Spirituality’ as reconceptualisation of the self: Alan Turing and his pioneering ideas on artificial intelligence

This article investigates the underlying agenda of the philosophy of artificial intelligence (AI) – a discipline of computer science – and proposes a threefold model of ‘spirituality’ as reconceptualisation of the self, composed of one’s search, adaptation and transformation of self-knowledge, specifically concerning the rational humanity. By using the life and ideas of the father of AI and computer science, Alan Turing (1912–1954) as a case study, I will carefully examine his three stages of self-reconceptualisation and highlight the relevance of seeing spirituality as self-reconceptualisation for the current digital age.     

KANT ON RELIGION AND SCIENCE: INDEPENDENCE OR INTEGRATION?

Abstract. Immanuel Kant's theoretical knowledge and practical knowledge tempt conclusion that natural science and religion are two independent discourses of a dualistic system. To be sure, knowledge is anchored in two kinds of causality. Theoretical knowledge is governed by physical causality. Practical knowledge is concerned with the human capacity to initiate a sequence of events that nature could not accomplish on its own—although in conformity with, not independent of, natural causality. Furthermore, the two realms presuppose a common totality of order not of humanity's creation. Without these presuppositions, we could not experience the world as we do, and it would never occur to us to engage in a scientific investigation of the natural world. Hence, we should first exhaust our attempts at explanation on the basis of physical causality before turning to the aid of teleology. The anomalous becomes an occasion to seek a physical law not yet known whereas the miraculous hinders search for a natural law. However, higher than knowledge of “what is” is our capacity to discern “what should be.” This is an inclusive moral capacity that establishes what it means to be human and unites all moral agents in an invisible kingdom of ends that constitutes a moral culture in the physical world uniting religion and science.     

Adaptable Robots

In this essay we consider some of the characteristics of adaptive biological systems and how these might work as models in designing a robot intended for the exploration of complex environments. Trying to design a robot that has such properties forces one to think hard about the nature of those properties. Here we have one intersection between philosophy and computing. We consider the nature of adaptability and some properties of complex biological systems that are relevant to designing adaptive robots, including direct perception, animacy, affordances, redundant degress of freedom, collective decisions, and emergent properties. We explain how these concepts were used in the development of a robotic arm.     

基于人工神经网络的一种效度凭证求取方法

针对基于统计学的效度凭证求取方法所存在的问题,提出了基于人工神经网络的效度凭证求取方法。蒙特卡罗模拟实验和对实际数据的分析表明,当测验分数和效标分数为单变量且非线性关系时,或者测验分数和效标分数为多变量时,运用神经网络方法可以比统计学方法更好地求取心理测验效度的基于和其他变量关系的凭证。     

Getting it right by getting it wrong: When learners change languages

When natural language input contains grammatical forms that are used probabilistically and inconsistently, learners will sometimes reproduce the inconsistencies; but sometimes they will instead regularize the use of these forms, introducing consistency in the language that was not present in the input. In this paper we ask what produces such regularization. We conducted three artificial language experiments, varying the use of determiners in the types of inconsistency with which they are used, and also comparing adult and child learners. In Experiment 1 we presented adult learners with scattered inconsistency - the use of multiple determiners varying in frequency in the same context - and found that adults will reproduce these inconsistencies at low levels of scatter, but at very high levels of scatter will regularize the determiner system, producing the most frequent determiner form almost all the time. In Experiment 2 we showed that this is not merely the result of frequency: when determiners are used with low frequencies but in consistent contexts, adults will learn all of the determiners veridically. In Experiment 3 we compared adult and child learners, finding that children will almost always regularize inconsistent forms, whereas adult learners will only regularize the most complex inconsistencies. Taken together, these results suggest that regularization processes in natural language learning, such as those seen in the acquisition of language from non-native speakers or in the formation of young languages, may depend crucially on the nature of language learning by young children.     

人工神经网络在临床应用中的伦理思考

现代临床医学中的海量信息具有非线性特质,人工神经网络的自我学习、记忆和归纳功能,刚好适应了医学的新发展,在医学领域有良好的应用前景。事实上,人工神经网络临床应用的理论研究成果丰富,但商业应用并不多见。本文探讨人工神经网络在临床应用中可能引发的社会伦理争议,对其临床适用范围进行初步的论述。     

脑电图分析的方法论

临床诊断中的脑电图分析方法可归为两大类：线性分析法与非线性分析法。本文介绍了这两类方法中常用的算法如谱估计、小波分析、混沌分析方法等,分析了这两类方法的特点、优势以及存在的不足。同时讨论了在临床应用中选取这两类方法所出现的问题。提出了将人工势场法用于脑电图分析的新思路,并对研究方案进行了可行性分析。     

Consistency Defaults

A consistency default is a propositional inference rule that asserts the consistency of a formula in its consequence. Consistency defaults allow for a straightforward encoding of domains in which it is explicitely known when something is possible. The logic of consistency defaults can be seen as a variant of cumulative default logic or as a generalization of justified default logic; it is also able to simulate Reiter default logic in the seminormal case. A semantical characterization of consistency defaults in terms of processes and in terms of a fixpoint equation is given, as well as a normal form. Presented by Melvin Fitting