and providing feedback that improves customer services.

CallMiner works in the field of artificial intelligence programs and provides its services to call centers by listening to phone calls and storing information in a database that can later be used by other call centers to understand whether the customer is satisfied with the service and identify risks in the call and other consequences such as the ability to pay the bill. Over time, The algorithms developed by the company can increase the efficiency of call center employees many times, saving companies millions of dollars.

There is a real potential opportunity to use this distinctive form of AI as a way to improve the customer experience in government especially in 311 information centers. Individuals call 311 to get answers to their questions, request services, or file a complaint about a matter. By combining all types of calls into a single database and then creating a machine learning system, Local governments can start by predicting caller ID based on the source of the mobile or landline call, whether they have previously called the center and provide information about their previous calls. Through the exploration of this information, AI can route specific caller calls to specific employees who can answer their questions or complaints faster and more accurately.

AI experts point out that the value of this current technology lies in its ability to transform a large amount of data, find glitches or patterns that may take a long time for humans to notice, and then use alerts to prompt employees to ask more relevant questions or enable the chatbot to provide more accurate answers. When these alerts, alerts and smart responses are circulated to a large number of government service centers and from 311 municipal systems to medical assistance eligibility programs, Performance efficiency starts with an impact on operations not to mention higher customer satisfaction.

Artificial intelligence as a tool to enhance performance, not a substitute

AI experts envision a stage in the near future in which chatbots will answer an increasing number of calls, inquiries and complaints on 311 and also predict the ability of these robots to transfer the initial questions that may be asked when calling the emergency number 911 before being transferred to the contact person. But the technologies are not yet there.

The challenge is to bring the call with the chatbot closer to a normal conversation. For now, Chatbots work well when asked a question they understand and can answer. But this is different from the nature of communication between humans. If you contact any call center, the employee and caller will exchange several questions and answers to clarify the situation. Reaching a normal call in which the robot exchanges information with the caller to understand their need is an important part of research in this area.

Other challenges arise with the widespread use of artificial intelligence, The first challenge concerns developing a better understanding of the source of some of the interrelationships. There is a vast difference between interrelationships that predict and make decisions based on air pollution patterns that affect the health and safety of individuals or other important government policy.

AI should therefore act as an enhancer of the task that people are performing, not as a substitute for them. This means that the expert responsible for making decisions based on artificial intelligence techniques is familiar with the data sources, outputs, and reasons that led the system to come up with a recommendation or link.

Another challenge is to maintain the neutrality of AI results. Almadon Labs spends a long time figuring out a way to make sure that the AI system hasn't been subjected to unintentional bias, but it's not an easy issue to solve.

Local and state governments face their own hurdles when starting to use AI, Beyond the fundamental challenges related to AI itself. We would not be surprised to learn that the continued decline in investment in information technology in the government sector has delayed the government's adoption of artificial intelligence technologies. The technical ecosystem in both local and state governments is very old and has not been updated as often as we see in the private sector.

The low number of data scientists in the government sector is another reason for the slow spread of AI technologies in the government sector. If they do not have the right knowledge or experience to come up with AI solutions, Local and state governments will rely on third parties to figure out the most appropriate way to use AI. We cannot forget here the concerns of individuals towards artificial intelligence. Therefore, The government should be more transparent than the private sector in adopting and using AI.

Let's beware of the technical gap

In a 2017 report on the potential uses of AI in government, Deloitte Insights predicted that AI will save 30 percent of government employees' time within five to seven years, provided there is the right investment and support. Similar to the change that digital spreadsheets have brought about in the nature of corporate accounting departments, A report by The Economist predicts that AI will bring efficiency to routine tasks and support processes.

This efficiency is expected to be achieved at the local and state levels. Government entities using AI can have the potential high value of combating fraud, waste and misuse of AI.

The best way to get started with AI is to identify key places where the technology can be applied in a program. The other aspect is related to ensuring that there is enough data in this program to train the system effectively.

If local and state governments have a candidate program for the application of AI and a sufficient amount of data, It can leverage existing knowledge software on the market to help it start a productive application of this technology. Providers of these technologies are particularly interested in the government sector market in terms of artificial intelligence.

In pursuit of a strategic approach to the future role of AI in government work, State and local governments should focus on dialogue with as many individuals as possible. Society is used to dealing with artificial intelligence in the commercial field and expects to use a virtual assistant, a chatbot, or any kind of smart service, It is therefore important that governments do not lag behind in adopting AI.

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