Delighted to report that the special issue collection of essays on Artificial General Intelligence that Janna guest edited for the journal Cosmos + Taxis has now been published. Read the open access collection at: https://cosmosandtaxis.org/ct-1256/ and Janna’s editorial at https://cosmosandtaxis.org/wp-content/uploads/2024/05/hastings_ct_vol12_iss5_6.pdf.
Artificial General Intelligence is a topic that is regularly in the news, with the accompanying debates being increasingly relevant as computational systems become better at simulating human performance in a wide range of tasks and modalities and are deployed into more and more aspects of our daily lives.
This collection is motivated by and responds to the book Why Machines Will Never Rule The World: Artificial Intelligence Without Fear, by Barry Smith and Jobst Landgrebe, who argue based on a variety of mathematical and philosophical considerations that genuine intelligence will never be manifested in digital computers. The response essays in this collection engage with, tackle and extend the arguments presented by Landgrebe and Smith, and provide a deep and broad discussion of the current AI era in the context of the quest for AGI.
I hope you will enjoy reading them as much as I did. Thanks to all the contributors, including William Rapaport, Jonathan Simon, Stefan Schulz, Emanuele Martinelli, Ragnar Fjelland, Robert West, Kirill Krinkin, Jana Sedlakova, Maria Hedblom, Jobst Landgrebe, and Barry Smith.
Medical Knowledge and Decision Support
We advance “Medical Knowledge and Decision Support” with data science and artificial intelligence, and qualitatively explore digital transformation in the clinic.
The overarching objectives of the research of the Medical Knowledge and Decision Support group are to implement innovative data science approaches, accelerate discovery, translation and integration of evidence into clinics, and to align technological progress with the needs of clinicians.
Methods
Our research draws methodologically from data science, bioinformatics, computer science, and psychology. We build ontologies and an associated ecosystem for logic-based automation. We apply and develop predictive models using AI/ML, particularly LLMs and neuro-symbolic approaches. We apply mathematical approaches including constraint-based modelling. In addition, we use qualitative approaches to study human perspectives.
Use Cases
We address a wide range of application use cases across our projects, including the discovery and prediction of functions and regulatory factors, biomedical and clinical evidence synthesis and automation, pre-trained large language and multi-modal model evaluation, extraction of data from clinical notes for predictive modelling, decision support, medical question answering, and interpretability and explanations for AI applications.
Clinical Areas
Our projects span a range of biomedical and clinical domains, including fundamental metabolism and metabolomics; drug discovery and molecular property prediction; RNA biology and regulatory interactions; oncology and personalised cancer biology; behavioural science and health psychology; mental health including anxiety, depression and psychosis; ophthalmology; infectious diseases; and physiotherapy.
Contact and Collaboration
If you are interested in partnering with us, have an idea you’d like to discuss, or simply want to get in touch, we would love to hear from you!
Please reach out via email to: janna.hastings@unisg.ch or janna.hastings@uzh.ch
School of Medicine
University of St.Gallen (HSG)
St. Jakob-Strasse 21
9000 St.Gallen, Switzerland
Institut for Implementation Science in Health Care (IfIS)
Universität Zürich
Universitätsstrasse 84
8006 Zürich, Switzerland
Now published: Edited Collection on Artificial General Intelligence
