One of the biggest issues faced by the public sector is a troubling gap in funding. It is estimated that this gap could total £8 billion by 2025.
The UK population is also expected to rise to nearly 70 million by this same year. The reality is that the demand for services are increasing yet resources are diminishing. Organisations must now innovate to meet the needs of their constituents.
The potential of artificial intelligence in the public sector was recently reviewed by the UK government. The results of this review were collated into a guide, published in June 2019. Using this guide, local authorities can determine how artificial intelligence could benefit them.
This is not to suggest, however, that artificial intelligence is a silver bullet solution. 'Artificial intelligence' encompasses many different processes and potential applications. This article will discuss some of the core components of AI, and how they can transform the public sector.
Automation has assisted many organisations in reaching new levels of efficiency. Like artificial intelligence in general, automation starts with algorithms. An algorithm is a pre-programmed instruction which allows AI to interpret information. This information enables a bot to perform tasks with minimal human intervention.
Artificial intelligence can help organisations in the public sector automate time-consuming processes. For instance, the Ministry of Justice (MoJ) began automating analyses of prison reports. This analysis would inform ongoing policies, but it suffered from a lack of structure. They created an ‘intelligent search tool’ to automatically categorise words and terms. Once the tool was implemented, the MoJ could quickly identify trends in inmate geography and behaviour.
Manual tasks such as data entry can have a long-term detriment on resources. Automating these processes enables humans to focus on more complex tasks. Over time, public sector services will become cost-effective without having to compromise on quality.
Fast Customer Service
Workers in the public sector spend a considerable amount of time answering routine queries. The answers may be simple, but the demand placed on staff can make customer service slow and inefficient. This is why many local councils are utilising chatbots. The goal is for chatbots to replicate human conversation, achieving a balance between fast service and customer satisfaction.
Natural Language Processing (NLP) is the technology through which bots comprehend human language. For bots, NLP has two main functions, not only understanding the words but also their intent. We must remember that words are not static – their meaning can shift based on context. This can cause complications for a bot, as they operate from quantitative data. For bots to effectively converse with humans, they must be programmed with a large linguistic dataset. This will help them make connections with certain words and their intended meaning.
One of the key characteristics of artificial intelligence is deep learning. Much like the human brain, a bot’s ability to learn increases as it processes more and more information. As a chatbot interacts with human beings over time, it will achieve a greater understanding of the subtleties of language.
We Build Bots recently worked with Monmouthshire County Council to develop its new chatbot, Monty. The success of this chatbot is a testament to NLP, as Monty is able to communicate in both English and Welsh. Monty is available 24/7, providing real-time responses to questions ranging from bin collection to housing.
Data-Driven Decision Making
All artificial intelligence is data-driven, and in 2019 we have access to unfathomable amounts of data. In fact, 90% of today’s data was created in the last two years. This data can be used in an unprecedented number of ways. For instance, it could be used for market research, behavioural analyses or sales. Every day, human beings make informed decisions. These decisions are based on our experience of a situation or environment. Even though at times we are driven by instinct, we never make inherently random decisions. In comparison, a bot will understand a task or situation based on data. As a bot processes more data, it becomes proficient at making accurate predictions.
A great example of predictive technology is how a signalling company created an AI system to help reduce train delays. This system drew on historical data taken from timetables to forecast lateness. It also identified patterns to determine possible reasons why these trains may be late. This allowed controllers to make data-driven suggestions for alternative routes. Using predictive analytics would yield remarkable results. After trialling the new system, London train stations reduced daily lateness by nearly 200 minutes.
When organisations make the wrong decisions, the consequences can be costly. With funding in such short supply, decisions must be made with absolute certainty. Predictive analytics can help make informed decisions with measurable outcomes.
At We Build Bots, we provide cutting-edge artificial technology for organisations across the public and private sector. By reducing service times and meeting audience needs, artificial intelligence can deliver a compelling return on investment. If you want to learn more about the benefits of artificial intelligence, contact us today to book a demo.