“Ingredients for Creating Disruptive Research Teams”, 2019-05-16 (; similar):
This post tries to answer the question of what qualities make some research teams more effective than others. I was particularly interested in learning more about “disruptive” research teams, ie. research teams that have an outsized impact on (1) the research landscape itself (eg. by paving the way for new fields or establishing a new paradigm), and/or (2) society at large (eg. by shaping technology or policy). However, I expect the conclusions to be somewhat relevant for all research teams…
Key findings: excellent researchers have individual qualities and diversity, with shared direction, purposeful vision, concrete goals, leadership, and no inconveniences. Their organizations emphasize autonomy & self-organization, organic decentralized collaboration (with possibly metrics, goal-setting, and incentives), spaces for interaction, shared physical space, shared ‘psychological spaces’ and forced interaction combined with psychological safety. Teams are small, seek external input and feedback, and value immaterial rewards.
…Based on the findings above, these are the most important takeaways for our research team at the Foundational Research Institute (FRI) as I see them: (1) We should continue to apply a high bar for hiring researchers…(2) Currently, we have staff who either excel at leadership or at research but nobody who combines both skill sets. We would likely benefit substantially from such an addition to our team…(3) We should continue to provide our research staff with as much freedom and operational support as possible…(4) Currently, many of our researchers work remotely which seems to have higher costs than I previously thought. As a consequence, I have become more convinced that we should try to create a research office geared toward the needs of our research staff…(5) We should invest more time into creating psychological safety for our research staff. I’m not yet sure how to best proceed here…(6) It was worth it to invest time into developing a theory of change, ie. thinking about how exactly our research would lead to real-world changes when it comes to AI designs and deployment…(7) Organizing research workshops with other organizations focused on similar questions is worth it. We should also look into other formats of high-intensity in-person interaction.
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