Conference Program
Chair: Leslie Anne Fendt, Roche, Switzerland
Roche Information Solutions, Switzerland
- driving efficiency and productivity in healthcare systems
- integrating and activating unstructured and disparate data
- enhancing insights and patient outcomes
- empowering patients, carers and healthcare professionals
Dalle Molle Institute for Artificial Intelligence Studies (IDSIA USI-SUPSI), Switzerland
University Hospital Zürich, Switzerland
University of Zurich (UZH), Switzerland
Roche, Switzerland
Roche, Switzerland
Roche, Switzerland
Roche Information Solutions, Switzerland
Dalle Molle Institute for Artificial Intelligence Studies (IDSIA USI-SUPSI), Switzerland
University of Zurich (UZH), Switzerland
Roche Innovation Center Zurich, Switzerland
University of Oslo, Norway
University of Basel, Switzerland
Roche Innovation Center Zurich, Switzerland
University of Applied Sciences and Arts Northwestern Switzerland (FHNW), Switzerland
Proton Mail, Switzerland
University of Oslo, Norway
Novo Nordisk, Denmark
aboutDigitalHealth.com, Germany
In 1966, Joseph Weizenbaum, a computer scientist at MIT, developed ELIZA, one of the earliest chatbots. Despite its primitive technology, patients interacting with ELIZA believed they were talking to an empathetic machine. In reality, ELIZA merely mirrored statements in a manner akin to a psychotherapist, creating the illusion of conversation—a phenomenon later termed the “Eliza effect.” This effect highlights our tendency to anthropomorphize machines, attributing them human features such as intelligence and empathy.
Today, modern generative AI models like ChatGPT exhibit a more sophisticated version of the Eliza effect. Although these models do not “understand” language in the human sense, their ability to analyze and generate text with perfect grammar and context strengthens the illusion of intelligence. With advances in AI, we are now on the brink of interacting with personalized bots capable of booking appointments or even carrying out emotionally expressive conversations.
The question remains: how will this deepening human-machine interaction evolve? As AI increasingly resembles human communication, will we trust these systems as we do family, doctors, or advisors? How far will we extend our trust to machines, even in intimate or specialized roles, such as healthcare? Exploring these questions requires a deeper understanding of psychology and human behavior in response to technology.
University of Basel, Switzerland
Novartis Foundation, Switzerland
Swiss Made Software, Switzerland
Novartis Foundation, Switzerland
StratejAI, Italy
University of Basel, Switzerland
University of Applied Sciences and Arts Northwestern Switzerland (FHNW)
aboutDigitalHealth.com, Germany
University of Basel, Switzerland
This lecture explores the transformative potential of consistently embedding cutting-edge software technologies within an Open Science framework to maximize productivity and actionable outcomes for global health. It starts off by introducing some grand challenges of medical research in the 21st century and how Open Science proposes to address them. As an example, it then highlights how Open Standards facilitate seamless data sharing, collaboration, and reproducibility, breaking down traditional silos in medical research and shifting data analysis paradigms, as outlined in international initiatives such as the Federated European Genome-Phenome Archive (FEGA) and the European Genomic Data Infrastructure (GDI). Finally, it attempts to extrapolate from these developments a vision for an open, federated and standards-based software platform that connects researchers, healthcare practitioners, patients and AI to collectively champion global health challenges.