Self-learning algorithms are gradually dominating more and more aspects of our lives. They do so by performing tasks and reaching decisions that were once reserved exclusively for human beings. And not only that-in certain contexts, their decision-making performance is shown to be superior to that of humans. However, as superior as they may be, self-learning algorithms (also referred to as artificial intelligence (AL) systems," smart robots," or" autonomous machines') can still cause damage.

When determining the liability of a human tortfeasor causing damage, the applicable legal framework is generally that of negligence. To be found negligent, the tortfeasor must have acted in a manner not compliant with the standard of" the reasonable person." Given the growing similarity of self-learning algorithms to humans in the nature of decisions they make and the type of damages they may cause (for example, a human driver and a driverless vehicle causing similar car accidents), several scholars have proposed the development of a" reasonable algorithm" standard, to be applied to self-learning systems.