Jointly with the Emergency Medical Services Copenhagen, we completed the first part of our trustworthy AI assessment.
A ML sytem is currently used as a supportive tool to recognize cardiac arrest in 112 emergency calls.
A team of multidisciplinary experts used Z-Inspection® and
identified ethical,technical and legal issues in using such AI system.
This confirms some of the ethical concern raised by Kay Firth-Butterfield, back in June 2018….
This is another example of the need to test and verify algorithms,” says Kay Firth-Butterfield, head of Artificial Intelligence and Machine Learning at the World Economic Forum.
“We all want to believe that AI will ‘wave its magic wand’ and help us do better and this sounds as if it is a way of getting AI to do something extremely valuable.
“But,” Firth-Butterfield added, “it still needs to meet the requirements of transparency and accountability and protection of patient privacy. As it is in the EU, it will be caught by GDPR, so it is probably not a problem.” However, the technology raises the fraught issue of accountability, as Firth-Butterfield explains. “Who is liable if the machine gets it wrong? the AI manufacturer, the human being advised by it, the centre using it? This is a much debated question within AI which we need to solve urgently: when do we accept that if the AI is wrong it doesn’t matter because it is significantly better than humans. Does it need to be a 100% better than us or just a little better? At what point is the use, or not using this technology negligent?”
The full report is submitted for publication. Contact me if you are interested to know more. RVZ
Download the Z-Inspection® Process
– “Z-Inspection®: A Process to Assess Ethical AI”
Roberto V. Zicari, John Brodersen, James Brusseau, Boris Düdder, Timo Eichhorn, Todor Ivanov, Georgios Kararigas , Pedro Kringen, Melissa McCullough, Florian Möslein, Karsten Tolle, Jesmin Jahan Tithi, Naveed Mushtaq, Gemma Roig , Norman Stürtz, Irmhild van Halem, Magnus Westerlund.
IEEE Transactions on Technology and Society, 2021
Print ISSN: 2637-6415
Online ISSN: 2637-6415
Digital Object Identifier: 10.1109/TTS.2021.3066209
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