  Evidence shows that in a significant number of cases the current methods of
research do not allow for reproducible and falsifiable procedures of scientific
investigation. As a consequence, the majority of critical decisions at all
levels, from personal investment choices to overreaching global policies, rely
on some variation of try-and-error and are mostly non-scientific by definition.
We lack transparency for procedures and evidence, proper explanation of market
events, predictability on effects, or identification of causes. There is no
clear demarcation of what is inherently scientific, and as a consequence, the
line between fake and genuine is blurred. This paper presents highlights of the
Theory of Enablers for Crowd-Based Scientific Investigation, or Theory of
Enablers for short. The Theory of Enablers assumes the use of a next-generation
investigative approach leveraging forces of human diversity, micro-specialized
crowds, and proper computer-assisted control methods associated with
accessibility, reproducibility, communication, and collaboration. This paper
defines the set of very specific cognitive and non-cognitive enablers for
crowd-based scientific investigation: methods of proof, large-scale
collaboration, and a domain-specific computational representation. These
enablers allow the application of procedures of structured scientific
investigation powered by crowds, a collective brain in which neurons are human
collaborators
