论文标题
为什么我们需要偏见的AI - 包括认知和道德机器偏见在内如何增强AI系统
Why we need biased AI -- How including cognitive and ethical machine biases can enhance AI systems
论文作者
论文摘要
本文强调了在两个方面的人工智能（AI）领域中偏见的重要性。首先，为了在复杂，不稳定和不确定的现实环境中促进有效的算法决策，我们主张在学习算法中的结构上实施人类认知偏见。其次，我们认为，为了实现道德机器行为，必须应用滤波器机制来选择代表社会或行为特征的有偏见的训练刺激，这些刺激在道德上是可取的。我们使用认知科学和伦理学的见解，并将其应用于AI领域，将理论考虑与七个描述有形偏见实施情景的案例研究相结合。最终，本文是明确追求重新评估机器偏见的道德意义的想法的第一步，并提出了将认知偏见实施到机器中的想法。
This paper stresses the importance of biases in the field of artificial intelligence (AI) in two regards. First, in order to foster efficient algorithmic decision-making in complex, unstable, and uncertain real-world environments, we argue for the structurewise implementation of human cognitive biases in learning algorithms. Secondly, we argue that in order to achieve ethical machine behavior, filter mechanisms have to be applied for selecting biased training stimuli that represent social or behavioral traits that are ethically desirable. We use insights from cognitive science as well as ethics and apply them to the AI field, combining theoretical considerations with seven case studies depicting tangible bias implementation scenarios. Ultimately, this paper is the first tentative step to explicitly pursue the idea of a re-evaluation of the ethical significance of machine biases, as well as putting the idea forth to implement cognitive biases into machines.
