Open Sci­ence - Shap­ing sci­ence to­geth­er

This image shows a cirlce with a missing part. The circle consists of three subunits. These units have different colors. These are: gray, blue and yellow. In the center of this circle there is a writing which says: "Open Science".

With the “Open Science” movement, scientists make their research processes visible to the public by clearly presenting their methods and sharing their data. This allows for fellow scientists and interested parties to understand the underlying projects and processes the scientist originally used in their research, and if necessary, collaborate on improvements beyond the confines of institutions.

“We raise the quality of our research by bringing transparency to the process” says Professor Dr. Katharina Rohlfing, spokesperson of TRR 318. “Within the Transregio, we are already working across disciplines: researchers from various scientific fields come together, exchange ideas and thus enhance each other’s knowledge. With Open Science, we are looking for exactly this kind of exchange with experts outside of the project.”

Re­sources

The TRR Wiki contains a glossary of terms from the field of explainable AI that are used in the subprojects of TRR 318. The Wiki was launched by members of the INF subproject and is continuously being updated and expanded.

Link: The TRR Wiki

The ADEX linguistic coding scheme is used to annotate the utterances of the interlocutors while explaining a game. This annotation includes the spoken and its content classification. The coding scheme was developed by TRR researcher Josephine Fisher in project A01 Adaptive explanation generation.

Download

Decisions made by Artificial Intelligence are not based on a single attribute, but on many. Most attributes interact with each other. Researchers of Subproject C03 developed the openscoure-tool shapiq to better understand these interactions. The tool allows the efficient computation of the attributes and can visualize the interactions.

More information in the GitHub-Repository.

The software was developed by project A05. The main focus of the system is to support the work in interdisciplinary teams and to enable also non-computer scientists to create, discuss and generate adaptive scaffolding strategies for robots in human-robot-interaction. 

More information: MAS / Projects / SFB TRR318 / A05 / SHIFT · GitLab

To the software

Um zu untersuchen, wie gut aktuelle Sprachmodelle (LLMs) ko-konstruktive Erklärdialoge führen können, haben Forschende des INF-Projekts einen Datensatz erstellt. Er umfasst Erklärinteraktionen zwischen Menschen und LLMs sowie Vor- und Nachbefragungen zum Verständnis der Nutzer*innen. Die Daten wurden analysiert und in einem Forschungsartikel veröffentlicht.

 

Link zu den Daten: GitHub - webis-de/sigdial25-co-constructive-llms-data

 

Demon­strat­ors from the work­shops

Medusa is an AI that uses neural networks to recognise faces and then assigns them to the male or female gender. Users can take pictures of themselves using a webcam or upload pictures, e.g. of celebrities, to test them (Medusa Image Checker).

Medusa - GitLab

Falcon is an educational software designed to help pupils familiarise themselves with neural networks. It uses reinforcement learning to teach spaceships to avoid asteroids. The underlying neural networks of the agents can be explored across the different generations.

Falcon - GitLab

This programme shows users various images of AI-generated and non-AI-generated animals, people and landscapes. Users have to decide whether the image is AI-generated or not.

Real or Fake - GitLab

The Etana AI is based on the principle of classification. Users can draw numbers from 0-9 in an input window and these are then recognised by the AI.

Etana - GitLab

The Demeter AI is characterised by the fact that it works according to the principle of reinforcement learning. The AI learns to play a game that is similar to the mobile game Flappy Bird. Users also have the option of playing the game themselves. Otherwise, they can let the AI play and observe how it learns and gets better and better.

Demeter - GitLab

Do Sci­ence Your­self! - In­struc­tions & tu­tori­als on sci­entif­ic meth­ods

Git is a free distributed version control system for software projects, released in its first version in 2005. The program allows multiple developers to work on a project simultaneously, regardless of their location.

Version control makes it easy to independently add changes to the project from anywhere, to log and track those changes, and to access older states of the project at a later time. Git is platform independent and can therefore be used in almost any environment.

TRR researchers Vivien Lohmer (A04) and Amelie Sophie Robrecht (A01) have summarised in a tutorial and cheatsheet how Git and sustainable data storage works:

Tutorial: GitLab-Tutorial and Guidelines

Cheatsheet: How to use GitLab.