DISA

When? Friday November 14, 14-16
Where? Onsite: D2273 and via zoom

Agenda
14.00-14.10 Welcome and practical information
14.10-14.55 Presentation and discussion: 
Artificial ‘ulama – Analyzing AI-Generated Islamic Theology – Jonas Svensson 
14.55 – 15.05 Coffee break
15.05 – 15.50 Presentation and discussion:  
Socio-Technical Considerations on Inter- and Intra-Organizational Sustainability Data Sharing – Anna Sell  
15.50 -16.00 Sum up and plan for our seminars in December

Abstracts
Artificial ‘ulama – Analyzing AI-Generated Islamic Theology – Jonas Svensson
The presentation provides information on, and preliminary findings from my research project Artificial ‘Ulama, examining how artificial intelligence systems produce Islamic theological content. The study focusses on how modern Large Language Models interpret and respond to prompts based on Islamic texts, concepts, and interpretational frameworks.

The presentation will focus preliminary results on having LLMs translate and interpret the Qur’an, produce views on  inter religious dialogue and producing synthetic data. 

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Socio-Technical Considerations on Inter- and Intra-Organizational Sustainability Data Sharing – Anna Sell
In response to new sustainability reporting requirements, such as the EU Corporate Sustainability Reporting Directive (CSRD), companies are increasingly expected to collect and share sustainability data, not only within their own operations but across entire supply chains. Most manufacturing companies operate in multiple supply chains and must adapt to the varying data requirements of each. The cross-organizational scope, unclear data expectations and lack of standardization make sustainability data particularly challenging to work with. Internally, companies’ existing data infrastructures and reporting capabilities are tailored to traditional business data, making them ill-suited for the complex and heterogeneous nature of sustainability data. In this research we explore the paradoxes and barriers that companies must navigate in order to move from compliance-driven reporting to value-creating use of sustainability data.  

When? Thursday November 6, 10-12
Where? Onsite D1172 and via zoom
Registration: No registration needed – just come by

Abstract
Transcribing numbers and Receipts with Generative AI – Nemi Pelgrom
This dissertation investigates the usability of multi-modal language models (MMLMs) as transcription tools, with a focus on their reliability, limitations, and error mechanisms in document parsing tasks.

The work addresses four research questions across three studies. First, the potential of vision-capable generative models for extracting structured information from complex financial documents is evaluated using GPT-4. Tested on 1,000 digital invoices and 1,000 photographic receipts, the model achieved near-perfect accuracy, 99.8\% and 99.5\% respectively, with an additional API-based trial reaching 94.4\%. Second, the capacity of MMLMs to transcribe long numerical strings is explored, showing that GPT-4 and GPT-4o maintain 100\% accuracy up to 75 digits, after which performance drops sharply. Third, systematic error patterns are identified in transcription of random number sequences; mistakes consistently occur in the same positions across repeated runs, and hallucinated digits account for only 23\% of total errors, indicating biases and structured failure modes rather than noise. Lastly, a framework for categorisation of transcription errors is introduced, based on the analysis of 5,502 mistakes across GPT-4o and ARIA.

This reveals three mutually exclusive categories, and a detailed examination of ways to automatically distinguish between them, where the Ratcliff/Obershelp similarity was found to be highly useful. Together, these findings demonstrate that state-of-the-art MMLMs can already be deployed in production settings where accuracy and scalability are critical, while also providing systematic methods for diagnosing their weaknesses and guiding future model development.

When? Friday 24 October,14-16
Where? Onsite: D1172 and via zoom
Registration: Please sign up for the seminar via this link, https://forms.gle/m3nRqxaQmnv8zETb6 by 20 October.

Agenda
14.00-14.10 Welcome and practical information
14.10-14.55 Presentation and discussion: 
The Self-Healing Hypochondriac: Confessions of an AI Nerd: From Skeleton Avatar Technology to medical insights and future directions in AI for eHealth – Welf Löwe
14.55 – 15.05 Coffee break
15.05 – 15.50 Presentation and discussion:  The Journey and Lessons of Emerging Technologies in Education: Insights from the European Project Exten.(D.T.)² – Alisa Lincke
15.50 -16.00 Sum up and plan for our seminars in November

Abstract
The Self-Healing Hypochondriac: Confessions of an AI Nerd
From Skeleton Avatar Technology to medical insights and future directions in AI for eHealth – Welf Löwe

This talk introduces our Skeleton Avatar Technology (SAT), an AI-based approach to video motion analysis. We will present ongoing research, recent results, commercialization efforts, and future directions, highlighting how SAT can provide valuable medical insights and transform applications in healthcare and elderly care. In addition, we will briefly outline our other research activities in AI and eHealth.

The Journey and Lessons of Emerging Technologies in Education: Insights from the European Project Exten.(D.T.)² – Alisa Lincke

This seminar introduces the Exten.(D.T.)² project (Extending Design Thinking with Emerging Digital Technologies), a Horizon Europe / Innovate UK initiative (2022–2025). The project enhances Design Thinking in schools by integrating technologies such as AI, augmented reality, robotics, 3D printing, with a main focus on authorable learning analytics and dashboards. Implemented in six European countries, it explores both the opportunities and challenges of using these tools to foster creativity, collaboration, problem solving, and digital literacy. Personal experiences from European research projects will be shared, with reflections on lessons learned in cross-national collaboration.