Maintaining intellectual diversity in data science

Abstract

Editor: Tobias Kuhn (https://orcid.org/0000-0002-1267-0234) Solicited reviews: Jodi Schneider (https://orcid.org/0000-0002-5098-5667); Melissa Haendel (https://orcid.org/0000-0001-9114-8737); Bjarke Mønsted (https://orcid.org/0000-0003-3683-312X); Victor de Boer (https://orcid.org/0000-0001-9079-039X) Received 5 March 2017 Accepted 28 March 2017Abstract. Data science is a young and rapidly expanding field, but one which has already experienced several waves of temporarily-ubiquitous methodological fashions. In this paper we argue that a diversity of ideas and methodologies is crucial for the long term success of the data science community. Towards the goal of a healthy, diverse ecosystem of different statistical models and approaches, we review how ideas spread in the scientific community and the role of incentives in influencing which research ideas scientists pursue. We conclude with suggestions for how universities, research funders and other actors in the data science community can help to maintain a rich, eclectic statistical environment.

Collective decision-making under changing social environments among agents adapted to sparse connectivity

“…The potential endogenous reduction in decision-making efficacy identified above has political implications in an age of ubiquitous online connectivity, but should also be a source of concern in an increasingly-connected scientific community (Mann and Woolley-Meza, 2017). Societies that have recently experienced large increases in connectivity may also be more vulnerable to exogenous misinformation (e.g.…”

“…Living in groups provides many advantages to social animals (Krause and Ruxton, 2002), including the opportunity to make use of ‘social information’ to improve the quality of decision-making (Ward et al, 2011; Wolf et al, 2013). Choices made by others are often a useful indicator of which option is best for oneself; if one trusts that others are acting rationally (Mann, 2018), and that they have similar preferences to oneself (Mann, 2020), then their decisions provide valuable clues about the quality of different options.…”

Collective decision-making under changing social environments among agents adapted to sparse connectivity

“…The potential endogenous reduction in decision-making efficacy identified above has political implications in an age of ubiquitous online connectivity, but should also be a source of concern in an increasingly-connected scientific community [51]. Societies that have recently experienced large increases in connectivity may also be more vulnerable to exogenous misinformation (e.g.…”

The functional aspects of selective exposure for collective decision-making under social influence

“…Contrary to this near-unanimous belief prevailing in political research and other areas, fragmented structures—more generally modular structures—in which individuals are tightly connected to others with similar traits and form cohesive local clusters, are known to be beneficial for maintaining diversity and enhancing groups’ ability to survive and adapt in hostile and uncertain environments 7 , 58 , 67 – 72 . Along these lines, Kao and Couzin 39 investigate the effects of modular structures on collective decisions, although neither opinion updates nor endogenous changes in network structure are taken into account.…”

“…Pescetelli et al 73 provide empirical evidence directly supporting this view, showing that modular groups composed of small independent subgroups consistently outperform non-modular groups in real-world forecast problems. Along with this line, Mann and Woolley-Meza 7 underscore the importance of modular structures in retaining intellectual diversity and fostering the generation of new knowledge within academic communities. This can be achieved by maintaining a basic level of isolation and independence between subfields and thereby preventing the dominance of specific models and methods.…”