BEA

Information

Start: 01.07.2021
Duration: 3 Years
Funded By: DFG (Deutsche Forschungsgemeinschaft)
Local Head of Project: Prof. Dr. Elisabeth André
Local Scientist: Klaus Weber
Webseite:

 

 

 

BEA - Bot für Engagiertes Argumentieren © University of Augsburg

About the Project

For humans, a natural way of resolving different points of view or forming an opinion is through conversation, i.e., through the exchange of arguments and knowledge. On the other hand, numerous opinions and information on almost every topic are nowadays also directly available online. However, the screening and evaluation of these multiple sources can be a time-consuming and demanding task. Filter algorithms aim to reduce this effort by taking previous user requests into account to serve the users’ interest. As a result, people tend to focus on a biased subset of sources that repeat or strengthen an already established or convenient opinion (so-called filter bubbles). In order to avoid this (often unconscious) process of intellectual isolation, we herein propose an approach to explore a vast amount of different information in a natural and intuitive way – through a conversation. To this end, we propose a virtual agent that engages in a deliberative dialogue with a human user in order to support a fair and unbiased opinion building process. In contrast to persuasive systems, the envisioned agent has no topic-specific agenda, but instead aims for providing a diverse and representative overview - embedded in a conversation with the user.

 

The proposed system will extend technologies investigated and developed in the scope of the EVA project during Phase I of the SPP Priority Program RATIO. Whereas in the EVA project users assumed the (passive) role of the audience, the system envisioned for Phase II will allow the user to actively participate in the argumentation process through a natural language interface. Therefore, the system will be able to react to user utterances, such as opinions, requests and questions, and provide an individualized conversation over the discussed topic. This will be supported by a transparent presentation of pros and cons towards the discussed topic through the agent’s access to recently developed argument search engines and thus contribute to explainability and deeper understanding.

Search