On Automating the Doctrine of Double Effect
On Automating the Doctrine of Double Effect
复制标题
关于双重效应理论的自动化
DOI：
10.24963/ijcai.2017/658
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
S. Bringsjord
中科院分区：
文献类型：
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作者：
Naveen Sundar Govindarajulu;S. Bringsjord
双重效果原则(DDE)是一项长期研究的伦理原则，它规定了何时允许既有积极影响又有消极影响的行动。本文的目标是实现DDE的自动化。我们简要地介绍了DDE，并使用一阶模态逻辑-道义认知事件演算-作为我们的框架来形式化该学说。我们提出了越来越强的原则版本的形式化，包括众所周知的三重效果学说。然后，我们使用我们的框架成功地模拟用于测试该原理在人类受试者中是否存在的场景。我们的框架可以在两种不同的模式下使用：一种可以用来从头开始构建符合DDE的自治系统；另一种可以使用它来验证给定的人工智能系统是否符合DDE，方法是在现有的系统或模型上应用DDE层。对于后一种模式，底层人工智能系统可以使用任何架构(规划器、深度神经网络、贝叶斯网络、知识表示系统或混合架构)来构建；只要系统在其模型中公开一些参数，这种验证就是可能的。在这里，DDE层的角色类似于检查现有软件模块的(动态或静态)软件验证器。最后，我们概述了如何将我们的DDE层应用于STRIPS风格的规划模型和修改后的POMDP模型的初步工作。这是说明第二种模式可行性的初步工作，我们希望我们的初步草图可以对其他研究人员将DDE纳入他们自己的框架中有所帮助。
The doctrine of double effect (DDE) is a long-studied ethical principle that governs when actions that have both positive and negative effects are to be allowed. The goal in this paper is to automate DDE. We briefly present DDE, and use a first-order modal logic, the deontic cognitive event calculus, as our framework to formalize the doctrine. We present formalizations of increasingly stronger versions of the principle, including what is known as the doctrine of triple effect. We then use our framework to successfully simulate scenarios that have been used to test for the presence of the principle in human subjects. Our framework can be used in two different modes: One can use it to build DDE-compliant autonomous systems from scratch; or one can use it to verify that a given AI system is DDE-compliant, by applying a DDE layer on an existing system or model. For the latter mode, the underlying AI system can be built using any architecture (planners, deep neural networks, bayesian networks, knowledge-representation systems, or a hybrid); as long as the system exposes a few parameters in its model, such verification is possible. The role of the DDE layer here is akin to a (dynamic or static) software verifier that examines existing software modules. Finally, we end by sketching initial work on how one can apply our DDE layer to the STRIPS-style planning model, and to a modified POMDP model. This is preliminary work to illustrate the feasibility of the second mode, and we hope that our initial sketches can be useful for other researchers in incorporating DDE in their own frameworks.