DOI
doi: 10.1111/j.1467-9248.2011.00901.x

Summary
The article represents a further analysis and critique of a previous paper about complexity written by Ian Sanderson (2009). In his article, Sanderson advocated for the adoption of Complex Theory in the Political science in order to avoid the mistakes and errors generated by linear and normative analyses, favoring a more “pragmatic” methodology based on adopting “what works”. This article does not challenge the main claim of Sanderson’s point of view, about the need to refuse linear analysis. Instead, it further enlarges this perspective, pointing to the fact that complex systems’ insights also challenge the kind of pragmatic model proposed by Sanderson, as it forces policy makers and scholars to accept the fact that errors and failure in political analysis and policymaking are inevitable. Starting from an analysis of the work of Michael Freeden on failure and Michel Foucault on error, Little demonstrates that by refusing epistemological certainty, policy makers can fruitfully adopt Complexity Theory to boost creativity, innovation and less risk-adverse forms of political action.

Relevance for Complex Systems Knowledge
Although this article does not directly discuss complex systems and complexity theory concepts (it does so only partially), it provides an interesting and fundamental perspective on how complex systems’ effects on social sciences should be understood. The aim of this paper is not to criticize complex systems theory, which well accepted and welcomed by the author, but to challenge our aversion for risk and failure. By accepting the inevitability of failure and error, Little establish a claim for accepting the epistemological limitations of our ideologies and traditional mental schemes.

Point of Strength
The main point of strength of this article is that it provides a different kind of contribution about complexity theory, one which is more related to epistemological, philosophical stances, instead of more scientific point of views. This is a very much needed analysis, as it problematizes how complex systems tools and concepts should be used.