AI Challenge
Prototype: AI Avatar – A trainer for diplomatic negotiation skills
This innovative tool is designed to support diplomats or attachés in training or in training in developing and practicing their negotiation skills. Users have the option to select from a range of predefined opponents representing diverse roles and areas of expertise, such as a diplomat specializing in climate policy, a Big Tech entrepreneur, or an EU representative focused on tariffs. Each avatar articulates its perspective in alignment with its role and strategic interests. Users can respond by recording their own statements, to which the avatar replies according to its position. Beyond predefined scenarios/roles, this prototype also offers the option to create customized cases: users can upload documents that the system processes into a new position or avatar for dialogue and debate. By engaging with these structured yet dynamic interactions, trainees can practice their responses /strengthen their ability to respond to complex real-world scenarios.
TECHNICAL EXPLANATION
In this prototype version, the Negotiation Trainer combines a FastAPI backend with a React frontend to create an immersive practice environment. Uploaded PDFs are processed with PyMuPDF, while ffmpeg and whisper.cpp handle German speech-to-text transcription. GenAI formulates opening statements and dynamic responses, which are delivered through a ReadyPlayerMe avatar using the Web Speech API. With this integration of natural language processing, speech recognition, and lifelike avatars, the tool provides a realistic and adaptive negotiation experience.
VISION
Future development of the Negotiation Trainer will include improved features for the user experience, including a wider range of predefined scenario options, offer preparatory tools for discussions, provide real life examples, and speech-to-text transcriptions available in multiple languages. Consideration is also being made for features such as defining goals and red lines, integrating cultural sensitivity, and enabling rapid-fire exchanges, which will allow users to practice under more complex conditions.
