Is Default Logic a Reinvention of Inductive-Statistical Reasoning?

Currently there is hardly any connection between philosophy of science and Artificial Intelligence research. We argue that both fields can benefit from each other. As an example of this mutual benefit we discuss the relation between Inductive-Statistical Reasoning and Default Logic. One of the main topics in AI research is the study of common-sense reasoning with incomplete information. Default logic is especially developed to formalise this type of reasoning. We show that there is a striking resemblance between inductive-statistical reasoning and default logic. A central theme in the logical positivist study of inductive-statistical reasoning such as Hempels Criterion of Maximal Specificity turns out to be equally important in default logic. We also discuss to what extent the relevance of the results of Logical Positivism to AI research could contribute to a reevaluation of Logical Positivism in general.     

Designing for Trust: A Case of Value-Sensitive Design

In this paper, we consider the meaning, roles, and uses of trust in the economic and public domain, focusing on the task of designing systems for trust in information technology. We analyze this task by means of a survey of what trust means in the economic and public domain, using the model proposed by Lewicki and Bunker, and using the emerging paradigm of value-sensitive design. We explore the difficulties developers face when designing information technology for trust and show how our analysis in conjunction with existing engineering design methods provides means to address these difficulties. Our main case concerns a concrete problem in the economic domain, namely the transfer of control from customs agencies to companies. Control of individual items is increasingly untenable and is replaced by control on the level of companies aimed at determining whether companies can be trusted to be in control of their business and to be in compliance with applicable regulations. This transfer sets the task for companies to establish this trust by means of information technology systems. We argue that this trust can be achieved by taking into account philosophical analyses of trust and by including both parties in the trust relationship as clients for whom the information technology systems are to be designed.     

基于面孔的印象形成:神经科学的视角

印象形成过程是心理学的经典研究主题,最近随着神经科学的兴起和脑成像技术的成熟,研究者开始从神经科学的角度审视人类的印象形成过程.印象形成主要基于三种信息,即面孔知觉,直接互动和二手信息.就面孔而言,基于面孔的印象形成更为快速和准确,其中杏仁核在其中起着重要的作用;作为对照,文章简要介绍了基于二手信息和直接互动的印象形成,它们更多涉及深思熟虑的任务,激活内侧前额皮层和颞上沟后端.印象形成的神经机制,线索之间的关系、印象形成的影响伴随着新技术的运用将会得到研究者的关注.     

情感预测偏差的相关研究评述

情感预测是预测将来的情绪状态。情感预测时会表现出各种偏差, 例如免疫性忽略、聚焦错觉和共情鸿沟。本文从认知–体验自我理论和心理模拟的角度对情感预测偏差的原因进行了整合, 对情感预测偏差的个体差异和矫正进行了分析。情感预测的未来研究方向应该从心理-行为机制、进化机制和脑机制几个方面展开。     

自我观的新形式:有关自悯的研究论述

由于自尊并不能完全地预见个体心理健康的程度,许多研究者提出了新的构念。本文介绍了其中的努力之一,在吸收东方佛学思想的基础上,Neff于2003年提出了自悯这种新的自我观形式。文章介绍了自悯的成分,即自我友善、普遍人性感和正念以及相关的研究方法;然后,从早期经验、社会文化的角度讨论了自悯的影响来源;在心理功能方面,自悯能有效地帮助个体应对负性事件,增强积极的心理品质和力量,对人际知觉和互动也有重要影响。自悯的这些积极功能已经在临床上得到了运用。最后,对未来的研究方向进行了展望。