Location:
TRiSS Seminar Room, 6th Floor, Arts Building, Trinity College Campus
PaCE Team Presenting at Conflict Forecasting Workshop
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Conflict Forecasting Workshop: Methodological Innovations, Data Opportunities, and Policy Relevance
Background on Conflict Forecasting
Conflict forecasting has evolved significantly over recent years, spurred by advancements in statistical modeling, machine learning, and the growing availability of data. Traditionally, statistical and ML approaches have been central in predicting the likelihood, intensity, and duration of conflicts. These models often rely on historical data, socio-political indicators, and increasingly, real-time data streams, to anticipate conflict scenarios.
Parallel to these developments, theoretical frameworks such as game theory have offered insights into the strategic interactions among conflict actors, providing a understanding of conflict dynamics. Another very successful approach relies on the "wisdom of crowds," where collective judgment and prediction markets are used to forecast conflicts, capitalizing on the diverse opinions of a large group of individuals.
The surge in data availability, including social media feeds, satellite imagery, and real-time reporting, presents both opportunities and challenges for conflict forecasting. This workshop aims to delve into these various approaches, and to explore how they can be integrated and leveraged to enhance the accuracy and usefulness of conflict forecasts.
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Objectives of the Workshop
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Showcase recent research: highlight cutting-edge research in conflict forecasting, focusing on both methodological advancements and innovative data use. This includes exploring, among others, statistical models, ML algorithms, game theory applications, and crowd-sourced predictions.
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Explore data-driven opportunities: examine the impact of the increasing availability of diverse data sources on conflict forecasting, discuss how to effectively harness this data while addressing challenges like data reliability and ethical considerations.
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Consider policy implications: the workshop included a focus on how these academic advancements can be translated into practical tools and insights for policy-making. This includes discussions on how forecasting models can inform conflict prevention, response strategies, and policy formulation.
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Foster collaboration: create a place for researchers to collaborate, share ideas, and potentially form partnerships for future research endeavors.
Format: The workshop featured paper presentations organized in panels. Each session was followed by a Q&A segment, encouraging active participation and exchange of ideas.