“…Fundamentally, our understanding of the world changes. Where once we saw
clockworks mechanisms, we now see self-organization and nested hierarchies
characterized by evolution and emergence, attractors, rapid change, and flips. In the
old way of seeing, cause and effect can be neatly separated; with complexity,
feedback loops dominate, and effects are also causes. A complicated system can still,
in principle, be predictable; a complex one is irreducibly uncertain. (…) Under
conditions of complexity, science can arrive at a set of answers that are not even
probably correct but are only, at best, possibly correct. These fundamental changes
in understanding have implications for practice. Under conditions of complexity, our
framing of the situation changes from one (correct) perspective to multiple
perspectives and scales. Our explanations shift from linear cause-effect models to
narratives about self-organization, attractors, cannons, and propensities.”
“Investigators into complexity do not seek prediction, control, right answers, or
efficiency. (…) Rather, the investigators seek understanding, adaptability, and
resilience. Scientific inquiry, more than ever, became an act of collaborative learning
and knowledge integration. The role of the experts shifts from problem solving to an
exploration of possibilities and from giving correct advice to sharing information
about options and trade-offs. Because there is no correct answer and no definitive
perspective, decision making under conditions of complexity must be broadly
participatory. Management shifts from top-down command and control to
collaboration and encouragement of self-organization about desired attractors. We
can no longer manage nature nor can we manage people because we ourselves are
all part of this fundamental complexity. The best we can do is to anticipate what
might happen and nurture adaptive interactions with the systems in which we are
embedded. We can no longer fall back on quantitative measures of correctness, on
“just the fact”, or on our rigorous ability to solve problems and avoid surprises.
However… the quality of our information can still be (vigorously) assessed, according
to its fitness for the purposes we have chosen. Quality control thus requires an
understanding of the possibilities open to us, a consideration of different
perspectives, and an ability to adapt and cope with surprises on the path we have
chosen. The key difference from normal science is that our community of peers is
enlarged to include a much wider array of epistemological communities.
Given all this changes, we are faced with some serious challenges…”

James J. Kay; ‘The Eco System Approach’, 2008