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Joint Cognition of Both Human and Machine for Predicting Criminal Punishment in Judicial System

机译:司法系统中人与机器的共同认知预测刑罚

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Thousands of research have been taking place to develop advanced Artificial Intelligence System which can't only perform faster but also predict better than human. But a human has some qualities which can never be gained by a machine like creativity, empathy, sensing, and critical thinking. By aggregating the best sides of both, a novel paradigm for the judicial system can be anticipated. For this purpose, we prepare a dataset both from an online survey (n=103) and interviews conducted in Bangladesh on cases related to `Women and Children Repression Prevention Act, 2000'. We apply several machine learning algorithms to make a machine that can predict punishment like a judge and calculate both the test accuracy and the predictive power of the models to observe which algorithm performs better and stable than the others. Even human can guide machine for judging a delinquent.
机译:已经进行了成千上万的研究来开发先进的人工智能系统,该系统不仅性能更快,而且预测效果比人类更好。但是,人类具​​有某些创造力,而这些创造力是诸如创造力,同理心,感知力和批判性思维之类的机器无法获得的。通过综合两者的最佳方面,可以预见司法系统的新范式。为此,我们准备了在线调查(n = 103)和在孟加拉国针对与“ 2000年妇女和儿童压制预防法”有关的案例进行的访谈,从而准备了一个数据集。我们应用了几种机器学习算法来制造一种可以像法官一样预测惩罚的机器,并计算模型的测试准确性和预测能力,以观察哪种算法比其他算法性能更好且更稳定。甚至人类也可以引导机器判断违法者。

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