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In the last lesson, you learned about some of the ways AI is integrated into your everyday life. Now, find out how AI is being used in the public sector.
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Complete the reflection activity (5 minutes)
In the last lesson, you discovered that — although there are two main types of AI — ‘machine learning’ is the type of AI most people are talking about today. You learned that instead of pre-programming computers with a set of rules, machine learning enables computers to develop intelligence from being exposed to large amounts of data.
In this lesson, you’ll learn some common ways machine learning is applied, before discovering how it is used in the public sector.
Let's pick up the conversation you started with your imaginary acquaintance in Lesson 1.1. In the last lesson, you discovered some general information along the lines of ‘what department they work in’. Now, you’re interested in learning the specifics of their role and areas of expertise.
Let’s deepen our understanding of what AI does by exploring some of its capabilities.
Here are 3 common ways AI is used, followed by everyday examples of the tasks it can complete and the types of problems it can solve1:
Computer vision extracts meaningful information from existing digital images or videos and can identify people's faces and objects. It’s used to unlock personal smartphones and help robots and self-driving cars navigate obstacles.
Natural language processing (NLP) interprets human language and can generate new spoken and written language. NLP is used to translate text from one language to another, answer questions and summarise information.
Speech recognition uses computers to analyse audio files to recognise and interpret spoken language. It is used to generate closed captions automatically.
Generative AI is a subset of machine learning that can create new content — such as text, images and audio — from large amounts of existing data.
Large language models (LLMs) are a type of generative AI that are trained on massive amounts of text data.
ChatGPT is a large language model (LLM) chatbot that uses natural language processing (NLP) to generate new text.
So far, we’ve thrown a lot of technical terms at you and we’re not expecting you to remember them. Download your glossary and be reassured that you don’t need to become a technical specialist to understand how AI impacts you and your government.2
Using the previous examples as a place to start, can you make some informed guesses about how AI is being used in the public sector?
Take a few minutes to think before navigating to the expandable boxes below to see some real-world examples from governments around the world.
In The Netherlands, computer vision has been used to detect trash on the streets of Amsterdam, improving refuse collection times by detecting garbage at an early stage and optimising refuse collection routes.3
In Singapore, the Smart Nation and Digital Government Group (SNDGG) launched a chatbot allows residents to easily report municipal issues via WhatsApp and Telegram. The chatbot guides users to provide relevant information in a real-time conversational manner to ensure that the feedback is accurately categorised and comprehensively logged.4
The Estonian Parliament is required to publish a verbatim report of all parliamentary sessions within an hour of them taking place. Since 2019, Parliament has been using speech recognition to replace stenography, a time-consuming ‘task that people are not particularly motivated to do’.5
You’ll discover more examples of how AI is being used in the public sector throughout this course, but what examples have you already heard about?
In this lesson, you learned about specific tasks AI can complete and some types of problems it can help the public sector solve.
Head to the next lesson to discuss what ideas have surprised and excited you with other learners on the course.
AI can be used to complete specific tasks and help solve various problems.
AI is used in the public sector to improve processes and services, from producing parliamentary meeting minutes to managing waste collection.
Berryhill, Jamie, Kévin Kok Heang, Rob Clogher, and Keegan McBride. “Hello, World: Artificial Intelligence and Its Uses in the Public Sector.” OECD Working Papers on Public Governance. Organisation for Economic Co-Operation and Development (OECD), November 21, 2019. http://dx.doi.org/10.1787/726fd39d-en, p. 15.
Working Group on AI Capacity Building, Tommaso Balbo Di Vinadio, Colin van Noordt, Carlos Vargas Alvarez del Castillo, and Renata Avila. “Artificial Intelligence and Digital Transformation Competencies for Civil Servants.” UNESCO Digital Library, 2022. https://unesdoc.unesco.org/ark:/48223/pf0000383325, p. 17.
Amsterdam, Universiteit van. “ABS Research Keeps Amsterdam Clean: Real-Time Image Recognition for Litter Collection - Amsterdam Business School.” Amsterdam Business School - University of Amsterdam, April 1, 2021. https://abs.uva.nl/about/inspiration/digital-and-ai/abs-research-keeps-amsterdam-clean.html?cb.
“New AI-Powered OneService Chatbot for Easy Reporting of Municipal Issues.” Accessed August 16, 2023. https://www.smartnation.gov.sg/media-hub/press-releases/new-ai-powered-oneservice.
Pihlak, Harle. “HANS, AI Support Tool for Estonian Parliament.” e-Estonia, December 18, 2019. https://e-estonia.com/hans-ai-support-tool-for-estonian-parliament/.
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