Artificial intelligence for emergency response and civil protection: opportunities and application areas for Colombia.
An online workshop delivered by Dr. Kakia Chatsiou on 17th March 2021 to policymakers, academics and independent researchers in Colombia, as part of the COLGOV project, at the University of Externado, Colombia.
The workshop was offered as part of a larger course on "Evidence-based decision making", part of a joint initiative between the Faculty of Economics, Faculty of Finance, Government and International Relations (FIGRI) and the support of the Department of Mathematics of the Externado de Colombia University, in alliance with the University of Essex, within the framework of an initiative of the United Kingdom cooperation fund for Global Challenges (GCRF).
Whether by predicting the global spread of the novel coronavirus or detecting wildfires, the use of artificial intelligence (AI) in civil protection promises to improve the prevention of, response to, and recovery from disasters of a country i.e. its resilience. Maximising the potential of AI for civil protection, requires consideration of the data available for the machine to learn and requires public sector and other emergency response organisations to make the most of their digital data, moving away from data silos and becoming more digitally and analytically mature.
At its core, AI is a research field spanning philosophy, logic, statistics, computer science, mathematics, neuroscience, linguistics, cognitive psychology, and economics. AI can be defined as the use of digital technology to create systems capable of performing tasks commonly thought to require intelligence. AI is constantly evolving, but it involves machines using statistics to find patterns in large amounts of data. It describes a machine’s ability to perform repetitive tasks with data without the need for constant human guidance. Recent advances in AI, are facilitated through recent improvements to algorithms, huge growth in the amount of data created and stored by digital systems, as well as increased access to computational power and the expansion of cloud computing.
The workshop reviews recent advancements in AI technologies that could be used to address different civil protection challenges as well as some examples from around the world that could find an application in the Colombian context and ways these can help build resilience in the system. We highlight the potential of AI in developing application-specific algorithms and novel mapping platforms that will harness the large volume of data that first responders are now able to collect through heterogeneous sensors (including visual, thermal and multispectral cameras, LIDAR, CBRN sensors, etc.) on-board RPAS units, and converting that data into actionable decisions for improved emergency response, as well as the potential to mine text from social media and publicly available reports to better understand citizens' and governments' opinions and approaches to resilience building. We then outline ways AI can help build resilience in emergency response and civil protection, such as by providing more accurate information, forecasts and predictions or, by providing emergency responders and citizens with personalised public services tailored to individual circumstances and automating repetitive and time-consuming tasks which frees up valuable time of frontline staff. Finally, we review some important considerations for using AI to meet prevention, mitigation and emergency response needs such as data quality, fairness, ethics, privacy, sustainability, explainability and transparency, costs, accountability, compliance with data protection laws.
By the end of the talk, participants will have a better understanding of:
- recent advancements in AI technologies that could be used to address different civil protection challenges
- ideas/examples/case studies of the use of AI in an emergency response setting that could find an application in the Colombian context
- how different types of data (numbers, images, text) are being used to help societies meet prevention, mitigation and emergency response needs
They will also have the opportunity to share their own examples and AI applications with the rest of the group.
Note: All times are UK times.
| Time(Colombia) | Time (UK) | Topic |
|---|---|---|
| 10.00 - 10.10 | 15.00 – 15.10 | Welcome to the workshop & Aims Introductions |
| 10.10 - 11.00 | 15.10 – 16.00 | Using AI in Civil protection & Emergency response: definitions and common ground - What is AI? What is not AI? - Disaster management cycle - Civil protection challenges & opportunities - Activity 1: Civil protection challenges in Colombia |
| 11.00 - 11.15 | 16.00 – 16.15 | Break |
| 11.15 - 12.00 | 16.15 – 17.00 | Using AI in Civil protection & Emergency response: from response to prevention - AI helping on the ground responders (response) - AI helping restoring and reconstructing (recovery) - AI helping understand risks & raising awareness (mitigation) - AI helps understand and reduce risk (prevention/ preparedness) |
| 12.00 - 12.15 | 17.00 – 17.15 | Break |
| 12.15 - 13.00 | 17.15 – 18.00 | Activity 2: Can any of these examples apply to the challenges identified in Activity 1? Discussion & Summary of ideas |
- AI in the UK: the story so far (Gov.uk)
- AI Council
- Office for Artificial Intelligence
- AI Watch Artificial Intelligence in public services (European Commission)
- Resources for Research on Crisis Informatics Topics - Crisis NLP
- A safer, more resilient world: Reducing disaster risks with AI
- How can Artificial Intelligence reduce disaster risks in countries? | AI FOR GOOD LIVE
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- AIDR - Artificial Intelligence for Digital Response
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