The Atlas of Social Complexity. Chapter 3: The Thirteen Situations

 

As we mentioned in our previous blog post on Chapter 2 of the Atlas, the study of social complexity is up against thirteen situations that are holding it back from evolving into the truly disruptive transdisciplinary science it has sought over the last three decades to become.

 

The 24+ areas of research we review in the rest of the book are, in one way or another, using the social science turn and a social complexity imagination to get past these situations. Some more so than others, but nonetheless, that is the goal. The purpose of is to outline these thirteen situations.

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ABSTRACT:  

This chapter is key for all readers as it outlines the thirteen challenges that the study of social complexity must address to advance as a transdisciplinary disruptive science -- see Table below for the list. 

 

These situations range from ignoring the social sciences and qualitative methods, to treating computational models and simulation as the holy grail to all things socially complex, to failing to address issues of power and inequality in systems, to being tone-deaf about the real world. 

 

By understanding these situations, readers will gain a strong sense of the innovations and advances numerous fields we survey in the Atlas make to overcome those thirteen situations. This chapter works in conjunction with the critical history of Chapter 2.

 

KEY WORDS: philosophy of complexity, history of complexity science, sociology of science, map of complexity, policy and complexity, coming crisis of empirical social science. 

 

Situation	Characteristics
1. No philosophy of complexity	=Few attempts to define an epistemology and ontology for social complexity
2. A failure to engage the wider social sciences	=Assumption that the social sciences can be ignored because the complexity sciences would offer superior insights
3. Reinventing the wheel	=Reinventing existing insights from the social sciences that are then presented as new insights
4. Old words, new words	=Rebranding existing insights using terms from the complexity sciences
5. Obscurantism and mystification	=Scientific overreach and complicated jargon combine to suggest that life’s biggest questions are uncovered
6. Forgetting multilevel thinking and modelling	=Despite the transdisciplinary approach of social complexity, almost all research focuses on a single level of analysis.
7. Technique in the absence of theory	=Focus on computational methods and big data pushes social theory out of sight
8. Learning tools vs. predictive machines	=The ability to learn from simulations is replaced by a desire to predict and control social complexity
9. Minor role of qualitative research	=Dominance of quantitative research and quantification of data established a blind spot for qualitative data and methods
10. Methodological closing of social scientific mind	=Shying away from advances in computational methods sees many social scientists becoming illiterate with such methods
11. The dire sound of technicalities	=Going into a spiral of ever-smaller technical refinement while losing the bigger picture out of sight.
12. Being tone-deaf about the real world	=Advanced analyses are coupled to crude recommendations that fail to appreciate the complexity in the target domain
13. Practice does not make perfect	=Pragmatic and rushed adoption of the complexity sciences by practitioners constitutes verbal detritus