This paper looks at a common law legal system as a learning algorithm, models specific features of legal proceedings, and asks whether this system learns efficiently. A particular feature of our model is explicitly viewing various aspects of court proceedings as learning algorithms. This viewpoint enables directly pointing out that when the costs of going to court are not commensurate with the benefits of going to court, there is a failure of learning and inaccurate outcomes will persist in cases that settle. Specifically, cases are brought to court at an insufficient rate. On the other hand, when individuals can be compelled or incentivized to bring their cases to court, the system can learn and inaccuracy vanishes over time.

翻译：本文将英美法系视为一种学习算法,以法律诉讼程序的具体特点为模型,并询问这个系统是否有效学习,我们这个模型的一个特征是明确将法院诉讼的各个方面视为学习算法,这种观点可以直接指出,当诉诸法院的费用与诉诸法院的好处不相称时,在解决的案件中将继续存在学习失败和不准确的结果,具体来说,案件以不足的速度提交法院;另一方面,当个人可以被迫或受到激励将其案件提交法院时,系统可以随着时间的推移学习和不准确的消失。