Assessing Trustworthy AI. Best Practice: AI Medical device for Predicting Cardiovascular Risks

We have used Z-Inspection® to evaluate a non invasive AI medical device which was implemented to assist medical doctors in the diagnosis of cardiovascular diseases.

  Assessment Completed.

Learn more.

Assessing Trustworthy AI. Best Practice: Machine learning as a supportive tool to recognize cardiac arrest in 112 emergency calls for the City of Copenhagen.

Jointly with the Emergency Medical Services Copenhagen, we completed the first part of our trustworthy AI assessment.

We use an holistic approach

“Ethical impact evaluation involves evaluating the ethical impact of a technology’s use, not just on its users, but often, also on those indirectly affected, such as their friends and families, communities, society as a whole, and the planet.“

–Peters et al.

Co-design of Trustworthy AI. Best Practice: Deep Learning based Skin Lesion Classifier.

We used Z-Inspection® as an ethically aligned co-design methodology and helped ML engineers to ensure a trustworthiness early design of an artificial intelligence (AI) system component for healthcare.

In cooperation with

German Research Center for Artificial Intelligence GmbH (DFKI)

Assessing Trustworthy AI in times of COVID-19: Deep Learning for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients.

We conducted a self assessment together with the

Department of Information Engineering and Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health – University of Brescia, Brescia, Italy 

Lessons Learned in Performing a Trustworthy AI and Fundamental Rights Assessment

This report shares the experiences, results and lessons learned in conducting a pilot project ‘Responsible use of AI’ in cooperation with the Province of Friesland, Rijks ICT Gilde-part of the Ministry of the Interior and Kingdom Relations (BZK) (both in The Netherlands) and a group of members of the Z-Inspection® Initiative. The pilot project took place from May 2022 through January 2023. During the pilot, the practical application of a deep learning algorithm from the province of Frŷslan was assessed.

The AI maps heathland grassland by means of satellite images for monitoring nature reserves. Environmental monitoring is one of the crucial activities carried on by society for several purposes ranging from maintaining standards on drinkable water to quantifying the CO2 emissions of a particular state or region. Using satellite imagery and machine learning to support decisions is becoming an important part of environmental monitoring.

The main focus of this report is to share the experiences, results and lessons learned from performing both a Trustworthy AI assessment using the Z-Inspection® process and the EU framework for Trustworthy AI, and combining it with a Fundamental Rights assessment using the Fundamental Rights and Algorithms Impact Assessment (FRAIA) as recommended by the Dutch government for the use of AI algorithms by the Dutch public authorities.


arXiv:2404.14366
[cs.CY]