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The Respective Roles of Intellectual Creativity and Automation in Representing Diversity: Human and Machine Generated Bias

机译:知识创造力和自动化在代表多样性中的各自作用:人为和机器产生的偏见

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The paper traces the development of the discussion around ethical issues in artificial intelligence, and considers the way in which humans have affected the knowledge bases used in machine learning. The phenomenon of bias or discrimination in machine ethics is seen as inherited from humans, either through the use of biased data or through the semantics inherent in intellectually-built tools sourced by intelligent agents. The kind of biases observed in AI are compared with those identified in the field of knowledge organization, using religious adherents as an example of a community potentially marginalized by bias. A practical demonstration is given of apparent religious prejudice inherited from source material in a large database deployed widely in computational linguistics and automatic indexing. Methods to address the problem of bias are discussed, including the modelling of the moral process on neuroscientific understanding of brain function. The question is posed whether it is possible to model religious belief in a similar way, so that robots of the future may have both an ethical and a religious sense and themselves address the problem of prejudice.
机译:本文追踪了围绕人工智能中的伦理问题的讨论的发展,并探讨了人类如何影响机器学习中使用的知识库。机器伦理中的偏见或歧视现象被视为是人类继承的,或者是通过使用偏见的数据,或者是由智能代理提供的以智能方式构建的工具所固有的语义。将人工智能中观察到的偏见类型与知识组织领域中发现的偏见类型进行比较,以宗教信徒为例,该群体可能会因偏见而被边缘化。实际演示了明显的宗教偏见,这些偏见源于广泛部署在计算语言学和自动索引中的大型数据库中的原始资料。讨论了解决偏​​倚问题的方法,包括对神经功能的神经科学理解进行道德过程建模。提出的问题是,是否有可能以类似的方式对宗教信仰进行建模,从而使未来的机器人可能既具有伦理意义又具有宗教意义,并且自己解决偏见问题。

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