Research evolves over time through generally incremental changes punctuated by breakthroughs, culminations, and unforeseen outcomes. Our research will of necessity uncover substantial insights other than the primary research direction; from their study, larger principles, insights, techniques, or opportunities should accrue.

Complex systems are built from base foundations according to very elementary rules or transition⁺ laws; but the seemingly ‘deterministic’ nature of such foundations belies the ultimate intricacy and unpredictability of the research program (e.g., see Three Body+).

Computers are now taking an increasingly important (and controversial) role in both verifying and discovering new science, and so we stand on the threshold of a new dynamic where we produce and build results that are humanly unverifiable by even the combined effort of the research community, and the veracity of certain results may only be known with some degree of probability.

Science embodies the ability to verify, reproduce, and convince others of the veracity of our evidence, so the work of scientists is inherently incremental and precise.

Layers of depth or specialization can be pursued but they all must ultimately come up to a common layer and be essential facets of a single understanding. It is incumbent on each of us to work toward building an understanding of “big picture” issues from the perspective of our own disciplines and beyond.

The bigger question is how this view of science fits with industrial R&D? Any takers?

Highlights excerpted with permission from Foote.