CE, digital passports and liability issues
status: Published online
Liability for harm caused by AI in healthcare: an overview of the core legal concepts
Published in Frontiers in Pharmacology
Medical malpractice liability in large language model artificial intelligence: legal review and policy recommendations
Published in Journal of Osteopathic Medicine
The emergence of generative large language model (LLM) artificial intelligence (AI) represents one of the most profound developments in healthcare in decades, with the potential to create revolutionary and seismic changes in the practice of medicine as we know it. However, significant concerns have arisen over questions of liability for bad outcome...
One, Two, Three… Fault? CJEU Rules on Civil Liability Requirements under the GDPR
https://conflictoflaws.net/2024/one-two-three-fault-cjeu-rules-on-civil-liability-requirements-under-the-gdpr/
La «adaptación» del derecho de daños a la inteligencia artificial: la propuesta de Directiva sobre responsabilidad
L’imparable avanç de la intel·ligència artificial i els potencials beneficis que genera són fets inqüestionables. No obstant això, també planteja importants reptes, per la qual cosa les institucions europees han mostrat especial interès a disposar d’una regulació adequada. En aquest sentit, apareixen dues realitats que, a vegades, semblen enfrontad...
Liability for harm caused by AI in healthcare: an overview of the core legal concepts
Published in Frontiers in Pharmacology
The integration of artificial intelligence (AI) into healthcare in Africa presents transformative opportunities but also raises profound legal challenges, especially concerning liability. As AI becomes more autonomous, determining who or what is responsible when things go wrong becomes ambiguous. This article aims to review the legal concepts relev...
Safer not to know? Shaping liability law and policy to incentivize adoption of predictive AI technologies in the food sy...
Published in Frontiers in Artificial Intelligence
Governments, researchers, and developers emphasize creating “trustworthy AI,” defined as AI that prevents bias, ensures data privacy, and generates reliable results that perform as expected. However, in some cases problems arise not when AI is not trustworthy, technologically, but when it is. This article focuses on such problems in the food system...
Assortative mating and parental genetic relatedness contribute to the pathogenicity of variably expressive variants.
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Published in American journal of human genetics
We examined more than 97,000 families from four neurodevelopmental disease cohorts and the UK Biobank to identify phenotypic and genetic patterns in parents contributing to neurodevelopmental disease risk in children. We identified within- and cross-disorder correlations between six phenotypes in parents and children, such as obsessive-compulsive d...
What's trust got to do with research: why not accountability?
Published in Frontiers in Research Metrics and Analytics
This paper explores the intricate dynamics of trust, power, and vulnerability in the relationship between researchers and study participants/communities in the field of bioethics. The power and knowledge imbalances between researchers and participants create a structural vulnerability for the latter. While trust-building is important between resear...
A guided framework for assessing off-label medication use in psychiatry.
Published in Australasian psychiatry : bulletin of Royal Australian and New Zealand College of Psychiatrists
The objective of this article is to present a decision aid in the form of a flowchart, designed to assist psychiatrists in navigating the challenges of off-label medication use. This tool is believed to be the only one currently available that combines guidance from medical indemnity insurers, RANZCP guidelines, CATG frameworks, and relevant legisl...
