by Dr. Lance B. Eliot
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Key briefing points about this article:
- The legal element of proximate cause is well-established in our courts and jurisprudence
- A key facet entails the identification of a cause or series of causes leading to an injury
- Some in AI are claiming that Machine Learning might defy proximate cause
- Few buy into that claim, a different claim about multitudes of AI systems is given more merit
- A now-classic legal research paper posits that Distributed AI (DAI) might be problematic
The legal notion of proximate cause comes up repeatedly in law school and serves as a key tool when practicing law. It is hard to imagine the law without also having at hand this keystone of legal constructs. You likely are immersed in proximate cause discussions or legal debates on a daily basis.
All this suggests that it might be handy to periodically take another look at what proximate cause consists of. In addition, we can mull over whether it stands the test of time.
Per the Cornell Law School’s online encyclopedia, proximate cause is defined as “an actual cause that is also legally sufficient to support liability.” Furthermore, there can be multiple actual causes and for which liability is not necessarily exhaustively applicable as to “all the actors responsible for those causes.” And the final kicker is that the reasonableness of referring to something as a proximate cause “increases as the cause becomes more direct and more necessary for the injury to occur.”
That provides a handy foundation for bringing up an ongoing qualm associated with the advent of Artificial Intelligence (AI).
Some are concerned that AI is going to defy the legal norms associated with a proximate cause. In short, AI might just get away with dastardly and untoward acts by finding a loophole in how we legally…