I2SC Lecture Series

The Interdisciplinary Institute for Societal Computing offers a regular Lecture Series to bring together researchers of different academic fields to analyze and discuss the broad topic of society and technology. The Lecture Series is designed as a laboratory of interdisciplinary research to encourage cooperation and new research approaches. The series will feature a mix of speakers from Computer  Science, Social Science, and Digital Humanities.

April 26, 2024

Anja Feldmann (MPI for Informatics), TBD 

May 10, 2024 

Vagrant Gautam (Computer Science, Saarland University), On Gender Gaps in Natural Language Processing

May 31, 2024

Christoph Sorge (Professor of Legal Informatics, Saarland University), TBD

June 14, 2024

Dilrukshi Gamage (Computational Social Science, University of Colombo School of Computing), The Rise of Generative AI: Exploring Trust, Believability, and Social Media Dynamics

June 28, 2024

Aline Deicke (Digital Humanities, Marburg University), Correspondences of early Romanticism

July 12, 2024

Evelyn Gius (Digital Philology, Technical University of Darmstadt), Theory vs. Computation? On building many Bridges over the Gap

The Lecture Series is in building E1 7, Room 3.23, on the campus of Saarland University from 12h-13h.  

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Program

Anja Feldmann

MPI for Informatics

April 26, 2024 

TBD

Vagrant Gautam

Computer Science

Saarland University

May 10, 2024

On Gender Gaps in Natural Language Processing 

In the field of natural language processing (NLP), gender gaps are thought of and treated similarly to the gender wage gap in economics. I will present previous work on the Gender Gap Tracker at Simon Fraser University and more recent work done at Saarland University on pronoun use with large language models, to illustrate how gender gaps are technically operationalized in NLP. These examples will serve as motivation to discuss bigger-picture epistemological gaps in how “gender” is treated in NLP - typically as binary, immutable, and directly inferable from characteristics such as a person’s name, pronouns, and so on. Drawing on methodologies, frameworks and viewpoints from other disciplines, including work I was involved in on the use of intersectionality in AI fairness, I will end with my thoughts and hopes for closing the epistemological gaps, with the goal of addressing the technical gaps more effectively and justly. 

Christoph Sorge

Professor of Legal Informatics

Saarland University

May 31, 2024 

TBD

Dilrukshi Gamage

Computational Social Science

University of Colombo School of Computing

June 14, 2024

The Rise of Generative AI: Exploring Trust, Believability, and Social Media Dynamics 

We have entered a new era of artificial intelligence (AI), characterized by the rapid proliferation of Generative AI (GenAI) and its numerous applications. As humans, our interactions with “content” in various forms, including text, images, and videos, have undergone a profound transformation due to the integration of AI technologies. It has become increasingly challenging to discern whether we are communicating with a human or an AI model. Concurrently, the content generated using Large Language Models (LLMs) and AI-synthesized images and videos using Diffusion models have significantly altered our perspectives in the real world and on social media. 

In certain instances, we encounter AI-generated fake profiles during job screening or marketing. In other cases, we are confronted with AI-generated fake videos, such as deepfakes, on social media, which purport to depict actions that never actually occurred. Notably, in an era of clickbait-incentivized social media platforms, deepfakes and other forms of appealing AI-generated content significantly increase human engagement, leading to various potential outcomes, both positive and negative. 

It remains uncertain how we can establish trust in AI or how society will be impacted on a large scale by AI-generated content. Several questions arise: How much will share, incorporate, and interact with content created by AI? Will people “trust” the outcomes generated by AI? Will people believe what the majority share on social media? 

In this presentation, I intend to engage in critical discussions on the topic of trust in AI, present empirical research findings on the believability and shareability of synthetic content, and explore the broader societal implications of GenAI applications and interactions. 

Aline Deicke 

Digital Humanities

Marburg University

June 28, 2024

Correspondences of early Romanticism

Evelyn Gius

Digital Philology / fortext lab

Technical University of Darmstadt

July 12, 2024

Theory vs. Computation? On building many Bridges over the Gap

In those areas of Digital Humanities where computational methods are integral to analysis, it becomes essential to critically examine the interplay between humanities theories on the phenomena of interest and their computational analysis. While concepts such as operationalization and modeling have been under discussion for some time, there's still a notable absence of a comprehensive perspective on the entire research process which also includes humanities’ theories. I will suggest to view computational research processes in Digital Humanities as input-process-output workflows in which theoretical concepts serve as integral components at various stages. Drawing on computational literary studies as a case study, my presentation aims to elucidate the connection between theory and computation by proposing a methodology for enabling theory-driven validity.