Data and AI for Social Impact
Data can tell us a lot about the world. It can reveal new details of the challenges that concern us most today at never-seen-before depths. Yet data alone are just numbers. It takes human expertise to understand, interpret, and take action.
We support Leiden University and its partners to enact social change using data and artificial intelligence (AI). We pilot data-driven solutions to societal challenges, and take into account the human aspects of data such as privacy, transparency and ethics.
Our Focus Areas
We use language understanding technology to connect to communities and make connections between people. For instance, we have used chatbot technology to connect to people in remote communities, such as farmers in Peru who inquire about realtime food prices. We can also unearth crucial information from overwhelming datasets and conduct social network analyses to search for connections between people and other entities of interest.
Geospatial Data Exploration
Maps and satellite imagery provide valuable sources of data. Our geospatial data exploration work includes designing complex filter systems and data visualisation, and helping partners to use geospatial information to search for vital information. Currently we are investigating if we can use geospatial data to map and find places of interest in remote (conflict) areas, such as cultural heritage sites.
Knowledge exploration encompasses projects where we delve into novel datasets and approaches to support the unique scenarios of our partner organisations. In this area, we focus on exploration capabilities and assessing data quality. We support our partners to get started with data analysis and interpreting insights, before going into any complex techniques. Moreover, this area allows us to explore new data- and AI-related tools and methodologies together with our partners.
We validate technologies by partnering with Leiden University faculties, and the public, humanitarian and private sectors. The ever-increasing abundance and use of data poses unique challenges and opportunities to all types of these organisations. We help our partners to better understand how they can use the data in their operations by piloting innovative solutions to their challenges.
To fully utilise maximise the use of data for social impact, we recognise we must protect the people behind the data. We focus on data responsibility throughout our projects to ensure that we minimise any potential risks associated with data-driven technologies, while maximising exploring possible opportunities. We analyse such risks and provide guidance for data responsibility in different contexts, among others by using our Data Responsibility Framework.
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Data & AI Stories
Using Facial Recognition in a Sensitive Context
Lessons learned from our pilot to support the validation of missing person inquiries One of the many tragedies of conflict and disaster is that people go missing, leaving their families to agonise over their fate, often for years. The International Commission on Missing Persons (ICMP) contributes to the search for these people through its Online Inquiry Centre (OIC). On the site, people can enter and retrieve information on individual missing person cases. One of the challenges presented by maintaining the OIC is the number of man-hours required to respond to inquiries that are received. Working with ICMP, the Centre for Innovation asked: would it be possible to support the verification of missing person inquiries by using facial recognition software? We developed a prototype to find out.