Lectures and seminars Networking meeting between the Wallenberg programs Data-driven Life Science (DDLS) and WASP-HS

08-06-2022 10:00 am - 4:00 pm Add to iCal
Campus Solna Air&Fire, SciLifeLab Solna

The purpose of the meeting is to explore opportunities for joint and multidisciplinary research ventures between researchers working within data-driven life science and researchers from the humanities and social sciences working on Artificial Intelligence and Autonomous Systems. Information regarding an upcoming call for seed-money for cross-program research collaborations will also be announced at the meeting. Apart from thematic parallel networking sessions, the program will include a study vi


Theme descriptions DDLS/WASP-HS networking meeting

A. Data Challenges

This theme centers around the ethical, organizational, and social challenges around data work. Questions could include for instance: What are the challenges in creating representative datasets for diverse populations? In making data travel between project or countries. Or when old historical data are used to model contemporary phenomena? How do the categories of databases shape the collection of life science data?

B. Implementation and Use

This theme centers on the ethical, organizational, and social challenges around implementation and use. Questions could include for instance: How can the generated medical knowledge be implemented in medical education and clinical practice? What are the legal and ethical implications thereof? How can a patient-centered, holistic perspective on a patient’s health situation be maintained (balancing data-driven bio-centric assessments with clinical findings)?How can the computational instruments explain their grounds for output (classification, assessment, diagnosis, or prediction) to a clinician or patient?

C. Prediction and Modeling

This theme centers on the ethical, organizational, and social challenges around prediction and modeling. Questions could include for instance: What are the ethical and social issues in modelling and forecasting.What are the challenges for model reuse from different domains? What are the challenges of using ”ground truth datasets” to assess model fit for real data cases. 

D. Governance and Economics

This theme centers on the legal, organizational, and governance challenges around data-driven life science. Questions could include for instance: Legal aspects of data (use, reuse, transfer, sharing etc) What is/could be/should be the big picture (non-technical) model of data governance at DDLS? What are the fundamental assumptions, expectations and procedures accepted by stakeholders?