iSchools: Contemporary Information Technology Theory Studies

The perfect merger of academic rigor and contemporary thinking has come together in the concept of iSchools, which give practical consideration and interesting learning opportunities to the most relevant issue of our time: information. So far there are over 50 worldwide iSchools; a global pool, like bitcoin for academia. The March 2014 conference was held in Berlin and the March 2015 conference will be at UC Irvine. With higher education under reinvention pressure from all directions, the possibility of making institutional learning relevant again cannot be underscored enough.

iSchools are the perfect venue to take up not just the practical agenda within the information technology field but also the theoretical, philosophical, and societal dimensions of the impact of information technology. There have started to be some conferences regarding ‘big data theory’ (Theory of Big Data, University College London, Jan 2015), and a calling out of the need for ‘big data theory’ (Big Data Needs a Big Theory to Go with It, Scientific American, Rise of Big Data underscores need for theory, Science News). These efforts are good, but mostly concern having theory to explain the internal operations of the field, not its greater societal and philosophical effect. In addition to how ‘big data theory’ is currently being conceptualized, an explicit consideration of the general theoretical and social impact of information technology is needed. Floridi’s distinction re: philosophy of information is apt; the main focus is how the field changes society, not the internecine methods of the field.

Research Agenda:
Contemporary Information Technology Theory Studies 
Here is a thumbnail sketch of a research agenda for Contemporary Information Technology Theory Studies. Early examples of topics taken up at institutes and think tanks (like Data&Society) are a good start and should be expanded and included in the academic setting. A more appropriately robust agenda will consider the broad theoretical, social, and philosophical impact of the classes of information technology below that are dramatically reshaping the world, including specifically how our ideas of self and world, and future possibilities are changing.

• Big Data (big data, smart data, personal data, group data)  
• Blockchain Technology (Institute for Blockchain Studies) 
• The Brain as an Information Technology (computational neuroscience, connectome, in-silico simulation, cognitive enhancement) 
• Smartcity, Connected World, Self-driving Vehicles 

Obtaining models for singularity futures thinking

The challenge is called out by science fiction writer Vernor Vinge as being related to the technological singularity, namely that any one future technology change could be so fundamental across all aspects of life that it is hard to write plausible science fiction, and more generally impacts how we think about the modern and future world. Any next node that has sufficient transformative power (e.g.; like the internet) could change things so fundamentally, globally, multi-dimensionally, and quickly that its impact would be essentially beyond cognition. Moreover, while there are some potential candidates visible for the ‘next internet’ such as smartphones, 3D printing, biotechnology, nanotechnology, and robotics, the real next node is likely to be an unforeseen discontinuity.

Comprehensive survey of thinking models
There is a paucity of models for thinking comprehensively and critically about the future in rigorous, sophisticated, justifiable, and transferable ways. A project that should be undertaken if not done so already is an examination of different models for structuring thinking from different disciplines. There is value in this at two levels: first generally in identifying, characterizing, and synthesizing different models for structuring thinking, and second in applying these models cross-disciplinarily to existing areas, and to new areas such as thinking about the future.

Eliciting explicit models for structuring thinking
The models that are used to structure thinking in different fields need to be made explicit. Practitioners immersed in fields may not be easily disposed to articulate these models. For example, it may be novel to inquire ‘What is the model for inquiry in this field?’ or even to have the concepts and vocabulary for explicating them.

Fields with models for structuring thinking
Some of the obvious fields to investigate for eliciting established models for structuring thinking are philosophy, complexity (complex adaptive systems, chaos theory, symmetry, etc.), computing (artificial intelligence, machine learning, knowledge representation, data management, etc.), systems-level disciplines (ecology, biology, cosmology, etc.), and social sciences (sociology, anthropology, economics, etc.).

The challenge of fishing structure and content from academic fields
Some of the immediate obvious barriers in accessing models for structuring thinking from academic disciplines are nomenclature and insularity. Semantic and conceptual nomenclature may prevent easy access to fields, but are largely a veneer that may be penetrated with a variety of translation techniques and concept mapping. Much more problematic is the potential lack of available suitable content in these fields. By default, many areas of academia are not externally-focused applied disciplines but rather inwardly-focused insular disciplines engaged in cataloging and interpreting the thoughts of their own ancestral brethren. The accompanying applied dimension to every field that would explicitly render the core ideas accessible, and proven and useful through deployment seems to be absent from many fields. Rather than being perceived as less pure of an exploit, the application of the central ideas and structures would seem to be a key raison d'être for these fields of knowledge.