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 Chapter’s Workshop on Societal Security Informatics in 2006, China’s 299^th Xiang Shan Scientific Conference on Social Computing in April 2007 (Figure 1), Harvard’s 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 Beijing’s 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 Kurzweil’s “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. Good’s “intelligence explosion”. To this end, our R&D 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 child’s 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 Merton’s self-fulfilling prophecy, might be used as governing laws for social dynamic systems, similar to governing laws, like Newton’s laws, for natural or physical processes. For example, in social-technological areas, Moore’s Law has been quite helpful in facilitating business planning and product development for semiconductor related industries. Other eponymous laws, such as Metcalfe’s, Reed’s, Sarnoff’s 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, let’s delve even further into the teachings of philosophers 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 Merton’s laws in scientific computing.

 

If you have little confidence in Russell’s idea, Popper’s 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 Popper’s 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 haven’t 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 Carley’s 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, it’s 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.

Back to my original question: Is culture computable? My answer for now is, let’s 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

 

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