We researched the many shortcomings of the standard voir dire process, which aims to select impartial jurors but often fails to do so. Relying on observation and question-and-answer methods to understand jurors' beliefs and biases is challenging, unreliable, and poses many ethical issues in and of itself. A more objective approach is needed; and the introduction of “scientifically-based” bias assessment tools like lie-detectors and the Implicit Association Test have been shown to be similarly unreliable. Indeed, the consequences for plaintiffs, defendants, and the judicial system are massive.

We therefore explored the potential use of neuroimaging (e.g. functional magnetic resonance imaging) and artificial intelligence algorithms, typically used in the healthcare setting for diagnostic purposes, in the jury selection process – neuro voir-doire. The use of such techniques has demonstrated promising opportunities in detecting both explicit and implicit biases in potential jurors, as well as championing other ethical, legal, and Constitutional ideals. However, employment of such technology is not without practical and ethical concerns of its own, and the certitude of the research is still in native stages.