Tomorrow’s Universities and the Seven Pillars of the Knowledge Revolution

The emerging Knowledge Revolution goes beyond the changing technologies and the challenges and opportunities they create to include the structure of knowledge and how it is transmitted inter-generationally and across countries. There are seven major features of that profound transformation, which I call “The Seven Pillars of the New Knowledge Revolution”. These are: (i) Parsing, Life & Organization; (ii) Image & Text; (iii) Humans & Machines; (iv) Complexity & Chaos; (v) Computation & Research; (vi) Convergence & Transformation; and (vii) Pluridisciplinarity & Policy. This diagnosis has profound implications on how one should think about the design and management of our institutions of learning, starting not only with universities, but also the school system, as well as our research institutions (whether in universities or in public and private labs), and the supporting institutions of knowledge (like museums, libraries and archives). Radical proposals are advanced for the content, method, participants and organizational setting of education, as well as the role of the University as mediator of transitions, its relationship with society and economy, as well as its physical presence, governance structure and the values it should promote. Core functions and curricula for the future, along with the possibility of a global university consortium, are discussed.

1. Introduction
We all agree that we are moving rapidly towards the knowledge based society and the technology based economy, with the well-known and well-documented aspects of globalization overlaid on this transformation. Here, I am speaking of the structure and presentation of knowledge and how we humans will most likely be interacting with knowledge, whether we are academics or researchers or simply the descendants of those who used to go to public libraries and ask the librarian for assistance with a good book to read or a reference source for the paper they are preparing for college. This knowledge revolution shall have profound implications for the institutions of education from kindergarten through post-doctoral levels, research, whether public or private, and the cultural institutions that support our knowledge structure such as libraries, archives and museums.

It is this that I refer to as the “New Knowledge Revolution”, a subject I have treated elsewhere at length and in more technical detail.1 This knowledge revolution can be diagnosed by seven key characteristics, which I would like to call “pillars”, and which I shall briefly describe here. These are:

  • Parsing, Life & Organization
  • Image & Text
  • Humans & Machines
  • Complexity & Chaos
  • Computation & Research
  • Convergence & Transformation
  • Pluridisciplinarity & Policy

Before proceeding to discuss the manner in which I think this revolution will specifically impact the universities of tomorrow, and making some recommendations as to how that inevitable transformation could be handled to smooth out the change and embrace the future, a brief word about each of these seven pillars is pertinent here.

2. The Seven Pillars of the New Knowledge Revolution

2.1. Parsing, Life & Organization
Since the beginning of time, whether we were writing on scrolls or on codexes, whether the codexes were printed or in the form of manuscripts, the accumulation of knowledge has been based on parsed structures, with units put next to each other like bricks in a wall of an emerging structure.

It was the juxtaposition of these individual parsed works that created the accumulation of knowledge… the rising edifice built piece by piece, brick by brick or stone by stone…

In addition, each piece was “dead”. By that I mean that once published it stayed as it was until a second edition would appear. If we both had copies of the same book, we could both open to, say, page 157 and find exactly the same thing in our respective copies. It did not change whether we did it immediately after the book appeared or decades later.

The Internet changed all that…

The web page became the unit of parsing. Instead of the classical sequence of presentation, we now think in terms of a home page and then hypertext links into other related documents. We can expect more fluidity into the merging of image, both still and video, and the transitions from one reference link into another.

Search engines complement the World Wide Web as the online material – unlike the traditionally published material – becomes alive. Today if I look up a web page, and you look it up at the same location a few hours later, it will probably have changed, since the material is constantly being updated.

Furthermore, as we move beyond the current structures of the web towards the semantic web, where we can search for relationships and concepts and not just objects, the structure of organization and presentation of knowledge will become one large interconnected vibrant living tissue of concepts, ideas and facts that is growing exponentially and which will require new modes of thinking to interact with it. It will automatically spawn these new modes of thinking and scholarship will no longer be parsed like bricks in a wall; it will be more like a smooth fluid flowing river.

If we were to try to take into account the emergence of the social linkages phenomena that the internet and the web have now made possible, we can now visualize what some specialists have called the “Meta-Web”, which is attributed to high knowledge connectivity and high social connectivity. Does the Meta-Web prefigure the connectivity of intelligence?

2.2. Image & Text
Throughout history, the primary means for the transmission of information has been text. Images were difficult to produce and to reproduce. This has changed. With the digital revolution, everybody can record images and video, and computer generated graphics are becoming affordable for everybody.

The human brain can process visual information with incredible rapidity. Enormous detail can be captured and processed in a fraction of a second. So some new features of the current knowledge revolution appear imminent. One is the far larger reliance on image – in addition to text – in the communication of information and knowledge and the changing forms of the storage and retrieval devices that this will require as we move from text dependent book and journal to digital still and video image presentations as well as three dimensional virtual reality and holographic presentations. Interactivity will also become a feature of this new image-based virtual-reality world. Again what does that mean in terms of the presentation, the search and retrieval functions and the interaction between the researcher and the material in the future?

And what does this mean for the effective description in meta-data, the storage, searchability and retrievability of this enormous and growing world of still and moving images, both fixed and interactive? We will no longer be looking up images through keywords entered into text databases such as meta-data catalogues: Computers will do this for us.

2.3. Humans & Machines
With the exception of pure mathematics and some aspects of philosophy, it will no longer be possible for any human to search for, find and retrieve, and then manipulate knowledge in any field, much less add to it and communicate their own contribution, without the intermediation of machines. Even in literary criticism and the social sciences, the stock of material to search through can no longer be done manually.

This is not good or bad. It just is.

Now, after a special chess playing program called Big Blue of IBM defeated world champion Garry Kasparov in Chess in 1997, can we indeed ask, as some visionaries are doing, whether “consciousness” and “intelligence” are emanating qualities from very complex systems? According to some, we are going to witness that happening with machines when they will pass certain thresholds of complexity and power, such as when the level of the processing power reaches certain sizes, and software advances within a decade or so after that to certain levels, all of which are likely to happen within the first half of the 21st century.

But whatever the merits of that particular debate and its ramifications, it is clear that changes are already noticeable in the domain of libraries and the internet. One example of that is the new World Digital Library: The system allows one to link video, image text and commentary and maps into one seamless whole and to search by many different approaches (time, geography, theme, cluster, or even by a single word) and browse the material as well as find what one wants from the digitized material on offer from all the countries of the world.

2.4. Complexity And Chaos
The world we live in is remarkably complex. The socio-economic transactions of a globalizing world are exceedingly intricate as, with the click of a mouse and the flight of an electron, billions of dollars move around the planet at the speed of light. The web of interconnected transactions is enormous, and the ripple effects of any single set of actions and its interaction with other effects are difficult to predict.

Our cities have become not only much larger but also much more complex, and ecosystems are not only delicate, they are intrinsically very intricate. So are biological systems.

The reality is complex and chaotic, meaning that complex systems have non-linear feedback loops that result in systems and subsystems that are extremely difficult to predict. Many of our models, based on the simple mathematics and analogies drawn from physics, are proving inadequate.

2.5. Computation & Research
Till now, Computing has been largely seen as the extension of a large calculating machine that can do dumb calculations at incredible speeds. Computer scientists and engineers were implementers who made the life of the creative people and the researchers less tedious. Wonderful tools, no doubt, but just tools all the same. Today, the concepts and the techniques of computing will become a central part of the new research paradigm. Computational Science concepts, tools and theorems will weave into the very fabric of science and scientific practice.

Consider data management. Data when organized becomes information. Information when explained becomes knowledge. That, in turn, when coupled with reflection, insight, and experience may lead to wisdom, but that is another story.

But beyond the scale and magnitude of the collections of data, we are looking for connections between collections of data. These pose particular problems that involve qualitatively different issues. Computer science is where the most work on such classes of problems has been done.

2.6. Convergence & Transformation
Domains are gradually converging. In simplest terms, once upon a time we had chemistry and biology as distinct and separate enterprises, now we have biochemistry. Such moments of convergence, generating new sciences and insights, turn out to be some of the most fecund moments in the evolution of our knowledge and the development of our technologies. Today we are witnessing the convergence of three hitherto separate fields with the birth of BINT: Bio / Info / Nano Technology.

At the same time, we need to develop what the NSF calls “Transformative Research”. That is, research capable of changing the paradigm in some fields and domains, such as synthetic biology and femtochemistry. Such research is extremely valuable. We thus witnessed the discovery of the structure and mechanism of DNA engendered fields like genomics, proteomics and metabolomics.

A question before us is whether such developments will remain serendipitous or our research paradigm will systematically force the development of such converging domains and transformative insights. I believe we are poised to do the latter.

2.7. Pluridisciplinarity & Policy
There is real value in crossing disciplines. Both in academic organization and in tackling real-life problems, we note that the old “silos” of disciplines when functioning alone are counterproductive. Much of the most interesting work is being done in between the disciplines, where they intersect or where there are gaps.

We increasingly recognize that our real life problems, such as poverty, gender or the environment, are all multi-dimensional and complex and require a special way of organizing all the various disciplinary inputs. Just as we say that diversity is enriching, so is the sharing of knowledge across disciplines.

The nature of the challenge, its scale and complexity, require that many people have interactional expertise to improve their efficiency working across multiple disciplines as well as within the new interdisciplinary area.

* A slightly different version of this material was presented at the meeting of the International Association of Universities (IAU) in Puerto Rico on 28 November 2012.
1 Ismail Serageldin, The Seven Pillars of the Knowledge Revolution (Alexandria: Bibliotheca Alexandrina, 2010). That material was based on a distinguished lecture delivered by the author at the NSF in Washington in 2010.

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