[bctt tweet=”In spite of advances in technology and changes in the economy, governments still operate on an obsolete 1970s model. We have a typewriter government in an Internet age – Matt Blunt” username=”accubits”]
Governments or Public services is one sector which can benefit the most out of the technological advancements. However, it probably is the laziest sector in adopting newer technologies. Most government agencies across the world still run using obsolete technologies and are missing out big time on the opportunities to improve governance using cutting edge technologies. In this article, we see how NLP – Natural Language Processing, which is a subset of Artificial Intelligence can help government agencies to offer better governance and enhance the citizen experience.
The key hurdle for the government is to get the already existing data usable. At present, most of these data are unstructured and not in digital format. Since most of the public offices still follow the traditional mode of documentation, making sense of the huge volumes of unstructured data is impossible, unless the office leverages on cutting edge technologies such as NLP, NLU – Natural Language Understanding, Machine learning, etc. Unstructured data can be anything such as reports filed by government employees, or feedback from public websites, and social media conversation by the public. Since the majority of data is unstructured, it becomes a challenge to identify patterns and to draw insight from it which is essential for better governance.
It’s better to think of unstructured data as being “trapped” in physical and virtual file cabinets. The immense inflow of unstructured data in both analog and digital form presents significant challenges for government operations, decision making, rule-making, policy analysis, etc. If the government could connect the dots and identify the patterns, it could improve effectiveness and helps to make better decisions.
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Natural Language Processing is simply the technology that enables a machine to process natural human language such as speech, text, etc and enable the machine to understand it. It can understand the entire process of recognizing human speech, understanding and processing natural language, and generating text that can be read and interpreted by humans. NLP has many capabilities. These capabilities allow government agencies to recognize patterns, categorize topics, and analyze public opinion.
Topic modeling is a technique based on statistical algorithms that help to uncover hidden topics from large collections of documents. These models are unsupervised methods of NLP and do not depend on predefined labels. Using such a model, governments can understand how citizen complaints. For instance, in the UK, mortgage complaints often contain allegations of racial discrimination. Uncovering such topics allows the government to address them.
Text categorization can identify and sort the text into specific taxonomies after training by a human. For example, complaints from citizens can be automatically classified into specific categories and send to appropriate departments.
Text clustering is used to group text or documents – such as news articles, tweets, and social media posts – based on similarities in content. Then it can be analyzed to discover important but hidden subjects.
It can be used to automatically find meaningful information in unstructured text. This would help to speed up government services and bring transparency and accuracy in government services. For instance, police reports are often written in haste and crime witnesses’ and victims’ accounts can be incomplete. In such cases, NLP could scan through witness and police reports and related news articles to identify crucial elements such as weapons, vehicles, time, people, clothes, and locations with high precision.
Sentiment analysis can extract the meaning behind the human language. This will allow government agencies to analyze and interpret citizen and business comments on social media platforms, websites, and other venues for public comment. For example, sentiment analysis can be used to examine the experiences of patients with various health care providers.
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NLP can provide the tools needed to identify patterns and insights from unstructured data, allowing government agencies to improve operations, identify potential risks, solve crimes, and improve public services. Let’s see how NLP can make use of unstructured data to improve governance.
Using NLP government agencies can analyze public feedback and use these insights to improve their services. NLP can analyze feedback, particularly in unstructured content, far more efficiently than humans can. Whether it’s a comment dropped into a suggestion box or an online survey or various grievances posted on social media, NLP helps government agencies to understand citizen concerns and better serve the public. Apart from that governments can also implement chatbots in public portals to guide the users to the right services and also answer their queries thus improving public service.
NLP-based solutions can improve investigations in critical areas such as law enforcement, defense, and intelligence. NLP can uncover connections implicit in large text documents taken from the crime scene. The European Union launched an initiative called RED (Real-time Early Detection) Alert to detect terrorism-related activities by using NLP to monitor and analyze social media conversations. The system can provide early alerts of potential propaganda and signs of warfare by identifying online content posted by extremists.
One of the best things about implementing NLP along with machine learning is its ability to facilitate better predictions which help government agencies to come up with preemptive measures. For example, police can use NLP to fight crime by observing the patterns and interrelations in criminal activities and identify pockets with a high incidence of crime, thus allowing for quicker interventions. It’s said about 75% of child trafficking involves online advertisements. NLP can be used to monitor and draw connections among the dubious content of online advertisements to prevent child trafficking.
Hospitals and health institutions generate a large form of both digital and paper-based unstructured-data. Using AI and NLP technologies, governments can derive valuable insights from it and make appropriate decisions and budget allocations to improve a country’s overall healthcare. Apart from that studies shows that many a time several patients are sent to wrong medical departments. Hence, by augmenting health records and by applying text analytics along with NLP, health institutions and hospitals can direct the patients to the right medical department.
The spread of fake news is a problem faced by governments all over the world. Fortunately, NLP can be used to tackle fake news and cyber-attacks. A key use of NLP is to understand the emotion or intent behind words. This will help government agencies to analyze the sentiment of suspicious posts on social media. For example, we can build a system to detect fake news in tweets by building models to automatically extract semantic information from Twitter posts. Another way to tackle cyber-attack is to create a database of annotated malware texts that can help security experts quickly draw critical information from lengthy threat reports instead of having to manually read through them.
NLP technologies and solutions can help governments to address the massive volume of emails, messages, letters, calls and social media posts from its citizens. Governments can use natural language processing to identify and prioritize the most urgent cases from thousands of emergency reports.
Government departments in most countries are under-skilled, under-staffed and resources are scarce. They face massive backlogs in many areas of their administration and as a result service delivery is often slow and poor. Although digitization of information is accelerating, government agencies still have to face the onslaught of unstructured data. Fortunately, Artificial intelligence technologies like NLP or Natural Language Processing can analyze such data in ways never before possible. It will help the government to derive meaningful insights and be more effective and efficient, decrease a lot of costs associated with bureaucracy while improving citizen services and ensure safety. That said the field is still nascent but holds great promise as a new generation of techniques and tools begins to unlock its full potential.
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