Better than Best: Epistemic Landscapes and Diversity of Practice in Science

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Submission Summary
When solving a complex problem in a group, should we always choose the best available solution? In this paper, I build simulation models to show that, surprisingly, a group of agents who randomly follow a better available solution than their own can end up outperforming a group of agents who follow the best available solution. The reason for this relates to the concept of transient diversity in science (Zollman 2010). In my models, the “better” strategy preserves a diversity of practice for some time, so agents can sufficiently try out a range of solutions before settling down. The “best” strategy, in contrast, may lock the group in a suboptimal position that prevents further exploration. In a slogan, “better” beats “best.”
My models are adapted from Lazer and Friedman (2007)’s model where a network of agents is tasked to solve an NK landscape problem. Here, agents search in a solution space with multiple “peaks.” They only have knowledge of their neighbor’s solutions, as well as (sometimes) the results of limited local exploration, so they may fail to ever discover the global optimal solution(s). The NK landscape model can be fruitfully applied to cultural innovation and problem solving, especially to complex problems where optimal solutions are not readily accessible from all starting points. Besides, NK landscape models are more general and realistic than other epistemic landscape models (e.g. Weisberg and Muldoon (2009)), due to their ability to represent multi-dimensional and interconnected solutions (Alexander et al. 2015).
My result of “better” beating “best” has several implications in social epistemology. First, this is another instance of the Independence Thesis, which states that individual and group decision-making can come apart (Mayo-Wilson et al. 2011). In my models, every round, an agent’s epistemic gain when they follow the “better” strategy is no greater than when they follow the “best” strategy, yet, they have greater long-term gain in a social setting.
Second, Zollman (2007, 2010) and Lazer and Friedman (2007) previously showed that a less connected community is more likely to arrive at superior beliefs or solutions, due to the transient diversity present. But limiting connectivity for the gain of diversity of practice may be too costly or impractical (Rosenstock et al. 2015). My result suggests that we can achieve comparable benefits if instead people choose “better.” Indeed, a completely connected group that follows the “better” strategy can outperform a very sparsely connected group that follows the “best” strategy.
Finally, insofar as some approaches to a problem are associated with particular social groups (Longino 1990; Fehr 2011), the “better” strategy also makes it more likely to preserve solutions arising from marginalized perspectives. These solutions may not be the most optimal at a given time, perhaps due to a historical lack of resources, but may nevertheless become promising after further explorations.
Alexander, J. M., Himmelreich, J., and Thompson, C. (2015). Epistemic Landscapes, Optimal Search, and The Division of Cognitive Labor. Philosophy of Science, 82(3):424–453.
Fehr, C. (2011). What is in It for Me? The Benefits of Diversity in Scientific Communities. In Feminist Epistemology And Philosophy Of Science, pages 133– 155. Springer.
Lazer, D. and Friedman, A. (2007). The Network Structure of Exploration and Exploitation. Administrative Science Quarterly, 52(4):667–694.
Longino, H. E. (1990). Science as Social Knowledge: Values and Objectivity in Scientific Inquiry. Princeton University Press.
Mayo-Wilson, C., Zollman, K. J., & Danks, D. (2011). The Independence Thesis: When Individual and Social Epistemology Diverge. Philosophy of Science, 78(4), 653-677.
Rosenstock, S., Bruner, J., & O’Connor, C. (2017). In Epistemic Networks, is Less Really More?. Philosophy of Science, 84(2), 234-252.
Weisberg, M. and Muldoon, R. (2009). Epistemic Landscapes and the Division of Cognitive Labor. Philosophy of Science, 76(2):225–252.
Zollman, K. J. (2007). The Communication Structure of Epistemic Communities. Philosophy of Science, 74(5):574–587. Zollman, K. J. (2010). The Epistemic Benefit of Transient Diversity. Erkenntnis, 72(1):17.
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University of California, Irvine

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