In evidence-based medicine, randomized controlled trials are said to be the highest evidence of what works, while anecdotes have low value or are not even considered to be medical evidence. Similar hierarchical views of evidence have infected other disciplines, including evidence-based education and evidence-based government. Here, I explore the artificial divisions of acceptable from unacceptable evidence, numbers from narrative and sciences from humanities. I challenge the deprecation of stories in medicine. Some stories are based on experiments while others are based on more or less plausible theories. Some stories offer vast and impressive statistics gathered from many observations while others present one noteworthy event. Published reports are themselves stories of what experimenters did. Systematic reviewers generate their own observations of collected stories of experiments. Reviewers of systematic reviews in turn report their observations of systematic reviews. All of these stories become evidence of what works in medicine.

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In this article, the author proposes a dynamic, interdisciplinary, network conception of expertise that differs from conventional static, linear conceptions. Using a range of graphic images, the author propose specific visualizations of this network conception of expertise. First, he discusses attempts to pin expertise down in a definition. Then he considers the network of notions from which expertise emerges. The author briefly describes representative nodes in the network, such as experience and excellence. He concludes with the view that there is no need to compromise the many existing conceptions of expertise by forcing them into a false common ground. Instead, he shows that existing accounts of expertise can be better understood by viewing them as connected parts of a complex network.

With examples from signal theory and decision theory, the literature search is analyzed in light of fundamental limits in the nature of informaiton. You can run from expertise but you cannot hide. Expertise is inevitably required to deal with these errors. So do-it-yourself searching is inadequate in the absence of expertise. The best decisions result from collaboration with subject matter experts and decision-making experts.