Thursday September 18 2025

Opening 2pm
Welcome with Seppo Gründler and Elisabeth Schimana

Introduction 2:30pm
Seppo Gründler - From Worms to Dartmouth and Beyond
History and Evolution of (Artificial) Intelligence

Always interested in the motivations, psychological and philosophical foundations of contemporary trends, I investigated the background and history of the attendees at the Dartmouth Summer Research Project on Artificial Intelligence in 1956, which is widely regarded as the birth of Artificial Intelligence. Where did the funding originate? Who were the invited guests, what were the backgrounds of these scientists, and what became of them afterward? Can we derive insights from the biographies of the scientists, their scientific, political, and personal backgrounds? What technological advancements were the driving force behind the project, and what AI technologies emerged directly as a result?

Only ten individuals attended, all male. Not much is known about the staff supporting the conference. The expertise ranged from Computer Science, Cognitive Science, Engineering to Psychology. Notably, no one affiliated with cybernetics or Norbert Wiener was invited. The term artificial intelligence was employed to distinguish the project from cybernetics.

However, the English term intelligence carries a more intricate meaning compared to its German counterpart, as exemplified by the Central Intelligence Agency. Analysing the term in its philosophical and sociological context can contribute to a deeper comprehension of the solutions and challenges associated with AI. Furthermore, considering the evolution of intelligence from the earliest brain appearing in a diminutive worm (Urbilateria) approximately six hundred million years ago, culminating in the brain of great apes (Homo sapiens) and subsequently, machines emulating human intellectual capabilities, provides valuable insights.

On the one hand, utilising the Dartmouth Summer Research Project on Artificial Intelligence as a pivotal point in the history of intelligence allows for a comparative analysis of the genesis of (artificial) intelligence. On the other hand, it serves as an excellent source of intriguing biographies, circumstances, and narratives.

Block 1 3:30pm

Elisabeth Schimana - Artificial Life, Neural Networks, and the Computational Brain
This block is dedicated to the early 1990s and asks about today..

As a student of musicology and ethnology, I encountered these concepts in a very condensed form in 1995 at the institute of scientific theory at the University of Vienna, and I was fascinated.

In his 1988 article “Artificial Life,” Christopher G. Langton propagated life beyond carbon-based life within a computer or other artificial medium. As a composer and musician of electronic music, neural networks for adaptive filters and pattern recognition, as well as speech recognition, were of great interest to me. And the fascination with modeling our brain using algorithms, or taking the signal processing in our nervous system as the basis for artificial neural networks, has remained to this day. The word intelligence was not of great significance in 1995.

Marlies Temper - Understanding Artificial Intelligence: The Technology Behind the Hype

Artificial intelligence (AI) is no longer a topic for the future - it already influences many areas of life today. But what is the technology behind this term? This lecture offers a concise insight into the fundamentals of modern AI systems: from machine learning and neural networks to current challenges such as bias, computing power, and interpretability. The aim is to explain how AI works and take a critical look at its possibilities and limitations.

Narly Golestani - Computational insights into the brain, language and aptitudes

How does the brain give rise to language, and why do our abilities differ? This talk will show how anatomy and experience shape the auditory cortex, and how machine learning can reveal hidden links between brain structure, language skills, and learning differences. I will also introduce computational decoding methods that make it possible to “read out” what the brain hears, opening new perspectives on the interplay between neuroscience and AI.

Ulla Rauter - Whispering Networks

Ulla Rauter has been exploring artificial voices in her work for years, both as a material and as a phenomenon. Through the constructive urge of the human brain and the (mis)interpretations of AI, poetic moments emerge in her works at the threshold of meaning and noise.

The creative potential of AI lies not in the perfection of imitation, but in the gaps and niches of the system – where space for something new emerges.