healthcare, medical malpractice, civil liability, “no-fault, ” strict liability, guidelines, artificial intelligence, robots
The traditional deterrence-based paradigm of civil liability may be understood as indirect market regulation, as the risk of incurring liability for damages provides an incentive to invest in safety. Such an approach, however, has proven to be inappropriate in medical civil liability. Extensive literature shows that the increase in the asymmetric protection of patients by extending medical civil liability beyond a certain limit does not improve safety; instead, that strategy determines the adoption of “defensive” techniques (the so-called “defensive medicine”). Paradoxically, this approach leads to a reduction in market efficiency and overall patient safety. The traditional paradigm of medical civil liability, moreover, is very likely to prevent the intensive use of artificial intelligence and robotization to further develop the healthcare landscape. In fact, under the current paradigm of civil liability, redress is allowed only insofar “somebody” is identified as liable to pay damages (either because of fault or based on strict liability). However, robots and software may “behave” far independently from instructions initially provided by designers and programmers. This possibility may rep-resent a disincentive to new AI technologies, as in this model de-signers and programmers could be held liable even if the damage derives from the “correct” operation of algorithms and robots. This article proposes that the law of redress in healthcare should evolve from an issue of civil liability to one of financial management of losses. No-fault redress schemes could be an interesting and valuable regulatory strategy in order to allow such an evolution. Also, some pieces of “no fault” legislation are discussed, and a few proposals and comments are provided.
Medical Civil Liability Without Deterrence: Preliminary Remarks for Future Research,
13 J. Civ. L. Stud.
Available at: https://digitalcommons.law.lsu.edu/jcls/vol13/iss1/4