Applying AI to crowdsource public decision-making in Belgium

Summary: The AI digital participation platform enables governments to make better-informed decisions while saving time and resources.

Client: Belgium

Problem Statement: 

The government of Belgium is increasingly striving to create policies and services driven by citizen input. This inherently requires significant engagement with citizens to grasp their perspectives, opinions, and needs. Digital participation platforms are vital tools for facilitating this engagement and enhancing government responsiveness. The primary challenge in citizen participation projects is not gathering input but analyzing it. Overburdened and under-resourced administrations often lack the time and technical expertise to process the contributions, leading to valuable insights being overlooked. AI can assist by efficiently processing citizen input and extracting key ideas, enabling governments to make better-informed decisions while saving time and resources.

Results: 

• In October 2019, the city of Kortrijk, with a population of 76,265,  was the setting of the first digital referendum in Flanders. The central question posed was: “Do you agree that the center of Kortrijk should be car-free for a fixed Sunday every month?”  Kortrijk utilizes intelligent dashboards to efficiently process contributions from the 1,300 users on their platform. They have organized ideas from discussions into main topics and shared the analysis results with the public. This approach fosters a genuine dialogue rather than a top-down directive. In Kortrijk’s “Great Questioning,” the initial results were announced just two weeks after the launch.
• The city of Temse engaged its citizens in discussions about mobility, mapping out their suggestions across the city. This process aided the administration in pinpointing areas affected by significant issues and deciding where to invest funds. By automating the time-consuming task of analyzing data, the platform allows administrations to invest more time in meaningful interactions with citizens. Furthermore, it offers governments deeper insights into citizens’ needs and priorities, leading to more informed decision-making.
• In early 2019, Belgian youth initiated protests demanding action on climate change, which later developed into the Youth for Climate Belgium movement. In response, CitizenLab established a participation platform called Youth4Climate, encouraging users to contribute ideas on addressing climate change. Within three months, users submitted 1,700 ideas, 2,600 comments, and 32,000 votes on preferred initiatives. An AI system analyzed this input, identifying and grouping the most significant and supported priorities.
• From citizens’ perspective, the use of CitizenLab’s NLP technology fosters trust and bolsters support for policy decisions. Additionally, it positively influences citizens’ willingness to engage in civic matters.

AI Solution Overview:

Belgium’s CitizenLab has created a public engagement platform empowered by ML algorithms, aiding civil servants in efficiently managing and utilizing thousands of citizen contributions for decision-making purposes. The platform’s dashboards categorize ideas, identify emerging topics, summarize trends, and group similar contributions based on themes, demographics, or location. CitizenLab has developed its own Natural Language Processing (NLP) techniques, utilizing ML and AI to swiftly extract key insights from large volumes of unstructured citizen input, such as ideas, comments, and votes. Leveraging Natural Language Processing (NLP), AI and ML, CitizenLab’s platform automatically analyzes citizen inputs collected from participation platforms. Ideas are classified, grouped, or geo-referenced automatically. Platform administrators gain immediate insights into citizen discussions, demographic variations in topics, and geographical distribution of conversations. With access to reliable data, policymakers can make informed decisions and craft policies that genuinely address citizens’ needs.

This enables civil servants to access real-time insights through intelligent dashboards, facilitating informed decision-making. The “Topic modeling” feature assists in identifying citizen priorities, while breakdowns by demographic groups and location provide a comprehensive view of variations in priorities. 

References: 

1. The human factor: helping governments tap into collective intelligence. https://www.citizenlab.co/blog/civic-engagement/the-human-factor-helping-governments-tap-into-collective-intelligence/
2. Natural Language Processing at CitizenLab: how machine learning can transform citizen engagement projects. https://www.citizenlab.co/blog/civic-engagement/natural-language-processing-at-citizenlab-how-machine-learning-can-transform-citizen-engagement-projects/
3. Applying artificial intelligence to citizen participation: the Youth4Climate case study. https://www.citizenlab.co/blog/civic-engagement/youth-for-climate-case-study/
4. Hello, World: Artificial intelligence and its use in the public sector. https://oecd-opsi.org/wp-content/uploads/2019/11/AI-Report-Online.pdf 

Industry: Crowdsourcing

Vendor: CitizenLab

Client: Belgium

Publication Date: 2019