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文化能计算吗?
热度 1 王飞跃 2009-12-7 10:36
非常高兴地看到专刊《人工智能与文化遗产》的顺利完成,感谢各位客座编辑的辛勤努力和工作。专刊总结了这一领域的最新研究成果,十分有意义。显然,在保存、加强、宣传我们的文化遗产方面,人工智能已经发挥并将继续发挥极其重要的作用。 借此机会,我想讨论一个相关的问题:文化计算或社会计算。 当前,各类各样的社会或文化问题都迫切需要有效的计算方法,社会计算和文化计算这一新兴领域也就应运而生。从国土社会安全到世界金融危机,人工智能应当也必须在解决这类新兴计算问题中发挥重要的作用。 然而,文化或社会真的能计算吗?对此,我没有确定的答案,因为这完全取决于我们对在什么意义下?这一问题的回答。在很大意义下,我相信只要我们能够解决如何利用常识进行推理或计算的问题,我们就应当能够有效地进行文化或社会计算。但是,常识无法指望,因为这一问题依然还是人工智能领域里最具挑战性最难啃的硬骨头之一。 尽管对最基本的可计算性还不清楚,但我们必须立即开展这项工作,因为我们已到了无法避免文化社会计算的时刻。在过去的三年里,作为在人工智能领域里号称第一号的杂志,《 IEEE 智能系统》在宣传这一新兴领域的工作中起了先导作用,已经刊登了几篇重要的文章并组织了一次社会计算的专刊。在世界范围内,几项类似的活动业已展开。例如: ACM (国际计算机协会)北京分会于 2006 年召开的社会安全信息学研讨会, 2007 年四月举行中国关于社会计算的第 299 次科学会议,哈佛大学 2007 年 12 月举行的社会计算社会科学研讨会,国际社会计算大会( SoSo 2008, 与 IEEE 系统、人和控制国际大会同时举行),中国科协新观点新学说社会计算沙龙等等。从去年 5 月,美国科学促进会的《科学》杂志至少发表了四篇与社会和文化计算直接相关的论文,非常高兴地看到其中一些文章是基于我们杂志上已发表的工作而完成的。 这些工作能给我们带来对社会和文化计算坚实科学基础的希望还是欺望?我既乐观也有信心,相信这可能是一个新的计算时代的开始:在一个联通世界里信息技术与社会科学将被无缝一致地整合在一起。 当然,这离未来学专家 Kurzweil 的奇点差得还很远(奇点是指人类脑智可用我们构造的技术来量度时候,有些人声称,不管是好是坏,在奇点处,机器智能将超过人类智能),但是我的确希望社会和文化计算的最终成功能把我们带进统计学家 Good 所预言的智力爆炸时代。为了实现这一目标,在社会与文化计算的研发中,我们必须考虑并使用其它相关新兴领域的概念与方法。 计算思维 在其发表于 2007 年 ACM 会刊 CACM 的文章里,计算机科学家周以真宣称计算思维代表着一种普遍的认识和一类普适的技能,每一个人,不仅仅是计算机科学家,都应热心于它的学习和运用。和在阅读、写作和算术(英文简称 3R )之外,我们应当将计算思维加到每个孩子的解析能力之中。一旦这一目标变成现实,或至少在社会和文化研究者中成为现实的话,那么,一个扎扎实实的社会和文化计算领域将产生,并被大家到处采用。当然,我理解这必须是一个需要极大努力的长期项目,但计算思维的概念可以为社会和文化计算的研究和教育带来即刻的帮助和长期的益处。 利用计算思维,社会科学和文化研究中的表述性假设和过程就能变成可以量化分析的计算步骤。更进一步,各种各样的社会定律的衍生物,比如莫顿的自我实现预言,就能被用来做为社会动力系统的主导定律,就像牛顿定律在自然或物理过程中那样。例如,在社会技术领域,莫尔定律在半导体行业的商业规划和产品研发上就发挥了十分有益的作用。其它齐名的定律,如 Metcalfe 定律, Reed 定律, Sarnoff 定律等等,也可能对社会计算和文化建模十分有价值。 罗素和波尔普的思想 如果你觉得社会学家莫顿离科学计算太远,那我们再走远一点,到哲学家罗素和波尔普那里去感受一下。 在 80 多年前的一次著名讲座《为什么我不是一个基督徒?》中,罗素声称非常多我们认为是自然定律的东西其实是人们的约定,你所导出的定律是一类可以随机出现的统计平均,并且,整个的定律意味着规律制定者的想法是由于自然与人类定律的混淆造成的。对很多人而言,他的这一断言和分析使得整个自然定律不再像过去那样令人神圣了。作为结果,我也希望这将有助于使在科学计算中应用广义的莫顿定律有理化。 如果你对罗素的想法不放心,你或许可以在波尔普关于现实的理论中得到帮助。这一观点包含三个互动的世界,分别是代表物理世界的世界 1 ,心理世界的世界 2 和人类脑力产物之人工世界的世界 3 。世界 3 是抽象体的大本营,包括理论、故事、神话、工具、社会组织、艺术、产生科学理论并使它们能够被批评和证伪的客观知识。因此,世界 3 为社会和文化计算提供了一个营养环境。人工生命和人工社会等新的建模方法的出现也证实了波尔普理论的有用性。例如,利用人工社会进行建模,社会科学中许多困难的技术问题,如不可观察非均性的反事实效应和识别问题中因果关系等,就很容易地被讨论。 文化学习和社会学习 不管是在计算上还是哲学上,我们都不能只想不做,我们需要更多的真正行动。从提倡人工社会建模、计算实验分析、平行执行决策和决策支持的 ACP 机制,到社会文化分析中的文化推理结构,已有许多方法被提出来了。然而,机器学习和数据挖掘在社会文化计算中的潜力还没有被充分且系统地考察过。 十多年来,机器学习已变革了统计学。目前,统计学招聘计算机专业,计算机系设立统计项目已成平常之事。机器学习在统计学习中的成功使我们看到了社会学习和文化学习也是社会计算和文化建模的一个很有前景的方向。利用机器学习,我们可以用统一的方式来进行文化和社会问题的分析,从个体条件和行为,社会活动和过程,到组织状态和行为,进而从个体分类到社会分层,最终到社会组织的各种功能。而且,一旦能将社会和文化学习结合或嵌入到人工社会或 Carley 的计算组织的构建之中,学习就可以具有更大的效力。 几年之前,我曾与几位编委讨论过是选择社会计算还是社会学习作为我们杂志的专刊题目,最终,我们选择了社会计算,并于 2007 年出了专刊。我非常高兴的通知大家,为了继续我们的努力,智能系统杂志将于 2010 年组织关于社会学习的专刊, 计算文化 对我而言,文化体现于个人与群体和环境的交互方式之中,因此是一种在特定历史、自然和社会条件下形成的生产方式。无论我们能通过社会和文化计算取得什么,文化不是也将不会成为科学。然而,随着信息技术的加速发展,我们可能在不久的未来就进入计算文化的时代,那时,具有计算思维的数字土著者已成为普遍的公民。在许多方面,过去的十年中我们已目睹了这一时代的一些生活方式和它们对我们社会的冲击。 计算文化的建立取决于计算思维在我们每一根社会纤维上的扩散。我相信,正如周以真所指出的那样,如同印刷普及了阅读,写作和算数,计算和计算机也将极大地普及计算思维。在我们迈向一个真正联通世界的过程中,社会和文化计算技术的新发展和有效应用将极大地加强这一普及过程的速度和规模。 其实,我们很可能将被强迫地进入计算文化的时代,否则,科技新发展史无前例的速度和规模会使我们面临危险。从语义网、万维科学到我们上一期关于语义科学知识集成的专刊,智能系统杂志已为提倡面向这一新数字时代的新研究、发展和应用做出了杰出的贡献,我们是并还将是这方面工作的主导力量。 回到我最初的问题 : 文化能计算吗?我的回答是,就目前而言,让我们先把精力聚焦在社会和文化计算眼下的工作和可能后果之上吧。
个人分类: 往事如云|13157 次阅读|10 个评论
文化能计算吗?
王飞跃 2009-5-5 09:31
A Letter from the Editor Is Culture Computable? Fei-Yue Wang I enjoyed reading the articles in this special issue on AI Cultural Heritage , thanks to the great effort of our guest editors. The issue summaries the state of the art in this area with interesting and successful results. Clearly, AI has played and will continue to play a vital role in preserving, enhancing, and presenting our cultural heritage. Here I would like to discuss a related topic: the emerging field of social and cultural computing, which is a natural extension of the research work described in this issue. The demand is urgent for effective computing methods to deal with various social and cultural problems such as homeland security and the world financial crisis. AI should and must play the key role in addressing these issues. However, this begs the question, is culture really computable? At this point, I have no definitive answer; it all depends on the answer to the follow-up question, In what sense? To a large degree, I believe that if we can solve the problem of reasoning or computing with common senses, then we should be able to conduct culture or social computing effectively. But common senses is currently out of question because the topic itself still reminds one of the most difficulty challenges in AI research. Although the answer to the fundamental computability of culture is not clear, we must forge ahead because we simply cannot afford the consequence of avoiding cultural computing now. Over the past three years, our magazine has been leading the effort in promoting this new field by publishing important articles and dedicating a related special issue to this emerging field. Many similar activities have been launched recently around the world, for examples, ACM Beijing Chapters Workshop on Societal Security Informatics in 2006, Chinas 299 th Xiang Shan Scientific Conference on Social Computing in April 2007 (Figure 1), Harvards Workshop on Computational Social Sciences in December 2007, International Conference on Social Computing (SoCo 2008) (in conjunction with the 2008 IEEE Conference on Systems, Man, and Cybernetics), and Beijings Seminar on Social Computing, a regular academic salon series for open scientific discussion funded by the Chinese Association of Science and Technology (Figure 2). Since last May, AAAS Science has also published at least four articles directly related to social and cultural computing, and I am glad to see that some articles are based on research reported earlier in Intelligent Systems . Will those activities bring us hope or hype towards a solid scientific foundation for social and cultural computing? I am hopeful and optimistic, and believe this could be the beginning of a new era in computing that would seamlessly integrate information technology with social sciences in a connected world. Of course, this is far from futurist Ray Kurzweils singularity, the point where the functionality of the human brain is quantifiable in terms of technology that we can build (some also claim that, at the singularity, machine intelligence will surpass our human intelligence, for good or bad), but I do hope the final success of social and cultural computing will bring us close to statistician I. J. Goods intelligence explosion . To this end, our RD effort for social or cultural computing must incorporate concepts and methods from several other related emerging areas. Computational Thinking Computer scientist Jeannette M. Wing, in her essay Computational Thinking published in the Communication of ACM , argued that computational thinking represents a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use. She also advocated that to reading, writing, and arithmetic, we should add computational thinking to every childs analytical ability. When this vision becomes realty, or at least a reality among social and cultural researchers, then a solid discipline of social and cultural computing will be created and utilized everywhere and by everyone. This will require a long term project of tremendous effort, but the concept of computational thinking could bring both instant help and long term benefit to research and education of social and cultural computing. With computational thinking, descriptive hypotheses and processes in social sciences and cultural studies can be reformulated into computational procedures for quantitative analysis. Furthermore, various derivatives of social laws, such as Mertons self-fulfilling prophecy , might be used as governing laws for social dynamic systems, similar to governing laws, like Newtons laws, for natural or physical processes. For example, in social-technological areas, Moores Law has been quite helpful in facilitating business planning and product development for semiconductor related industries. Other eponymous laws, such as Metcalfes, Reeds, Sarnoffs laws, might also be valuable for social computing and cultural modeling. Russell and Popper If you think sociologist Merton is too ambiguous for scientific computing, lets delve even further into the teachings of philosopher s Bertrand Russell and Karp Popper. In his famous lecture Why I Am Not A Christian , delivered more than 80 years ago in London, Russell stated that a great many things we thought were natural laws are really human conventions, the laws at which you arrive are statistical averages of just the sort that would emerge from chance, and the whole idea that natural laws imply a lawgiver is due to a confusion between natural and human laws. For many, his statements and arguments made this whole business of natural law much less impressive than it formerly was, as a result, I hope it has also justified the use of generalized Mertons laws in scientific computing. If you have little confidence in Russells idea, Poppers theory of reality may help you. His model of the universe includes three interacting worlds: World 1 the physical world, World 2 the mental world, and World 3 the artificial world of products from the human mind . World 3 is home to abstract objects such as theories , stories , myths , tools , social institutions , and works of art . It contains the objective knowledge upon which all scientific theories are formed, which enables them to be criticized and potentially falsified . Therefore, World 3 provides a nurturing environment for social and cultural computing. The emergence of new modeling and analysis methods using artificial life and artificial societies testify to the usefulness of Poppers theory. For example, by modeling with artificial societies, many difficult technical issues in social sciences, such as the counterfactual effects in unobserved heterogeneity and the causes of effects in identification problems, can be easily addressed. Cultural Learning and Social Learning Computationally or philosophically, we cannot just thinking, we need real and more actions. From my ACP-based mechanism that promotes modeling with artificial societies, analysis by computational experiments, decision support and making through parallel execution, to the Cultural Reasoning Architecture for socio-cultural analysis, many approaches have been proposed so far. However, we still havent fully and systematically investigated machine learning and data mining techniques for social and cultural computing. For more than a decade, machine learning has transformed statistics. It is now a common practice for statistics departments to hire computer scientists and computer science departments to embrace statistics programs. The success of machine learning in statistical learning suggests that social learning and cultural learning are also promising directions for social computing and cultural modeling. After all, statistics is the most important tool of modeling and analysis in social sciences and cultural studies. With machine learning, we can proceed in a unified fashion for analysis of social and cultural issues, from individual conditions and behaviors, social activities and processes, to organizational states and behaviors, that is, from individual clustering to social stratification, and eventually to various functionalities of social organizations. Social and cultural learning would be even more powerful if it is combined with or embedded in construction of artificial societies, as well as Kathleen Carleys computational organization theory. A few years ago, I had discussed with some our Associate Editors about the choice between social computing and social learning for a special issue in IS , we ended up with a social computing issue in 2007. I am glad to inform you that, to continue our effort, we have already scheduled another special issue on social and cultural learning in 2010. Computational Culture To me, culture is embodied in how people interact with other individuals and with their environment. Therefore, its a way of life formed under specific historical, natural, and social conditions. Culture is not and will not be a science, no matter what we can accomplish with social and cultural computing. However, with the accelerated advancement of IT technology, we may arrive at an age of computational cultures in the near future, where digital natives with computational thinking are ordinary citizens. In many aspects, we have already witnessed new computer-based lifestyles and their impact on our society during the past decade. The establishment of a computational culture depends on the spread of computational thinking thoughout every fabric of our society. I believe, as Wing pointed out, just as the printing press facilitated the spread of the three Rs, computing and computers will greatly facilitate the spread of computational thinking. As we are entering a truly connected world, the speed and scale of this spreading process can be greatly enhanced through new developments and effective applications of social and cultural computing techniques. In many senses, we will be forced to enter the age of computational culture because survivability and sustainability might otherwise be at risk, owing to the unprecedented speed and scale of social changes caused by new scientific and technologic developments. From semantic web to web science to our last special issue on semantic scientific knowledge integration, IS has significantly contributed to promoting new research, development, and application towards this new digital age, and we will continue to be a leading force in this endeavor. B ack to my original question: Is culture computable ? My answer for now is, lets focus on the current tasks and potential consequence of social and cultural computing. Figure 1. Fei-Yue Wang co-organized and chaired the 299 th Xiangshan Scientific Conference on Social Computing at Fragrance Mountain, Beijing, China, in 2007. Figure 2. A discussion at the CAST Seminar on Social Computing at KuanGou, Beijing, China in 2008
个人分类: 往事如云|10409 次阅读|7 个评论

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