Artificial intelligence and its related fields, including deep learning, have a wide range of applications. A recently published 2017 paper goes into detail on the various societal impacts of what has been dubbed the “forthcoming AI revolution.”
While the potential societal impacts of AI are disparate, two of the most important areas it has the potential to influence are the government and the public sector. This article goes into detail on five examples of using AI and deep learning within the government and public sector. However, you’ll first get a clear definition on what AI and deep learning actually are.
The term artificial intelligence was coined by a computer scientist named John McCarthy as far back as 1955. It is best understood as a field of computer science that enables computers and machines to learn how to perform tasks that normally require human intelligence.
Machine learning is an application of artificial intelligence concerned with using statistical techniques to facilitate computers in learning how to perform tasks and improving their performance at those tasks without specific programming.
Deep learning has emerged as a more advanced method of machine learning in which computer systems can model high-level abstractions in data. Applications of deep learning include providing color to black and white images, classifying objects in images, and assisting healthcare professionals with diagnosis through medical image analysis.
Advances in algorithmic computer science coupled with the availability of powerful computing systems at a relatively low cost have facilitated the rapid growth in AI and deep learning in recent years. Companies and governments can now easily use AI platforms, such as IBM Watson, platforms like Amazon Machine Learning, or deep learning.
The AI Index, published annually, keeps track of the progress and evolution of artificial intelligence. The 2017 AI Index reported that the number of AI papers produced each year has increased by more than 9x since 1996, reflecting a growing scientific interest in AI. Additionally, the same paper reported that the number of active U.S .startups developing AI systems has increased by a factor of 14 since 2000.
Cyberdefense is a subject that has been in the media spotlight in recent times after the revelations of Russian interference in the U.S. election process. With increasingly sophisticated forms of attack, it’s imperative that governments have technology available that can defend against such attacks.
Technology company NVIDIA, together with Booz Allen Hamilton, have teamed up to build machine learning and deep learning solutions that can detect cyber threats faster and more efficiently. The end result promises stronger federal cyberdefense and governments that are less susceptible to outside interference in their democratic processes.
Busy urban areas are often plagued with traffic congestion issues that local authorities struggle to contain. Part of the problem is that traffic congestion is surprisingly difficult to predict. Aside from the key rush hour times, traffic can build up at other times over the course of the day, causing significant backlogs on roads.
In an interesting 2016 paper, the results of an experiment to use deep learning methods for predicting short-term traffic conditions revealed excellent predictive value at 90 percent. Being able to predict traffic conditions hands the power back to local authorities and the personnel responsible for traffic control, assisting them in taking proactive measures to ease traffic congestion across the busiest areas of a city’s transport infrastructure.
A large part of the appeal of artificial intelligence lies in its ability to automate processes that are normally time-consuming for humans to perform. A set of processes that often presents significant problems to immigration and naturalization departments within governments is the application and processing of visa and immigration applications.
There is often a significant backlog in immigration departments due to the time it takes to process each case. However, AI can come into its own here by automating some of the processing, which helps to augment the roles of the civil service workers who still make the final decision on each case.
The powerful machine learning and deep learning algorithms that have revolutionized image detection and classification can be used by state police forces to identify criminals. Facial recognition software continues to improve, and governments can use these advancements to their benefit by identifying on-the-run criminals in public spaces.
The improved identification comes from using the software to analyze images from CCTV and other sources throughout a region in which the suspect is expected to be.
Many modern countries are multi-cultural and multi-lingual with inhabitants and visitors speaking a diverse range of languages. Frustration can arise in the context of public service settings when citizens or visitors seek to communicate with various governmental departments, only to find that their fluency in the local language is lacking.
Improvements in speech-to-text translation systems, thanks to machine learning and deep learning, can remove these communication barriers by providing real-time translation in public service settings.
The examples given here are just a snapshot of what artificial intelligence and deep learning methods can bring to governments and public sectors. As these technologies continue to evolve, expect to see the range of use cases of AI grow even larger and become more innovative.