Leveraging LLMs in Enhancing Multilateral Negotiations

Challenge Started!

Harnessing the power of AI with the Retrieval Augmented Generation (RAG) technique to streamline decision-making in foreign policy negotiations through efficient document analysis and insights. In this 8-week challenge, you will join a collaborative team of 50 AI engineers from all around the world.

The problem

In the intricate world of foreign policy, experts are frequently tasked with navigating complex negotiations that encompass a wide range of policy areas. These areas, which include but are not limited to digital rights, climate change, feminist concerns, and budgetary agreements, are underpinned by a vast and ever-growing body of policies, international treaties, and related documents.

The sheer volume of this information presents a multifaceted challenge. Firstly, accessing relevant documents in real-time during negotiations can be a daunting task, given the multitude of sources and the lack of a centralized repository. Secondly, once accessed, processing this information to extract pertinent points and understanding the nuances becomes time-consuming. This often leads to delays and can potentially result in missed opportunities or oversight of critical details. Lastly, leveraging this information to make informed decisions requires a synthesis of the data into actionable insights, a task that demands expertise and time.

Furthermore, the dynamic nature of international relations means that these documents are frequently updated, amended, or superseded, adding another layer of complexity to the process. As a result, foreign policy experts often find themselves overwhelmed, not just by the volume of information but also by the need to stay updated with the latest changes and understand their implications.

In essence, the core problem lies in the efficient and effective access, processing, and leveraging of a vast array of policy-related documents to aid foreign policy experts in their negotiations, ensuring that they are equipped with the most relevant and up-to-date information to make informed decisions.

This project seeks to address this challenge by harnessing the power of Large Language Models (LLMs) and advancements in Natural Language Processing (NLP). The aim is to develop an AI-driven tool that can swiftly analyze extensive policy domains, providing foreign policy experts with invaluable guidance during negotiations. This tool will not only streamline the negotiation process but also identify and summarize crucial actionable insights, serving as a comprehensive blueprint for navigating complex negotiations. Through this initiative, we also aspire to showcase the potential of AI tools in revolutionizing the decision-making process in foreign policy and negotiations.

The project goals

The ultimate goal of this project is to develop an AI-powered assistant using the Retrieval Augmented Generation (RAG) technique that can efficiently access, process, and analyze a diverse range of policy documents. This assistant aims to serve as a comprehensive guide for foreign policy experts, enhancing their decision-making capabilities across various policy scenarios and streamlining the negotiation process.

The main goals of this AI Innovation Challenge are:

Data Collection: Accumulate a comprehensive set of policies, treaties, and relevant documents across various domains, including digital rights, climate change, feminist concerns, budgets, and more.
Data Processing: Undertake the task of sanitizing, categorizing, and structuring the amassed data, ensuring it’s primed for efficient AI retrieval and analysis.
Model Integration: Incorporate the Retrieval Augmented Generation (RAG) model into the system (laveraging prompt engineering & vector database). This integration aims to proficiently retrieve and generate insights across multiple policy arenas, enhancing the tool’s analytical capabilities.
Interface Development: Design and deploy a basic user-friendly UI tailored for foreign policy experts. This interface will facilitate easy access to the AI tool’s features and insights.

Why join? The uniqueness of Omdena AI Innovation Challenges

A collaborative experience you never had in your working life! For the next eight weeks, you will not only build AI solutions to make a real-world impact but also go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.