This post is a revision of a post on the science of information that I wrote on October 23, 2008. The earlier post, which makes up the last part of this post starting with the paragraph that begins "In 1969, Herb Simon…" was done in a rush and ended up providing a grossly inadequate response to the topic. I have added some material to overcome the inadequacy of the discussion, at least as I see it. This post now replaces the earlier post which has been removed.
In 1979, as a part of my dissertation work, I struggled with the question of what constituted a profession. As a part of that work, I asked the question of how professions differed from disciplines, which include the sciences. That led me to a 1966 book by King and Brownell (King, A.R. and Brownell, J.A. The Curriculum and the Disciplines of Knowledge: A Theory of Curriculum Practice. New York: John Wiley and Sons, 1966.) In their treatise, they lay out and discuss the characteristics of a discipline. These include obvious characteristics -- e.g. it is a community of persons, and expression of human imagination, a tradition; derivative characteristics -- e.g. there is a specialized language, it is an "instructive community", it has a literature, etc.; and what I consider the fundamental characteristics -- it has a domain of inquiry, a mode of inquiry, and a conceptual structure. While I would bow to my colleagues in History and Philosophy of Science who I suspect have much better models, King and Brownell provide a simple framework that makes sense to me. The three characteristics I call fundamental is where I focus this discussion. (Although I must admit that it is fun to ask how the Science of Information defines a "valuative and affective stance.") Let me address the domain, conceptual structure, and method of inquiry for a science of information.
It is pretty clear that the domain of physics is the physical universe, the domain of biology is living organisms, the domain of literature is writings, etc. At gross levels, these domains are difficult to constrain, but as we talk about astrophysics, or vertebrate biology, the domains seem to become a little more sharply defined. Sometimes, they get fuzzier -- e.g. molecular biology, or social psychology, but let us avoid that confusion and simply ask what the domain of information science might be? I am not very happy when the discussion turns to everything being information and leads information science to have a domain which includes all the other disciplines. The disciplines get more clear as they get more focused, or as we shall see below, the conceptual structure gets more clear and universal. I am also not happy when we suggest that we don't need to define or circumscribe the definition of information to have a science of it. I would suggest that lacking a reasonable definition of living organisms would make it very difficult to define what biology is all about. A related issue here has to do with outliers. While you and I would have no trouble agreeing that a vertebrate or a plant is a living organism, there are surely some fungi and other fringe entities that lack one or more of the attributes we use to define living organisms. We can argue about these, but Biology began by demarcating the 99% of the domain we agree is living organisms. (Actually, I don’t think anyone knew about the special cases until much later in time.) When it comes to information, it seems we only want to argue about the fringe of the domain and ignore the 99% that is at the core. So what is the domain of information science. I would say that it is the messages exchanged between humans that change the state of what the receiving human "knows" -- another definitional problem, but we will get to it in a future post. The interested reader should see my earlier posting -- September 25, 2008 on a definition of information.
Ok, we are coming to grips with what we want to study. What is the conceptual structure we overlay on the phenomenon? In physics, we have had a number of conceptual models of the physical world, at both microscopic and macroscopic levels. Newtonian mechanics worked for a long time. Quantum mechanics takes another view, not necessarily contradictory, but in some arenas of matter, more explanatory. I will be careful not to anger my colleagues in Physics by exposing any more of my ignorance of the subtleties of the conceptual domain. Suffice it to say for my purposes here, that in the Newtonian conceptual structure we find concepts like force = mass * acceleration. This concept is not a part of the domain of inquiry, it is a part of the conceptual structure that is overlaid to explain something about the domain. So, what is the conceptual structure of the science of information? Some might suggest that it is Claude Shannon's conceptualization of information as the log of the sum of the inverse of the probabilities of the components of the message. I would suggest this is a good start -- we have seen our Newton but are still awaiting Einstein. Moreover, while force is one small part of physics that was conceptualized, Shannon's measure of the amount of information in a communications channel is yet a smaller component of the conceptual framework that needs to be defined for a science of information. Would that I could share with you a comprehensive conceptual structure for information, or better yet a grand unified theory. Sometimes, I sense that I see something, but all too often what seemed so clear in a state of deep thought vaporizes as I work it. What I am convinced is that information is a phenomenon worthy of our study and the domain can be demarcated. Further, if we "discipline" ourselves, we can begin to develop a conceptual structure. As in all the disciplines, that conceptual structure will evolve and face radical points of evolution over time. Today we are at a very primitive beginning with a few giants such as Claude Shannon and Alan Turing who have provided some first efforts at a conceptual structure.
And now we turn to the method of inquiry. There are two answers to this question. The first is a simple evolutionary answer. I think, again I would bow to my colleagues in History and Philosophy of Science, that most disciplines have evolved from an early period in which the primary mode of inquiry was simple observation and classification to a more evolved mode that was more formal and which enabled assessment of the validity of the conceptual model via replicable evaluation. For most sciences, this more formal method has become some variation of the scientific method. I suspect that the maturity of the science of information warrants a longer period of observation and classification to build a base of concepts that we may later be able to relate. I like Zipf's law, and Metcalfe's law, and the many others that are little more than observational science, but in academia, we are always driven to the more formal methods, and we "know" that the best are those of the old natural sciences. Herb Simon has suggested that might not be the most appropriate methodology, and I whole-heartedly agree.
In 1969, Herb Simon wrote “The Sciences of the Artificial” in which he discussed the differences between natural and artificial sciences. As I read the book, I am holding the second, 1981, edition, he was encouraging his colleagues to develop a new paradigm for conducting research in the “design sciences.” What is cogent in these remarks, I credit to Herb Simon. What is silly in my remarks, I take full responsibility for. Surely, this brief entry cannot do justice to the carefully reasoned arguments he posits in a little over 200 pages. Let me begin with two passages from the book:
My dictionary defines “artificial” as “Produced by art rather than nature; not genuine or natural; affected; not pertaining to the essence of matter.” It proposes, as synonyms: affected, factitious, manufactured, pretended, sham, simulated, spurious, trumped up, unnatural. As antonyms, it lists: actual, genuine, honest, natural, real, truthful, unaffected. Our language seems to reflect man’s deep distrust of his own products. I shall not try to assess the validity of that evaluation or explore the possible psychological roots. But you will have to understand me as using “artificial” in as neutral a sense as possible, as meaning man-made as opposed to natural. (2nd edition, page 6)
And:
… hence we can set the boundaries for sciences of the artificial:
- Artificial things are synthesized (though not always or usually with full forethought) by man.
- Artificial things may imitate appearances in natural things while lacking, in one or many respects, the reality of the latter.
- Artificial things can be characterized in terms of functions, goals, and adaptation.
- Artificial things are often discussed, particularly when they are being designed, in terms of imperatives as well as descriptives.(2nd edition, page 8)
In some sense, rereading his words for the fourth time in as many decades, I feel that there is little left to be said – he really has said it all. I firmly believe, as I have described in other posts, that information is an artifact of the human effort to communicate. If that is the case, information science is an artificial science, and not a natural science. Natural sciences endeavor to describe and explain the natural world around us and that natural world is a given. Artificial sciences endeavor to improve the design of the artifacts that we create. As Simon points out, talk about artificial anything and the sense is that it isn’t as good as the natural thing. Natural sweetener is obviously better than artificial sweetener. An artifact is a construct of human imagination. A science of artifacts or the artificial is a science of the things we build.
In academia, there is strong pressure to do good research. Many times this is equated to descriptive and explanatory research focused on the natural world around us. We can’t make a pulsar something it is not. We simple try to explain it. In their research, engineers would be like physicists and doctors would be like biologists. Maybe we need to rethink the paradigm of our science, more focused on the matter of our science – artifacts – than on the paradigms of those who study nature.
In a previous post, I talked about structured documents. These are not a product of nature, but things constructed by humans. We have the ability to define and redefine them so as to meet our needs to build systems of artifacts. For example, consider a stipulated definition that defines them as sequences of symbols. If we find that we can’t communicate what we wish to via the existing symbol set, we can change the symbol set. As another example, if we find a sequenced set of symbols does not provide adequate facility to manipulate and control the document, we can define document as a directed acyclic graph of elements over that symbol set. This might allow us to do partial locking and structural analysis. We could take the example further and introduce attributes and metadata to the model to give us additional capability. This kind of design science is very different from the descriptive natural science that says a document is what it is and it is our goal to describe it in its natural form.
In these examples, we are describing a science that changes the object of study so as to better achieve the design goals set for it. If our cars don’t provide adequate crash protection, we redesign them to provide better crash protection. Similarly, if buildings don’t survive earthquakes, we redesign them so that they will. If the structures and mechanisms by which we create and share information are inadequate, we need to build new structures that allow us to achieve our goals. I am reminded of the Serpent, who in Act 1 of George Bernard Shaw’s Back to Methuselah, says to Eve: “You see things; and you say 'Why?' But I dream things that never were; and I say 'Why not?'."