About the series
It is a pleasure and honor to be with you this afternoon at this very stimulating Forum. Early in my career I lived here in Budapest for some months while I taught at Szamok - a United Nations Development Program (UNDP) -supported training institute for 3rd world computer professionals. I have remained in touch with some of the friends I made here almost 30 years ago, and have a fondness for Budapest, so it is a special pleasure for me to be here today.
This afternoon we will discuss some aspects of the connections among information, knowledge, and society. There are obviously a multitude of things that can be said on this subject and my colleagues and I will only be able to scratch the surface of the topic. Their talks and our discussions with you, the audience, will explore only a few of the many topics of relevance.
In the few minutes I have, I want to focus on how science and technology in an information-based society can lead to new knowledge and, in particular, how new, ICT-based techniques can be both very powerful and potentially very problematic.
Science and technology have become a major – perhaps dominant – means of developing formal and systematic knowledge in much of the world today, but it has not always been that way. To provide some context for my main point this afternoon, I think it will be useful to begin with a very cursory historical review.
In ancient times, while there was certainly some activity that one could recognize as similar to modern science (the geometers of Egypt, the astronomical observations of the Babylonians, and the untutored observations of nature by many), we can say that there was little “science” in the modern sense at least up to the year 1000 in the CE. Knowledge was informal, often mythical, and except in very restricted ways, not used as the basis for building and operating society.
Around 1000 and up to about 1600, science – and thus the knowledge it produced – was mostly observational. That form of science, which, of course, is still practiced today, laid the foundation for later modalities. Society began to scientifically organize the development of knowledge that was needed for practical purposes – for example, navigation – in ways that rapidly changed society.
An extremely important technological development in the 1400’s was the development of the movable type printing press – the Gutenberg bible was printed in 1454. This, of course, was essential to the dissemination of knowledge, including scientific knowledge. More about this later.
Starting around 1600 – William Gilbert’s book on the laws of magnetism is an example – we begin to see the emergence of empirical science in which experiments are posited and carried out to develop needed knowledge that could not be directly observed. This permitted some of the relationships between effects or events, for example, to be determined. This knowledge, in turn, became increasingly important to society.
Not long afterwards – Newton’s Principia Mathematica in 1686 is a good example – theoretical science started to develop. Theories, once validated by observation and experimentation, then permitted us to make predictions, to explain a large number of observations by a single, compact theory, and to create knowledge that was much more general.
Until quite recently then, science produced knowledge by one of these three means – observation, experimentation, or theorizing. The growth of the importance of science and technology in our societies – because of their power to ultimately produce useful knowledge – has grown exponentially over the past 400 years, primarily because we have learned to apply these discovery modalities with great skill and we have learned to build on previous knowledge very skillfully. We have gotten to be very good at science, but how we do it has not fundamentally changed.
Design can be viewed as another approach to generating and using knowledge and information. Design is a process of synthesis that may use scientific knowledge, but it also incorporates artistic, esthetic, and creative knowledge to produce new artifacts. One could argue that designing mechanisms and artifacts, whether in an engineering or an architectural process, is another mode of developing knowledge. It is certainly the case that these processes do
A new building design, for example, provides by example the knowledge for other designers to copy and evolve. And a new manufacturing process that is created by engineers creates a new standard and way of doing things for other engineers to utilize. How "design" relates to "science" is an interesting area for exploration that I have long been interested in, which I leave today for you to consider further.
In 1953, Enrico Fermi, John Pasta, and Stanley Ulam performed what may have been the first computer experiment. To study entropy, they created a virtual world to study vibrations in an atomic lattice. In the 50 years since, this mode of scientific enquiry – simulation on a computer - has grown to be an extremely important element in the toolkit of scientists because of its ability to permit us to develop knowledge about things that cannot be directly observed or experimented with or dealt with by compact theories.
As a personal aside – to illustrate how rapidly science is progressing – my position at the US National Science Foundation is a direct descendent of the position that John Pasta later held and I recall as a young professor interacting briefly with him in the process of applying for funding for my research.
Thus, after 400 years we have added a new form of scientific discovery – computational – which is now rapidly becoming extremely important, if not dominant, in many fields of science. This mode of knowledge creation is certainly speeding the development of the information-based society directly through the rapid expansion of scientific knowledge. As so often happens, the techniques first used in science – simulation in this case – are rapidly picked up and used for many other purposes ranging from predicting share prices to providing entertainment via electronic games!
It appears now that yet another mode of creating scientific knowledge is emerging. We are still too close to events to pick a specific event like the Fermi, Pasta, Ulam simulation as the "first instance," but I can provide an example that may be one of the first.
There is an effort, funded by the NSF and others, to create a "National Virtual Observatory (NVO)" that will eventually contain all of the data that is available to astronomers. Simply creating such a large collection of data and providing the means for searching it and comparing different forms of astronomical observations, while challenging, is not in and of itself a new form of science.
But, what one of the collaborators on this project – Dr. Jim Gray – observes is that scientists are using this data collection in new ways. Instead of just looking up specific facts, they are using the NVO to make correlations, observe trends in the data (not directly in nature), and in short, developing scientific results not through observation, experimentation, theorizing, or simulation, but through informatic operations – what we might call "informational science."
I should note that the astronomer leading this project is Dr. Alex Szalay of the Johns Hopkins University in Baltimore. He was born here in Budapest and may be better known to some of you as an original member of the music group Penta Rhei!
Again, I must leave for discussion and future validation whether or not this is a new form of scientific creation of knowledge, but there is no doubt that it is producing new knowledge in ways that none of the other forms of scientific discovery are capable of doing.
There is a form of this informational approach – one in which knowledge is developed not by any of the usual means but by making observations of online information – which is already in heavy use by some commercial firms to discover patterns in consumer behavior that may be useful in targeting advertising, adjusting production levels, or even predicting future behavior. The term "data mining" covers some of this, but other means may also be employed.
I think that we should view this as the “first derivative” of observation since it is properly seen as observations on observations. While this is not new in and of itself, the power of the computer to be able to do this over truly huge collections of information, widely distributed, and in a very short time, provides essentially new capabilities. In turn, this suggests to me that we must be prepared to encounter other, new forms of discovery that have not yet been conceived of.
In an information-based society in which there is often an electronic record of a large part of the activity of every person – and, especially, when you consider that these records can be searched rapidly and in a widely integrated manner, and particularized to an individual – then it is possible to create knowledge about an individual (as well as a group) from this electronic record and without the knowledge of the individual.
Let me draw together the several themes I have touched on today to assert that modern computational and communicational capabilities are fundamentally changing science. Further, they are at the same time revolutionizing the dissemination of science and, indeed, often doing both at the same time. We have not even begun to glimpse what this means for the production and dissemination of scientific knowledge and its usage by an information-based society.
I will close by observing what I hope is obvious: This new form of knowledge creation provides a powerful tool for doing good (e.g. warning an individual when it appears that their health is failing) as well as for doing harm (e.g. tracking the actions of an individual in order to exploit them financially).
So, as we consider just what an information-based society is and how knowledge is created in it, I would claim that understanding knowledge creation and dissemination in the context of science first will help us understand better the broader implications for society.