Law Commons^™

How Can I Tell If My Algorithm Was Reasonable?, Karni A. Chagal-Feferkorn

Michigan Technology Law Review

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 (AI) 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 …

Saliency, Anchors & Frames: A Multicomponent Damages Experiment, Bernard Chao

Michigan Technology Law Review

Modern technology products contain thousands, sometimes hundreds of thousands, of different features. Nonetheless, when electronics manufacturers are sued for patent infringement, these suits typically accuse only one feature, or in more complex suits, a handful of features, of actual patent infringement. But damages verdicts often do not reflect the relatively small contribution an individual patent makes to an infringing product. One study observed that verdicts in these types of cases average 9.98% of the price of the entire product. While both courts and commentators have blamed the law of patent damages, the role cognitive biases play in these outsized damages …