Deep transdisciplinary thinking challenges many presumptions of straightforward multi-disciplinary collaboration. Situations are mapped in lieu of problems being formed, expertise is networked in lieu of collaborative teams being defined, and systemic interventions are proposed in lieu of solutions being offered. This requires unique collaborative methods, techniques of creative and critical thinking, and tools and systems for visualization and intervention. This is the foundation of Thinklab.
Limits to use are a function of knowledge about and interface to these tools and techniques
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(e.g., they often remain within the disciplinary domains within which they were
developed: social networking, library archiving, ‘big data’ analysis techniques,
intelligence analysis, digital humanities, gaming, etc.).
Environmental/spatial/situated configuration and assembly of the tools is a critical component of the ‘knowledge and interface’ function
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(i.e., how readily available and intuitive the tools and techniques are in a given work
environment plays a huge role in how willing we are to employ them, who can use them, who gets
to ‘drive,’ etc.).
Computational tools allow geographically dispersed and synchronous/asynchronous work to be indexed and archived in common, linkable structures, even as recording formats and data may be highly format-divergent or incomplete
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(e.g., common collaboration tools, RDF linkable data formats, neural computational
systems, natural user interfaces).
Recording, indexing, and ultimately tracing relationships among various “marks” and “markers” left by individuals, contexts, projects, etc. is the key to building knowledge with this archive
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(e.g. marks include voice; marks with pens, both digital and analog; images, still and moving; files
and documents, etc.).
Such an archive, active and dynamic, with properly structured interfaces to it, can greatly enhance collective intelligence on complex situations.