Title Dirbtinis intelektas ir civilinė atsakomybė: medicininės diagnostikos atvejis /
Translation of Title Artificial intelligence and civil liability: the case of medical diagnostics.
Authors Rimkutė, Deimantė
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Pages 73
Abstract [eng] The Master's thesis analyses the possibilities of tort liability for health care institutions and manufacturers when damage to the patient's health (or life) is caused by the use of assistive-diagnostic artificial intelligence software during the provision of personal health care services. The first part of the Master's thesis analyses the legally relevant features of AI assistive-diagnostic software, finding that it raises problems of qualification as a product, problems of establishing the causal link between the manufacturer's liability and the extent to which the standardisation of diagnostic methods and the (mis)classification of AI in these methods will affect the scope of professional duties of doctors. The second part of the paper presents a model of compensation for damage caused to patients' (consumers') health (life), established in Lithuania, whereby tort liability relations would be formed between the patient and (1) the healthcare institution; and (2) the manufacturer of artificial intelligence. The third part analyses the direct and indirect liability of healthcare institutions. It is discussed that direct liability would apply to an institution if it breaches its duties in relation to the organisation of healthcare institutions. Indirect liability would arise if the patient suffers harm as a result of a breach of the doctor's professional duties. Whether or not a doctor has breached his or her duty would depend on whether artificial intelligence is part of the standard of medical science and practice. If it were, the doctor's actions would be judged in the light of the legislation or standards governing medical science and practice which set the guidelines for the use of artificial intelligence. If not, the doctor's actions would be evaluated without taking into account the prognosis of artificial intelligence. The fourth part assesses the manufacturer's liability for a defective product by analysing the most problematic issues. Design defectiveness would be determined by applying the consumer expectation test, i.e. assessing whether, among other things, an alternative design existed at the time the product was launched that could have prevented the harm. Only an indirect causal link could be established between the damage caused and the unlawful conduct.
Dissertation Institution Vilniaus universitetas.
Type Master thesis
Language Lithuanian
Publication date 2022